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the events that compromise the produced alerts of the monitored services travel through The Argo Messaging Service. Through its supplementary tool, the argo-ams-library a client can access the source directly and inspect the events, process them and even create its own downward syncs.Although its recommended to use the library to interact with the messaging service, you can also use plain HTTP requests.","s":"Process events/alerts directly from the source(AMS)","u":"/argo-monitoring/docs/guides/AMS-consume-publish-events","h":"","p":1},{"i":4,"t":"# set up the ams client ams_host = \"{0}:{1}\".format(\"example.com\", str(443)) ams = ArgoMessagingService(endpoint=ams_host, project=\"test\", token=\"secr3t\")","s":"Initialising a connection","u":"/argo-monitoring/docs/guides/AMS-consume-publish-events","h":"#initialising-a-connection","p":1},{"i":6,"t":"Topics are collections in the messaging service, that group events logically. THe clients indicate which message goes to which topic.In order to consume events from a topic an assigned subscription to the desired topic is required. 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The results of this process will become available via the EOSC Exchange Monitoring WebUI (https://argo.eosc-portal.eu). In order to start monitoring an onboarded service, several requirements should be met. In addition to the basic information provided during the onboarding process, the service provider needs to provide some extra information needed by the ARGO monitoring service, described in the section below.","s":"Introduction","u":"/argo-monitoring/docs/guides/case1","h":"#introduction","p":9},{"i":13,"t":"In order to start monitoring a service, a customer should follow the steps described below.","s":"Solution","u":"/argo-monitoring/docs/guides/case1","h":"#solution","p":9},{"i":15,"t":"Before the service can be monitored, it should be onboarded into the EOSC Portal. The procedure for service on-boarding is described in detail in the EOSC portal onboarding process wiki page.","s":"Step 1 Onboard the service","u":"/argo-monitoring/docs/guides/case1","h":"#step-1-onboard-the-service","p":9},{"i":17,"t":"When the service has been successfully onboarded, the ARGO monitoring service requires some additional information. First and foremost, the monitoring service requires the probes and metrics to be associated with the service. Once the service provider decides on the probes/metrics they wish to use, the metrics should be mapped to the service they wish to monitor in EOSC-Exchange Metric Profile. After the metric profile, aggregation and thresholds profiles should also be updated.","s":"Step 2 Provide additional info for monitoring","u":"/argo-monitoring/docs/guides/case1","h":"#step-2-provide-additional-info-for-monitoring","p":9},{"i":19,"t":"Once all the information has been provided, the monitoring of the service starts and the ARGO monitoring Computation and Analytics component calculates availability and reliability of the service, and creates a report. The Service Provider can have a look at the A/R and status results from the EOSC-Exchange Monitoring UI.","s":"Step 3 Start monitoring","u":"/argo-monitoring/docs/guides/case1","h":"#step-3-start-monitoring","p":9},{"i":22,"t":"Use case 2 covers the scenario when infrastructure monitoring requirements cannot be met by EOSC-Exchange Monitoring. For example, one the following are required: defining custom topology and aggregation of monitored endpoints selecting from existing range of probes and adding custom ones managing profiles and metrics for different services","s":"Introduction","u":"/argo-monitoring/docs/guides/case2","h":"#introduction","p":20},{"i":24,"t":"In order to start monitoring an infrastructure, an Infrastructure Manager should follow the steps described below.","s":"Solution","u":"/argo-monitoring/docs/guides/case2","h":"#solution","p":20},{"i":26,"t":"The Infrastructure Manager opens a ticket on EOSC Helpdesk requesting creation of an ARGO Monitoring instance for monitoring new infrastructure. Minimum information that should be provided in ticket: Infrastructure topology Personnel responsible for managing profiles URLs for POEM and UI components","s":"Step 1 EOSC helpdesk request","u":"/argo-monitoring/docs/guides/case2","h":"#step-1-eosc-helpdesk-request","p":20},{"i":28,"t":"ARGO team will create a new tenant based on provided information and reply to the initial request that all instances are ready for use.","s":"Step 2 ARGO team initial actions","u":"/argo-monitoring/docs/guides/case2","h":"#step-2-argo-team-initial-actions","p":20},{"i":30,"t":"Minimum set of profiles that must be defined before monitoring can start: List of metrics must be selected from the metric repository Metric Profile Aggregation Profile","s":"Step 3 Define initial monitoring profiles","u":"/argo-monitoring/docs/guides/case2","h":"#step-3-define-initial-monitoring-profiles","p":20},{"i":32,"t":"Once all the information has been provided, the monitoring of the service starts and the ARGO monitoring Computation and Analytics component calculates availability and reliability of the service, and creates a report. The Infrastructure Manager can have a look at the A/R and status results from the dedicated UI. Monitoring new services is described in Use Case 1.","s":"Step 4 Start monitoring","u":"/argo-monitoring/docs/guides/case2","h":"#step-4-start-monitoring","p":20},{"i":35,"t":"In order to be able to scale-out and take advantage of existing Monitoring systems, the EOSC Monitoring service is capable of accepting data from external sources. When referring to external sources we mean other monitoring engines that want to connect with the EOSC Monitoring Service. This use case is split in two different sections as follows: Case 3.1: Supported Monitoring Engine and Operating System (Nagios on Centos 7 or Debian 8). Case 3.2 Other Monitoring Engine and Operating System","s":"Introduction","u":"/argo-monitoring/docs/guides/case3","h":"#introduction","p":33},{"i":37,"t":"The connection of a monitoring system with EOSC is based mainly on the data that have the necessary information to create the final report. In this use case an external monitoring system replaces the internal monitoring engine and is thus reliable for the validity of the monitoring data that is published.","s":"Solution","u":"/argo-monitoring/docs/guides/case3","h":"#solution","p":33},{"i":39,"t":"The interested party opens a ticket on EOSC Helpdesk requesting to start the process to connect to the EOSC Monitoring Service. During the preparation of its request they need to prepare their systems to be able to provide the following information: The type of system used Infrastructure topology Personnel responsible for managing the necessary profiles URLs for POEM and UI components.","s":"Step 1: EOSC helpdesk","u":"/argo-monitoring/docs/guides/case3","h":"#step-1-eosc-helpdesk","p":33},{"i":41,"t":"The monitoring team creates a new tenant on the monitoring service and at the same time requests from the messaging team to create the necessary configuration on the EOSC Messaging service. As a result the team will then send to the customer the necessary instructions and access tokens to connect to the Monitoring Service.","s":"Step 2: The Monitoring team creates a new Tenant.","u":"/argo-monitoring/docs/guides/case3","h":"#step-2-the-monitoring-team-creates-a-new-tenant","p":33},{"i":43,"t":"The profiles that need to be defined Metric Profile Aggregation Profile.","s":"Step 3: The monitoring team assists the interested party to create the necessary profiles.","u":"/argo-monitoring/docs/guides/case3","h":"#step-3-the-monitoring-team-assists-the-interested-party-to-create-the-necessary-profiles","p":33},{"i":45,"t":"The customer will need to make the necessary configuration on their monitoring engine in order to start publishing metric data via the EOSC messaging service. The EOSC Monitoring Service supports two options Case 3.1: Supported monitoring Engine and Operating System (Nagios on Centos 7 or Debian 8).​ If the customers uses Nagios as its monitoring tool, EOSC Monitoring offers the argo-nagios-ams-publisher tool that is currently supported on Centos-7 and Debian-8. argo-nagios-ams-publisher is a component acting as a bridge from Nagios to ARGO Messaging system and finally to the ARGO Monitoring Engine. It is responsible for forming and dispatching messages that wrap up results from the monitoring engine. In order to use the this solution the customer will need to : a) Install argo-nagios-ams-publisher and ams-library b) Configure argo-nagios-ams-publisher c) Enable OCSP in Nagios: In /etc/nagios/nagios.cfg add this configuration obsess_over_services=1 ocsp_command=argo_service_check ocsp_timeout=15 d) Add OCSP command: should add an OCSP command in /etc/nagios/objects/commands.cfg define command { command_name argo_service_check command_line /usr/bin/ams-metric-to-queue --queue /var/spool/argo-nagios-ams-publisher/metrics/ --hostname \"$HOSTNAME$\" --status \"$SERVICESTATE$\" --summary \"$SERVICEOUTPUT$\" --message \"$LONGSERVICEOUTPUT$\" --servicestatetype \"$SERVICESTATETYPE$\" --actual_data \"$SERVICEPERFDATA$\" --service \"$_SERVICESERVICE_FLAVOUR$\" --metric \"$_SERVICEMETRIC_NAME$\" } e) All the Services to be published must have following attributes set: define service { use generic-service; Name of service template to use host_name grnet.gr service_description HTTP check_command check_http check_interval 5 _service_flavour WebPortal //the service _metric_name org.nagios.WebCheck } f) Start argo-nagios-ams-publisher by executing: service ams-publisherd start Case 3.2 Other monitoring systems​ In this solution - use case the client cannot or doesn't want to use the solution described in the case 3.1 . Then the external monitoring system should find a way to send the monitoring data (metric data) to the EOSC Monitoring . These data should follow a predefined format. The data should be stamped with their source and timestamp. Every metric should be prefixed with [source_type], following the metric naming best practises. Every metric is also labelled with the hostname and service description. These predefined messages should be sent to the EOSC Messaging service which is the service responsible to pass them to the computations engine which performs the necessary calculations to produce the reports. { \"hostname\": \"host101.example.com\", \"service\": \"eu.eosc.portal.services.url\", \"metric\": \"org.nagios.WebCheck\", \"timestamp\": \"2022-01-02T00:24:38Z\", \"status\": \"OK\", \"tags\": { \"endpoint_group\": \"GroupA\" }, \"summary\": \"200 OK\", \"actual_data\": \"time=0.085796s;;;0.000000 size=1126B;;;0\", \"monitoring_host\": \"monbox.example.com\",//name of the external monitoring box \"message\": \"a more detailed message about the monitoring result\" } Metric data comes in the form of avro files, (json files support currently in development ) and contains timestamped status information about the hostname, service and specific checks (metrics) that are being monitored. A typical item of information in the metric data contains the field listed in the snippet below. {\"namespace\": \"argo.avro\", \"type\": \"record\", \"name\": \"metric_data\", \"fields\": [ {\"name\": \"timestamp\", \"type\": \"string\"}, {\"name\": \"service\", \"type\": \"string\"}, {\"name\": \"hostname\", \"type\": \"string\"}, {\"name\": \"metric\", \"type\": \"string\"}, {\"name\": \"status\", \"type\": \"string\"}, {\"name\": \"monitoring_host\", \"type\": [\"null\", \"string\"]}, {\"name\": \"summary\", \"type\": [\"null\", \"string\"]}, {\"name\": \"message\", \"type\": [\"null\", \"string\"]}, {\"name\": \"tags\", \"type\" : [\"null\", {\"name\" : \"Tags\", \"type\" : \"map\", \"values\" : [\"null\", \"string\"] }] }] } Snippet: Accepted Avro schema The monitoring team will validate the published metric data against the supplied topology and perform a number of dry runs to ensure that there is no issue with the supplied data. As soon as the metric data is validated by the Monitoring Team these will be the main data to compute A/R and status results.","s":"Step 4: Publish Metric Data","u":"/argo-monitoring/docs/guides/case3","h":"#step-4--publish-metric-data","p":33},{"i":47,"t":"Once information has been provided, the monitoring of the service starts and the ARGO monitoring Computation and Analytics component calculates availability and reliability of the service, and creates a report. The Infrastructure Manager can have a look at the A/R and status results from the dedicated UI. Monitoring new services is described in Use Case 1.","s":"Step 5: Start Monitoring","u":"/argo-monitoring/docs/guides/case3","h":"#step-5-start-monitoring","p":33},{"i":50,"t":"This use case covers the scenarios where the topology and the results of multiple tenants need to be combined in a number of reports.","s":"Introduction","u":"/argo-monitoring/docs/guides/case4","h":"#introduction","p":48},{"i":52,"t":"In order to combine results from tenants A, B (example names), those tenants should be already monitored by ARGO Monitoring service complete with the following definitions for each tenant: Latest Data available: Each tenant should be checked that has an active stream of incoming monitoring data. Topology: Each tenant should already have a well defined source of topology that includes lists of groups, endpoints and services. Metric Profile: In simple terms, a list of all services to be checked along with all relevant metrics per service","s":"Prerequisites","u":"/argo-monitoring/docs/guides/case4","h":"#prerequisites","p":48},{"i":54,"t":"Step 1: Open a ticket to helpdesk​ In order to have results, the customer should create a ticket on the helpdesk describing: Tenants to be used in the combined report Services and metrics Aggregation profile. For each tenant that is going to take part in producing the combined results check that all of the prerequisites (mentioned in the previous section) do apply. Step 2: Creation of the Combined Tenant.​ Create a new tenant that will host the combined report. This tenant will act as a host tenant for the combined results and will rely on the data of the other tenants as input for the computations of the availability, reliability and status results. Step 3 Start monitoring​ Once all the information has been provided, the monitoring of the service starts and the ARGO monitoring Computation and Analytics component calculates availability and reliability of the services, and creates a report. The User can have a look at the A/R and status results from the combined reports from the UI.","s":"Solution","u":"/argo-monitoring/docs/guides/case4","h":"#solution","p":48},{"i":57,"t":"This use case covers the scenario of getting (A/R) Availability and Reliability data from the EOSC-Monitoring Service based on the resource-id. One scenario is to get the A/R data of a service Onboarded to EOSC via the Providers Portal. Based on the Service-ID of the service from the Providers Portal you can get the A/R from the monitoring service. Before we start Availability: Service Availability is the fraction of time a service was in the UP Period during the known interval in a given period. Availability rate is useful to know, as it provides information of the time the monitored item is available for use. Reliability: Service Reliability is the ratio of the time interval a service was UP over the time interval it was supposed (scheduled) to be UP in the given period. Reliability rate is also useful to know, as it provides information about the quality of monitored item during the monitoring time, whereas it is reliable of usage or not. More information about Availability/Reliability can be found from here","s":"Introduction","u":"/argo-monitoring/docs/guides/EOSC-getARData","h":"#introduction","p":55},{"i":59,"t":"When a resource is on-boarded in the Providers Portal is automatically gets a resource-id. By the time it is on-boarded, it is also integrated with EOSC-Core services like Monitoring. The Monitoring Service based on the data defined in the Providers Portal, starts monitoring the resource and creates near real time status reports, and availability and reliability reports. This is the information a customer can get for a resource. In this guide we describe how the customer can get the A/R data for a specific resource-id. In order to start getting A/R monitoring data for a service or a list of services, a customer should follow the steps described below.","s":"Solution","u":"/argo-monitoring/docs/guides/EOSC-getARData","h":"#solution","p":55},{"i":61,"t":"The first step to start using/testing the service is to request an account via the EOSC helpdesk and from the unit monitoring service. Just create a ticket with the title Account request to fetch the status of the services. In the description of the ticket please describe the use case and the service that needs this type of monitoring data. Example Title: Account request to fetch monitoring data of a service Description: I am the service owner of EOSC Marketplace and i would like to display the monitoring data. I would like to request an account to get access to the onboarded resources. If you already have an account and you are fetching the status data you can just ask access for the A/R monitoring data.","s":"Step 1: Request an account","u":"/argo-monitoring/docs/guides/EOSC-getARData","h":"#step-1-request-an-account","p":55},{"i":63,"t":"In the response you will get the following information Name Description report_name The Name of the report that contains information about the status of the resource id. URL The URL where you may find the api account details Your account details. We usually send them via another service (dnote) for security reasons","s":"Step 2 The response","u":"/argo-monitoring/docs/guides/EOSC-getARData","h":"#step-2-the-response","p":55},{"i":65,"t":"By the time you have the data described in the previous step, you can start using the API. The API method supports the following parameters ?granularity=monthly|daily: to view monthly of daily A/R results for the requested resource-id. (start and end_time are required) start_time: a parameter to view the A/R results for this specific resource-id under a certain period of time end_time: the end_time of the period requested You may test the API call in the following links. Details of the API Call Test it online: AR Results (v3): GET /v3/results/{report_name}/id/{resource_id} Example Request 1: default daily granularity with specific resource-id​ Request​ Method​ HTTP GET Path​ /api/v3/results/Report_A/id/simple-queue?start_time=2015-06-20T12:00:00Z&end_time=2015-06-26T23:00:00Z Headers​ x-api-key: \"tenant_key_value\" Accept: \"application/json\" Response​ Code​ Status: 200 OK Body​ { \"id\": \"simple-queue\", \"endpoints\": [ { \"name\": \"host01.example\", \"service\": \"service.queue\", \"group\": \"Infra-01\", \"info\": { \"URL\": \"http://submit.queue01.example.com\" }, \"results\": [ { \"date\": \"2015-06-22\", \"availability\": \"99.99999900000002\", \"reliability\": \"99.99999900000002\", \"unknown\": \"0\", \"uptime\": \"1\", \"downtime\": \"0\" }, { \"date\": \"2015-06-23\", \"availability\": \"99.99999900000002\", \"reliability\": \"99.99999900000002\", \"unknown\": \"0\", \"uptime\": \"1\", \"downtime\": \"0\" } ] ] }","s":"Step 3 Start using the api","u":"/argo-monitoring/docs/guides/EOSC-getARData","h":"#step-3-start-using-the-api","p":55},{"i":68,"t":"This use case covers the scenario according to which the customer needs to use the results of the EOSC Monitoring Service in an external service/dashboard. The customer can access the following information via an API: A/R information about the service and its service components Status information about the service and its service components The topology and grouping of the service","s":"Introduction","u":"/argo-monitoring/docs/guides/case5","h":"#introduction","p":66},{"i":71,"t":"Τhe user that wants to gain access to this type of monitoring information will get a token with read-only access to the A/R and status results. The user via the EOSC helpdesk may send his request to the monitoring team by sending: The name of the service that wants the information An email to create the user The type of information (A/R results, status results, both)","s":"Step 1: EOSC helpdesk","u":"/argo-monitoring/docs/guides/case5","h":"#step-1-eosc-helpdesk","p":66},{"i":73,"t":"The monitoring team will provide the required token and information, guidance on how to retrieve the information.","s":"Step 2: Start Ingesting the data.","u":"/argo-monitoring/docs/guides/case5","h":"#step-2-start-ingesting-the-data","p":66},{"i":75,"t":"Retrieve availability, reliability and status results of a service​ In this example we are going to present how the user can get the availability, the reliability values and the status of the AMS (Messaging Service) (endpoint: https://msg.argo.grnet.gr) of the Organisation GRNET. The Monitoring Service Monitoring Service is checking the services at regular intervals. It actually runs explicit tests (checks) in order to assess the status of the service. The result of the checks decides on the status of the service. In order to display status information it uses reports where it keeps all the necessary information. At the same time it produces useful conclusions about the monitoring item via the monitoring analytics engine. One very useful conclusion is to decide if the item is available for usage and if it is considered as reliable. To succeed this, availability/reliability values (hourly, daily, monthly) are calculated. These different types of information are also encapsulated in a report. The EOSC monitoring service monitors the Messaging Service and it performs the following checks cert_validity_check : a metric that checks the validity of the certificate used by the service ams_check: a metric that checks a list of functionalities provided by the messaging service. Based on the explanation provided above, the information about the service follows: Definition Value Description GROUP GRNET A collection of services SERVICE AMS The type of one of the services of the collection SERVICE endpoint msg.argo.grnet.gr(AMS) is defined as the combination of a hostname and Service Type. (a Service Type of AMS listening on port/s on the host msg.argo.grnet.gr is a service endpoint) Grouping used in the report SERVICEGROUPS the way the services are organized (e.g. in groups of sites, in groups of services) in the monitoring engine A/R report Default The place where the A/R results are provided. Status report Default The place where status results are provided. This is the configuration that the user will have to use to use the api calls. API call examples for A/R reports​ The api authenticates the user using the api-key within the x-api-key header. Users can specify time granularity (monthly or daily) for retrieved results and also format using the Accept header. Depending on the form of the request the user can request a group, service or service endpoint. Detailed documentation: ARGO web api v3 a/r results Example: For the AMS the corresponding api call to get the A/R of the service group GRNET is: Request for A/R results for service group GRNET: $ curl -X GET -H \"Accept: application/json\" -H \"Content-Type: application/json\" -H \"x-api-key: secret-token\" https://api.argo.grnet.gr/api/v3/results/Default/SERVICEGROUPS/GRNET?start_time=2021-08-05T00:00:00Z&end_time=2021-08-05T23:59:59Z API call examples for status reports​ The api authenticates the user using the api-key within the x-api-key header. Users can specify time granularity (monthly or daily) for retrieved results and also format using the Accept header. Depending on the form of the request the user can request a group, service or service endpoint. Detailed documentation: ARGO web api docsARGO web api v3 status results Example: For the AMS the corresponding api call to get the status of the service group GRNET is: Request for status results for service group GRNET: $ curl -X GET -H \"Accept: application/json\" -H \"Content-Type: application/json\" -H \"x-api-key: secret-token\" https://api.argo.grnet.gr/api/v3/status/Default/SERVICEGROUPS/GRNET?start_time=2021-08-05T00:00:00Z&end_time=2021-08-05T23:59:59Z","s":"Examples","u":"/argo-monitoring/docs/guides/case5","h":"#examples","p":66},{"i":78,"t":"This use case covers the scenario of getting status data from the EOSC-Monitoring Service based on the resource-id. One scenario is to get the status data of a service Onboarded to EOSC via the Providers Portal. Based on the Service-ID of the service from the Providers Portal you can get the status from the monitoring service.","s":"Introduction","u":"/argo-monitoring/docs/guides/EOSC-getStatusData","h":"#introduction","p":76},{"i":80,"t":"When a resource is on-boarded in the Providers Portal is automatically gets a resource-id. By the time it is on-boarded, it is also integrated with EOSC-Core services like Monitoring. The Monitoring Service based on the data defined in the Providers Portal, starts monitoring the resource and creates near real time status reports, and availability and reliability reports. This is the information a customer can get for a resource. In this guide we describe how the customer can get the Status data for a specific resource-id. In order to start getting status monitoring data for a service or a list of services, a customer should follow the steps described below.","s":"Solution","u":"/argo-monitoring/docs/guides/EOSC-getStatusData","h":"#solution","p":76},{"i":82,"t":"The first step to start using/testing the service is to request an account via the EOSC helpdesk and from the unit monitoring service. Just create a ticket with the title Account request to fetch the status of the services. In the description of the ticket please describe the use case and the service that needs this type of monitoring data. Example Title: Account request to fetch the status of the services Description: I am the service owner of EOSC Marketplace and i would like to display the status monitoring data. I would like to request an account to get access to the onboarded resources.","s":"Step 1: Request an account","u":"/argo-monitoring/docs/guides/EOSC-getStatusData","h":"#step-1-request-an-account","p":76},{"i":84,"t":"In the response you will get the following information Name Description report_name The Name of the report that contains information about the status of the resource id. URL The URL where you may find the api account details Your account details. We usually send them via another service (dnote) for security reasons","s":"Step 2 The response","u":"/argo-monitoring/docs/guides/EOSC-getStatusData","h":"#step-2-the-response","p":76},{"i":86,"t":"By the time you have the data described in the previous step, you can start using the API. The API method supports 2 different methods a simple form: It will return the latest status result for the requested resource-id. With view=details the user can examine a detailed timeline for the current day, or specify a different period of time (using start_time and end_time) an advanced form: This form supports a number of filters which help the customer get more information about the requested resource-id. ?view=details: to view the most recent timeline of results for the requested resource-id start_time: a parameter to view the detailed timeline of results for this specific resource-id under a certain period of time end_time: the end_time of the period requested You may test the API call or get detailed information about the API method in the following links. Details of the API Call Test it online: Status Results (v3): GET /v3/status/{report_name}/id/{resource_id} Example Request 1: Latest status result for endpoint with id: simple-queue​ Request​ Method​ HTTP GET Path​ /api/v2/status/Report_A/id/simple-queue Headers​ x-api-key: \"tenant_key_value\" Accept: \"application/json\" Response​ Code​ Status: 200 OK Body​ { \"id\": \"simple-queue\", \"endpoints\": [ { \"hostname\": \"queue01.example.com\", \"service\": \"compute.queue\", \"group\": \"Infra-01\", \"info\": { \"URL\": \"http://submit.queue01.example.com\" }, \"statuses\": [ { \"timestamp\": \"2022-10-12T13:25:26Z\", \"value\": \"OK\" } ] } ] }","s":"Step 3 Start using the api","u":"/argo-monitoring/docs/guides/EOSC-getStatusData","h":"#step-3-start-using-the-api","p":76},{"i":88,"t":"In ARGO you may combine top level A/R results (such as results referring to you data center, institution as a whole) into a higher level of abstraction such as organisations, projects, federation. In this level each member contributes to the final A/R score based on its resource capacity. This contribution is expressed as a weighted average, which is obtained by various ways such us by running benchmark on the infrastructure (ex. hep spec 06)","s":"Weights","u":"/argo-monitoring/docs/information_feeds/weights","h":"","p":87},{"i":90,"t":"ARGO Monitoring Service takes into consideration the weights to combine top level A/R results.","s":"How weights are used in the computations","u":"/argo-monitoring/docs/information_feeds/weights","h":"#how-weights-are-used-in-the-computations","p":87},{"i":92,"t":"In ARGO we actually define sets of weights applied to top level items (as we've mentioned, those are groups that represent data centers, institutions etc..). The definition includes: a name the type of top level group items that the weights are applied to the type of weights (related to computational cores, benchmark scores, TFLOPS, storage capacity, etc...) And the list of weighted items (tuples of item names along with the weight assigned to them which is usually a float number) The Json definition of a weight set is described in the example below: { \"name\": \"Example_Weightset\", \"weight_type\": \"HEPSPEC06_score\", \"group_type\": \"DATACENTERS\", \"groups\": [ { \"name\": \"DC_01_AMSTERDAM\", \"value\": 12356.4 }, { \"name\": \"DC_02_LONDON\", \"value\": 16791.5 }, { \"name\": \"DC_03_FRANKFURT\", \"value\": 18791.5 } ] } Monitoring Service has a number of connectors for setting the weights: VAPOR CSV files (predefined format) Json files (predefined format) xml files (predefined format)","s":"How can I define the weights","u":"/argo-monitoring/docs/information_feeds/weights","h":"#how-can-i-define-the-weights","p":87},{"i":94,"t":"The term downtime is used to refer to periods when a service is unavailable. Downtime can be caused by failure in hardware (physical equipment), (logic controlling equipment), interconnecting equipment (such as cables, facilities, routers,...), transmission (wireless, microwave, satellite), and/or capacity (system limits). Apart from a downtime due to an unplanned event there is also downtime as a planned event due to a routing maintenance. Scheduling downtime is an effective way to prevent unnecessary or unwanted notifications from being received during a period of expected service interruption.","s":"Downtimes","u":"/argo-monitoring/docs/information_feeds/downtimes","h":"","p":93},{"i":96,"t":"ARGO Monitoring Service takes into consideration the scheduled downtime to calculate the Reliability of a service or a group of services. It also affects the uptime value. At the same time the Monitoring Service doesn't send unnecessary notifications during periods of expected service interruption.","s":"How Downtimes are used in the computations","u":"/argo-monitoring/docs/information_feeds/downtimes","h":"#how-downtimes-are-used-in-the-computations","p":93},{"i":98,"t":"A scheduled downtime is a combination of the endpoint, the service type and the start and end time of the downtime . \"hostname\": \"www.grnet.gr\", \"service\": \"WEBSITE\", \"start_time\": \"2021-09-04T00:00:00Z\", \"end_time\": \"2021-09-04T23:59:00Z\" Monitoring Service has a number of connectors for well-known configuration databases and sources to get the downtimes like: DPMT (Data Project Management Tool, that also manages topology and resources information) GOCDB (Repository for storing and presenting topology and resources information) CSV files (predefined format) Json files (predefined format) xml files (predefined format)","s":"How can I define a Downtime","u":"/argo-monitoring/docs/information_feeds/downtimes","h":"#how-can-i-define-a-downtime","p":93},{"i":100,"t":"One of the main sources of truth used in the Monitoring Service is the topology. It helps to discover and map relationships between services / resources. Via the topology the owner may have in-depth visibility into the infrastructure, by enabling the Monitoring Service to categorize, classify, and finally monitor the services in it. Topology includes all the necessary information about how an infrastructure is structured and organized. ARGO Monitoring Service via the connectors (components used to connect to well known Configuration Databases (DPMT, GOCDB, csv files, json) retrieves information about the infrastructure, the hierarchy of the services that will be monitored, and the service owners. Topology information includes : the monitored services the way they are organized (ex. in groups of sites, in groups of services, in projects). The Service can model different types of infrastructure architectures the service actors (owners, admins) The ways the services are organized (sites, services, projects) can be part of a bigger structure, that gathers a number of groups. Organisations offer services that can be grouped based on the location (SITES), or based on the project they are used by (PROJECT) . This can be one more level to the topology hierarchy. The topology should also provide information about this bigger group, it's type and the services it contains. The ARGO Monitoring Service allows the users to model their infrastructure by defining multiple level of groups, starting from groups of Service Endpoints and moving to higher level groups of groups. In this way it is easy to model different infrastructure architectures. We have to mention here that the levels of the topology is something that can be updated and depends on the requirements of each infrastructure. But before we start lets explain a few acronyms. Type Description Example Grouping A way to organize and group the services SITE An organization responsible for the service PROJECT When you offer services on behalf of a project SERVICE GROUPS A group of related services SITE GRNET PROJECT MyProject SERVICE GROUP Cluster of databases Service Type Each service type can have a defined sets of metrics, which are explicit tests when we check repository Endpoint the combination of hostname and Service Type, defining where the service runs a repository at www.example-repository.com uses port 4333 Service actors the people responsible for the service operation Administrator : John Smith jsmith [AT] grnet.gr Site Owner: John Doe jDoe [AT] grnet.gr Security: George Papadopoulos jpapad [AT] grnet.gr","s":"Topology","u":"/argo-monitoring/docs/information_feeds/topology","h":"","p":99},{"i":102,"t":"Via a Topology the structure of a Project, an Organization, a SITE, can be monitored. For example:","s":"Examples","u":"/argo-monitoring/docs/information_feeds/topology","h":"#examples","p":99},{"i":104,"t":"When we participate at a Project we offer a number of services. Based on this a project gathers the services to offer to a higher level and creates one more level of hierarchy. Project acts as a group, at the top level of the infrastructure definition. Project |---Service or Group of services |--Service Endpoints As an example, we may say that we have a project (MyProject) which offers an AAI Service and a Document Management Service. The information about the topology includes the group (MyProject), the services (AAI service, Document Management Service) that combine the service endpoints (aai.myproject.org, aai1.myproject.org) and (docu.myproject.org, database.myproject.org) . The following image is trying to represent the hierarchy of the topology. MyProject |---AAI service |---Document Management Service |------aai.myproject.org |------docu.myproject.org |------aai1.myproject.org |------database.myproject.org","s":"Example 1: Monitoring the services of a Project- The topology:","u":"/argo-monitoring/docs/information_feeds/topology","h":"#example-1-monitoring-the-services-of-a-project--the-topology","p":99},{"i":106,"t":"Another way to organise the topology is to add a new layer of group which is the Organisations. An Organisation usually has a number of Sites where it hosts the services used by the users. In the following example the hierarchy of this type of topology is represented. ORGANINATION |----SITE |---Service or Group of services |------Service Endpoints As an example, we may say that we have an organization, such as GRNET, which has a number of Sites like HEBLAB,IASA,EKT. Each Site gathers a number of services like SRM and WEBDAV. These services combine a number of like service-endpoints grid02.physics.uoi.gr, se01.marie.hellasgrid.gr, se01.athena.hellasgrid.gr. The following image is trying to represent the hierarchy of the topology. GRNET |---- HEBLAB |-- SRM |-- grid02.physics.uoi.gr |---- IASA |-- WEBDAV |-- se01.marie.hellasgrid. |---- EKT |-- SRM |-- se01.athena.hellasgrid.gr A visual representation of the above topology example can be represented from the image below: Monitoring Service has a number of connectors for well-known configuration databases and sources like: DPMT (Data Project Management Tool, that also manages topology and resources information) GOCDB (Repository for storing and presenting topology and resources information) CSV files (predefined format) Json files (predefined format) An example of the Json file is as follows: [ { \"Service Description (Alphanumeric and basic punctuation)\": \"My service\", \"URL\": \"https://example.com\", \"SITENAME-SERVICEGROUP\": \"MY_SITE\", \"Service Unique ID\": \"1234\", \"COUNTRY_NAME\": \"Greece\", \"notification flag?\": \"Yes\", \"CONTACT_EMAIL\": \"address@example.com\", \"Status \": \"Development\", \"SERVICE_TYPE\": \"my.service.type\" } … ] xml files (predefined format)","s":"Example 2: Monitoring the services of 1 or more Organisations - The topology:","u":"/argo-monitoring/docs/information_feeds/topology","h":"#example-2-monitoring-the-services-of-1-or-more-organisations---the-topology","p":99},{"i":108,"t":"Monitoring is the key service needed to gain insights into an infrastructure. It needs to be continuous and on-demand to quickly detect, correlate, and analyse data for a fast reaction to anomalous behaviour. The challenge of this type of monitoring is how to quickly identify and correlate problems before they affect end-users and ultimately the productivity of the organisation. Management teams can monitor the availability and reliability of the services from a high level view down to individual system metrics and monitor the conformance of multiple SLAs. The key functional requirements are: Monitoring of services Reporting availability and reliability, Visualisation of the services status, Provide dashboard interfaces, Sending real-time alerts. The dashboard design should enable easy access and visualisation of data for end-users. APIs should also be supported so as to allow third parties to gather monitoring data from the system through them. The key requirements of a monitoring system are: Support for multiple entry points (different types of systems can work together) Interoperable High availability of the different components of the system Loosely coupled: support API's in the full stack so that components are independent in their development cycles Support for Multiple Tenants, Configurations, Metrics and profiles to add flexibility and ease of customisation. For EOSC there are two monitoring services already in place: EOSC CORE and the EOSC Exchange Monitoring Service. These two services are responsible to monitor the Core services (EOSC Core Monitoring) and the services onboarded to the Marketplace (EOSC-Exchange Monitoring).","s":"Introduction","u":"/argo-monitoring/docs/guides/intro","h":"","p":107},{"i":110,"t":"The service collects status (metrics) results from one or more monitoring engine(es) and delivers daily and/or monthly availability (A) and reliability (R) results of distributed services. Both status results and A/R metrics are presented through a Web UI, with the ability for a user to drill-down from the availability of a site to individual test results that contributed to the computed figure. Figure 1. High level architecture of a Monitoring service The main components of a monitoring service are depicted in the high-level architecture diagram and described below. Monitoring Engine(s): This service component executes the service checks against the infrastructure and delivers the metric data (probe check results) to the Messaging Service. Sources of Truth: The Monitoring system should support a number of connector plugins that are able to fetch topology, Metrics and Factors from various sources such as the CMDB and the Providers Portal. It also offers a Metric and Profile Management Component which is used in order to define checks (probes) and associate them to service types. Each grouping of checks and service types forms a profile. Messaging: The monitoring system depends on a Pub/Sub Messaging Service to be in place, in order to facilitate the communication between its components. Computations & Analytics: This component of the system should include computational job definitions for ingesting data, calculating status and availability/reliability and a management service to automatically configure, deploy and execute those jobs on a distributed processing engine for stateful computations. At the same time this component analyzes the monitoring results and sends notifications based on a set of rules, to inform the users (operators, NGIs) about the status of their services. WEB API: Rest-like HTTP API service that provides access to status and availability/reliability results. It supports token based authentication and authorization with established roles. Results are provided in JSON Format. WEB UI: The Web UI is the component used to store, consolidate and \"feed\" data into the web application. The global information from the primary and heterogeneous data sources is retrieved by means of the different plugins. The collected information is structured and organized within configuration files in the service and, finally, made available to the web application without the need for any further computations. This modular architecture is conceived in order to make it easy to add new data sources and to use cached information if a primary source is unavailable. The resulting data is exposed through a RESTful web service interface.","s":"High-level Service Reference Architecture","u":"/argo-monitoring/docs/guides/intro","h":"#high-level-service-reference-architecture","p":107},{"i":112,"t":"In this section we explain the basic concepts of EOSC Monitoring. A Tenant is an isolated instance of the ARGO Monitor service that relies on common components and provides the user with its own environment. ARGO provides default UI and POEM URLs in following form: UI: https://.ui.argo.grnet.gr POEM: https://.ui.argo.grnet.gr In case custom ones are to be used, the customer is responsible for providing valid certificates and DNS aliases. ARGO Monitoring service requires following topology information in order to monitor services: the services and service endpoints they are running, the way they are organised (e.g. groups of sites, groups of services), the service actors (owners, admins, contact points). Topology can be further extended with attributes needed for individual probes (e.g. service port or URL, path to be used in case of storage services, e.g.). Supported topology sources are: EOSC Resource Registry (Providers Portal): Need to be extended to hold the following information for Monitoring. Service unique Id the service endpoints, the way they are organised (service, service components), the service actors (owners, admins, contact points). EGI Configuration Database (GOCDB) EUDAT DPMT JSON feed in the predefined format. A Metric is a chunk of code that checks specific functionality of a given service. For example a metric such as Portal-WebCheck runs on a site and checks if the HTTP connection responds correctly or not. A Probe is a piece of code that implements single or multiple tests. The probe must comply with the guidelines for monitoring probes. ARGO provides a registry of probes and metrics. New probes and metrics can be added to the registry with the support of the ARGO monitoring team. A Metric Profile is used to associate a Service with the corresponding metrics. An Aggregation Profile defines how to aggregate service statuses into higher hierarchical grouping (i.e. a service_group) status results. They are actually used to define logical rules on how to aggregate individual service status computations into groups. The results of the metrics are computed, into EOSC Monitoring Service calculations, in order to conclude into the operational state of the service, during a specific period. In order to conclude about the operational state of the service, all or part of the metrics that check the service's functionality should be taken into account. In Metrics Profiles are included, for each service, these metrics whose results are considered to the computations of the service's state. For example, a service WebSite runs on host1.example.com. The WebSite service should operate properly, be accessible and some actions should be available such as downloading or uploading material (documents, images etc). Three metrics can apply on the service to check it's functionalities: Portal-WebCheck is a metric to check if the http responds http.download is a metric to check if download functionality operates well http.upload is a metric to check if upload functionality operates well The service is assumed to operate properly if it is accessible and can support downloading material. Uploading material does not affect the state of the service (whether it is working properly or not). So in the Metrics Profile, the metrics Portal-WebCheck and http.download will be defined in order to be taken into account for concluding the status of the service. Adopted Standards REST (https://www.ics.uci.edu/~fielding/pubs/) SAML2 (https://wiki.oasis-open.org/security/FrontPage) X509 (https://www.rfc-editor.org/info/rfc5280) Apache Avro (http://avro.apache.org/) Adopted Protocols HTTPS (https://tools.ietf.org/html/rfc2818) Nagios Plugin API (https://nagios-plugins.org/doc/guidelines.html) ARGO API over REST API (http://argoeu.github.io/guides/api/)","s":"Definitions","u":"/argo-monitoring/docs/guides/intro","h":"#definitions","p":107},{"i":116,"t":"The electronic infrastructure availability / reliability monitoring service is designed for Service Level Monitoring, for medium and large infrastructures. It monitors the status, availability and reliability of services provided by electronic infrastructures with moderate to high complexity. It supports flexible development models and modular design, allowing easy communication with external systems (such as CMDBs, Service Catalogs, etc.). The service allows the creation of multiple reports using profiles (profiles are different ways and filters of organizing and displaying the services and their service components), which are defined by the client (e.g. for managing SLAs, operations, etc.). When calculating reports (using big data management technologies) the service takes into account a number of external factors, such as specific service parameters, scheduled or unscheduled downtime, etc.","s":"Measuring and Monitoring the Availability and Reliability of Electronic Infrastructures","u":"/argo-monitoring/docs/intro","h":"#measuring-and-monitoring-the-availability-and-reliability-of-electronic-infrastructures","p":113},{"i":118,"t":"There are several things to consider when monitoring a Service. The more complex a system gets, the harder it gets to monitor. The ARGO Monitoring follows a plan for solving these kinds of challenges and provides an easy path to gain powerful insights. The ARGO Monitoring service starts monitoring the service by checking its liveness /health of the service. The main focus though is to check the availability and reliability of the services as well as groups of services by simulating the actions that the respective user would do interacting with it. For instance, in the case of a file transfer server (FTP), the service tries to transfer, save and delete a file in the server. These tests are performed at regular random intervals (e.g. every hour or 15 minutes) and their results are recorded to be included in the measuring of the availability and reliability of the service. The service supports different profiles for creating the topology and grouping of services and the algorithm for calculating the availability and reliability of services. The calculations are done in big data management and processing infrastructures (use of apache flink platform) which provide results both in real time and their correction at regular intervals. The service publishes the results of its calculations in real time, thus allowing the creation of a control panel of the status of the services (through a special interface that has been created) and provides the possibility of timely notification (alerts via email as well as SMS and slack messages) of administrators in case to detect an error. Argo monitoring provides a modern and comprehensive web-ui in which users can easily view details and results (status results and a/r scores) on items monitored. Users can navigate through the different layers of topology (groups, services, endpoints) and with various levels of granularity (monthly, daily, etc…)","s":"How it works","u":"/argo-monitoring/docs/intro","h":"#how-it-works","p":113},{"i":121,"t":"This document describes the policy to develop, package and integrate new probes into the ARGO Monitoring Engine.","s":"Overview","u":"/argo-monitoring/docs/monitoring/guidelines","h":"#overview","p":119},{"i":123,"t":"Before starting with development, check if probe already exists on Nagios Exchange. Please refer to the official Nagios documentation for probe development guidelines: Nagios Development Guidelines, Nagios Plugin API. Probes can be developed in any of these languages: Python, Perl - in case of Perl use of module Nagios::Plugin is highly recommended, C/C++, shell scripting (Bash, Bourne). ARGO Monitoring engine currently supports RHEL 7 and derivatives, so probes should use language versions and libraries provided for these distributions. List of existing probes can be found in POEM. Some other conditions: Each probe must provide the following arguments: -h help (--help) -t timeout (--timeout) -H hostname (--hostname) The following arguments can also be used if applicable: -p port (--port) -u url (--url) -v verbose (--verbose) -w warning threshold (--warning) -c critical threshold (--critical) -u username (--username) -p password (--password) Maximum output size for test/plugin output is 16KB. Above that limit the output will be truncated.","s":"Development","u":"/argo-monitoring/docs/monitoring/guidelines","h":"#development","p":119},{"i":125,"t":"Actual data is additional information about service behaviour that can be used in combination with threshold mechanisms to generate new metrics. Probes can report actual data by following the Nagios guidelines for performance data. Some other conditions: This is the expected format of actual data: 'label'=value[UOM];[warn];[crit];[min];[max]","s":"Actual Data","u":"/argo-monitoring/docs/monitoring/guidelines","h":"#actual-data","p":119},{"i":127,"t":"Probes must be provided in the form of RPM packages, where a single package may contain multiple probes. Please refer to the official EPEL documentation for packaging: EPEL Guidelines And Policies. Some considerations about naming: Package should ensure a unique namespace by using tenant, project (e.g. egi, eudat, argo) or product team (e.g. cream, htcondor) name. Package name should use \"argo-probe--\" form where is the name of the service probes are testing (e.g. argo-probe-grnet-agora). For more generic probes (not project specific) name \"argo-probe-\" is also acceptable (e.g. argo-probe-webdav). Some considerations about structure: Probes should be stored in directory: /usr/libexec/argo/probes/ (For more generic probes (not project specific) directory used by EPEL nagios probes (/usr/lib64/nagios/plugins/) is also acceptable.) If probes create temporary files, package should create directory: /var/spool/argo/probes// with ownership nagios:nagios and permissions 750. If probes package contains configuration files, they should be stored in directory: /etc/argo/probes//. Some considerations about dependencies management: Each probe is responsible for handling its dependencies. The environment needed to execute each probe must be defined by the probe.","s":"Packaging","u":"/argo-monitoring/docs/monitoring/guidelines","h":"#packaging","p":119},{"i":129,"t":"Each develops and tests its own probes in their development environments. Pre-requirements for the integration and testing of probes are: Each publishes probe(s) on an accessible: Git repository with a valid RPM spec file; Yum repository with RPM packages. Each probe provides an accessible web page with the relevant documentation. Integration of new probes starts with adding above information into POEM.","s":"Integration, Testing and Deployment","u":"/argo-monitoring/docs/monitoring/guidelines","h":"#integration-testing-and-deployment","p":119},{"i":131,"t":"Testing consists of the following steps: If the probe is provided in Git repository ARGO will clone it and attempt to build the package. ARGO will deploy the RPM package, test and validate the new probe.","s":"Testing","u":"/argo-monitoring/docs/monitoring/guidelines","h":"#testing","p":119},{"i":133,"t":"Deployment consists of the following steps: ARGO in cooperation with the Service owner defines metric templates performed by the new probe in POEM. ARGO in cooperation with the Service owner adds mappings between service flavours and metrics in POEM. ARGO in cooperation with the Service owner follows project’s procedures for deployment to production.","s":"Deployment","u":"/argo-monitoring/docs/monitoring/guidelines","h":"#deployment","p":119},{"i":136,"t":"The ARGO Monitoring service provides a flexible and scalable framework for monitoring status, availability and reliability of a wide range of services provided by infrastructures with medium to high complexity. ARGO generates reports using customer defined profiles (e.g. for SLA management, operations, etc.). During the report generation, ARGO takes into account custom factors such as the importance of a specific service endpoint and scheduled or unscheduled downtimes.","s":"Overview","u":"/argo-monitoring/docs/monitoring/SP_guide","h":"#overview","p":134},{"i":138,"t":"Topology database is actually a central registry for e-Infrastructure topology.","s":"Topology","u":"/argo-monitoring/docs/monitoring/SP_guide","h":"#topology","p":134},{"i":140,"t":"Monitoring service relies on topology database to provide the following information: the monitored service(s), the service types they are running (e.g. wiki), the service endpoints of the service (e.g. endpoint), the way they are organized (e.g. in groups of sites, in groups of services), the service actors (owners, admins, contact points).","s":"Topology information","u":"/argo-monitoring/docs/monitoring/SP_guide","h":"#topology-information","p":134},{"i":142,"t":"A metric is a procedure that checks specific functionality of a given service, i.e. a single measurement. For example: generic.http.connect: checks the http if it responds; generic.certificate.validity: checks the validity of a certificate.","s":"Metrics & probes","u":"/argo-monitoring/docs/monitoring/SP_guide","h":"#metrics--probes","p":134},{"i":144,"t":"Probe is piece of code which implements single or multiple tests. All the probes intended to be used for monitoring must comply with the guidelines for monitoring probes. The owners of the service are the ones that know exactly how the service is working. The service development team with the support of the monitoring team is responsible to implement the probe that checks and at the same time mimics the actual end user behaviour without requiring special privileges or special configurations. Before you start implementing your probe, please check in the POEM library if appropriate probe is already used for monitoring services.","s":"Service probe","u":"/argo-monitoring/docs/monitoring/SP_guide","h":"#service-probe","p":134},{"i":148,"t":"This Website uses technologies such as \"cookies\" and \"pixel tags\". By browsing the webpage, the User agrees to the creation and use of cookies. If User does not wish to consent to the use of cookies, User may either disable them or discontinue browsing this webpage. For the purpose of this Policy, the following terms shall have the following meaning: \"Cookie\" or \"Cookies\": Cookies are small text or message files sent from the server of an organization and stored on your computer. Cookies do not have access to data stored on your computer's hard disk or to Cookies placed by other websites, and they may not harm or damage your system. \"Persistence cookies\" remain during multiple website visits and get stored on your hard disk. \"Session Cookies\" are temporary cookies that disappear automatically after you leave a website; \"Third Party Cookies\" are cookies used by the websites of our partners, as integrated in our own Website or used by websites we link to.","s":"1. Purpose of this cookie policy","u":"/argo-monitoring/docs/policies/CookiePolicy","h":"#1-purpose-of-this-cookie-policy","p":146},{"i":150,"t":"When you access and/or use the Website, we place one or more Cookies on your device for the purposes described herein. The following table and relevant information set out the cookies used for the Website.It also provides details of third parties setting cookies: Cookie Type Cookie Provider Cookie Name Third party cookie Persistent or session Cookie Purpose of cookie Session State WEBUI URL JSESSIONID No Session Preserve user session information","s":"2. Which cookies are placed on your device when using our Website?","u":"/argo-monitoring/docs/policies/CookiePolicy","h":"#2-which-cookies-are-placed-on-your-device-when-using-our-website","p":146},{"i":152,"t":"The duration for which a cookie will be stored on your browsing device depends on whether it is a \"persistence\" or a \"session\" cookie. Session cookies will be stored on a device until you turn off your web browser. \"Persistence cookies\" shall remain on your device after you have finished browsing until they expire or until they are deleted by you.","s":"3. How long are cookies stored on your device?","u":"/argo-monitoring/docs/policies/CookiePolicy","h":"#3-how-long-are-cookies-stored-on-your-device","p":146},{"i":154,"t":"You can usually use your web browser to enable, disable, or delete cookies. To do so, follow the instructions provided for by your web browser (usually located in the \"Help\", \"Tools\" or \"Edit\" settings). You can also set your web browser to reject all cookies or to indicate when a cookie is being sent.","s":"4. How can you disable cookies that have been placed on your device?","u":"/argo-monitoring/docs/policies/CookiePolicy","h":"#4-how-can-you-disable-cookies-that-have-been-placed-on-your-device","p":146},{"i":156,"t":"By registering as a user you declare that you have read, understood and will abide by the following conditions of use: You shall only use the resources/services to perform work, or transmit or store data consistent with the stated goals, policies and conditions of use as defined by the body or bodies granting you access. You shall provide appropriate acknowledgement of support or citation for your use of the resources/services provided as required by the body or bodies granting you access. You shall not use the resources/services for any purpose that is unlawful and not (attempt to) breach or circumvent any administrative or security controls. You shall respect intellectual property and confidentiality agreements. You shall protect your access credentials (e.g. private keys or passwords). You shall keep all your registered information correct and up to date. You shall immediately report any known or suspected security breach or misuse of the resources/services or access credentials to the specified incident reporting locations and to the relevant credential issuing authorities. You use the resources/services at your own risk. There is no guarantee that the resources/services will be available at any time or that their integrity or confidentiality will be preserved or that they will suit any purpose. You agree that logged information, including personal data provided by you for registration purposes, may be used for administrative, operational, accounting, monitoring and security purposes. You agree that this logged information may be disclosed to other authorised participants via secured mechanisms, only for the same purposes and only as far as necessary to provide the services. You agree that the body or bodies granting you access and resource/service providers are entitled to regulate, suspend or terminate your access without prior notice and without compensation, within their domain of authority, and you shall immediately comply with their instructions. You are liable for the consequences of your violation of any of these conditions of use, which may include but are not limited to the reporting of your violation to your home institute and, if the activities are thought to be illegal, to appropriate law enforcement agencies.","s":"Terms Of Use","u":"/argo-monitoring/docs/policies/Terms","h":"","p":155},{"i":158,"t":"Controller details Α public limited company (societe anonyme) under the corporate name \"National Infrastructures for Technology and Research S.A.\" and the distinctive title \"GRNET S.A.\" Controller's Contact Details dpo at grnet.gr Processor Details ARGO Support Team Processor's Contact Details argo at grnet.gr Scope of this Privacy Statement National Infrastructures for Technology and Research S.A. (hereinafter referred to as \"GRNET SA\") is bound by European Regulation 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of individuals with regard to the processing of personal data and on the free movement of such data (General Data Protection Regulation -- hereinafter referred to as \"the GDPR\") and Law 4624/2019 (Government Gazette 137/A/2019) on \"Data Protection Authority, measures for the implementation of Regulation(EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of individuals with regard to the processing of personal data and for the incorporation into national law of Directive(EU) 2016/680 of the European Parliament and of the Council of 27 April 2016 and other provisions\", as in force at any time (hereinafter referred to as \"the Law\"). This Privacy Statement details all information necessary for the processing of personal data carried out in the context of Argo Service Monitoring., as well as the policies and procedures implemented by GRNET SA for the protection of the Argo Service Monitoring users privacy. This Privacy Statement sets out the criteria as well as the terms and conditions under which GRNET SA collects, processes, uses, stores and transmits the personal data of the service users, how it ensures the confidentiality of such information, including any law and/or regulation implemented or enacted in accordance with Union and national laws on personal data protection and electronic privacy, as well as any law and/or regulation amending, replacing, issuing or consolidating any of the latter, including any other applicable Union and national laws on the processing of personal data and privacy, which may exist in accordance with applicable law. GRNET SA reserves the right to amend and update this Privacy Statement whenever necessary, whereas any such updates shall become effective five (5) days after they have been posted on the Argo Service Monitoring website. For the purposes of this Privacy Statement, the terms \"processor\", \"controller\", \"third party\", \"supervising authority\", \"personal data\", \"processing\", \"data subject\" shall have the meaning ascribed to them by applicable legislation on the protection of personal data. In addition, for the purposes of the present, the following definitions shall also apply: \"Website\" -- the website accessible via domain name web-ui-url including the entirety of the web pages thereof. \" Argo Service Monitoring Service\" - web-ui-url \"User\"- the Argo Service Monitoring online service user, whom the data refers to, whose identity is known or may be verified, namely it may be directly or indirectly determined.","s":"Privacy Policy","u":"/argo-monitoring/docs/policies/Privacy","h":"","p":157},{"i":160,"t":"i. GRNET SA-- as processor -- processes its \"users\" personal data as referred to in the following section, for the following purposes: Authentication of Argo Service Monitoring service users \"Users\" authentication is carried out through the login service Federated AAI Providing the Argo Service Monitoring service Seamless operation of the \"website\" and the Argo Service Monitoring service. Technical support to the \"coordinators\" of the Argo Service Monitoring service Easy and user friendly operation of the \"website\". Enhancement of the online experience in providing Argo Service Monitoring services Proof of Acceptance of the Terms of Use and the Privacy Statement Creation of statistical reports and charts to monitor the Argo Service Monitoring service Statistical reports and charts data do not contain any \"users\" personal data, as they result from anonymized information. ii. GRNET S.A. -- as the processor -- collects and processes personal data of \"users\" using its infrastructure for the purpose of providing the Argo Service Monitoring.","s":"A. Purpose/s for processing the data collected:","u":"/argo-monitoring/docs/policies/Privacy","h":"#a-purposes-for-processing-the-data-collected","p":157},{"i":162,"t":"i. For the Authentication of Argo Service Monitoring \"users\" The authentication of the service \"users\" is carried out through the Federated AAI service, the local login of individual components. For the sole purpose of the authentication of the service \"users\", GRNET SA collects through the aforementioned authentication procedure, and processes -- as processor- the following personal data per component: ARGO MONITORING - WEB UI Name Surname e-mail address Affiliation, in broad categories such as student, faculty, staff, alum, etc, within a particular security domain representing the organisation or sub-organisation of the affiliation Group membership and role information for the sole purpose of their authorised access to the service In addition to the personal data retrieved through the aforementioned authentication procedure, the service collects the following personal data: Name Surname e-mail address Unique identifier for the sole purpose of their authentication in the service (Persistent Id). *( Analysis of usage data (Google Analytics): Our website uses Google Analytics, a web analysis service provided by Google Inc., 1600 Amphitheatre Parkway Mountain View, CA 94043, USA (\"Google\"). Google Analytics uses cookies (text files which are stored on your computer and which enable an analysis of your use of the website). The information generated by the cookie about your use of our website will generally be transmitted to and stored by Google on servers in the United States. With the activation of IP anonymization on our website (see below), your IP address will be shortened by Google within member states of the European Union or in other contracting states of the Agreement on the European Economic Area. Only in exceptional cases will the full IP address be transmitted to a Google server in the USA and shortened there. Google will use this information on our behalf to evaluate your use of our website, to compile reports on website activity and to provide us with other services relating to website activity and internet usage. The IP address transmitted by your browser as part of Google Analytics is not combined with other data from Google. You can prevent the collection of the data generated by the cookie and related to your use of our website (including your IP address) and transmission to Google as well as the processing of this data by Google by downloading and installing the browser extension (plug-in) available under this link. For more information about privacy at Google Analytics, please see Google's privacy policy. ARGO MONITORING - POEM User Name Name Surname e-mail address Last Login Group membership and role information for the sole purpose of their authorised access to the service In addition to the personal data retrieved through the aforementioned authentication procedure, the service collects the following personal data: Distinguished Name Display Name Unique identifier for the sole purpose of their authentication in the service (Persistent Id). ARGO MONITORING - Monitoring box Unique identifier for the sole purpose of their authentication in the service (Persistent Id). In addition to the personal data retrieved through the X509 authentication procedure, the service collects the following personal data: Distinguished Name Display Name ii. For providing the Argo Service Monitoring service For the use of the Argo Service Monitoring service as well as for the efficient and lawful provision of this service, GRNET SA processes -- as processor -- the following personal data: The IP address wherefrom the \"user \"connects to the Argo Service Monitoring service The X509 certificates Service use timestamp \"Users\" e-mail address. iii. For communicating with Argo Service Monitoring service \"users\" For communicating with Argo Service Monitoring service \"users\", GRNET SA processes - as processor - the following personal data: E-mail address iv. Special categories of personal data GRNET SA does not collect, process or gain access in any way to specific data categories, as set forth in the provisions of the legislation in force (in particular data relating to racial or ethnic origin, religion, health data, etc.). In the event that a \"user\" posts any such special category data on the \"website\" or on the Argo Service Monitoring, such data will be removed as soon as the management team become aware thereof.","s":"B. Categories of personal data processed:","u":"/argo-monitoring/docs/policies/Privacy","h":"#b-categories-of-personal-data-processed","p":157},{"i":164,"t":"The processing of \"users\" personal data is necessary for the performance of the Agreement on the provision of Argo Service Monitoring services, in accordance with the needs (technical and organisational) to provide the best possible services, to serve the \"users\".","s":"C. Legal bases for processing","u":"/argo-monitoring/docs/policies/Privacy","h":"#c-legal-bases-for-processing","p":157},{"i":166,"t":"For providing Argo Service Monitoring services and the seamless operation of such services, access to the \"users\" personal data shall be granted to the following: To the Argo Service Monitoring service support team, consisting of personnel engaged in a contractual relationship of either a project or an independent service agreement with GRNET SA. hereinafter referred to as \"GRNET associates\". From SRCE, CNRS / IN2P3 hereinafter referred to as \"GRNET Project Partners\". The processing of Argo Service Monitoring service \"users\" personal data by the aforementioned, is carried out under the supervision and only at the request of GRNET SA, within the scope of the mission and the role of each associate. Such associates undertake to comply with the same privacy and personal data requirements as GRNET SA itself in accordance to the present Privacy Statement","s":"D. Access to personal data:","u":"/argo-monitoring/docs/policies/Privacy","h":"#d-access-to-personal-data","p":157},{"i":168,"t":"GRNET SA shall in no way transmit or in any way disclose the Argo Service Monitoring service \"users\" personal data to any third-party entities, private businesses, natural persons or legal entities, public authorities, agencies or other organizations, other than as expressly set out herein. The Argo Service Monitoring service \"users\" personal data may be disclosed or transmitted to governmental authorities and/or law enforcement officials, only if necessary for the abovementioned purposes, in the context of enforcement of a court decision or a provision of law or if necessary to secure the legitimate interests of GRNET SA in its capacity as processor, in compliance with the terms and conditions of applicable law.","s":"E. Recipients of collected personal data:","u":"/argo-monitoring/docs/policies/Privacy","h":"#e-recipients-of-collected-personal-data","p":157},{"i":170,"t":"The Argo Service Monitoring service users personal data shall be retained no longer than it is necessary for the needs of the service and the audits the service is subjected to. More specifically: Categories of personal data collected Time and place of retention of personal data IP address Data from website navigation through Cookies 18 months (log retention) Unique User Identifier User Name Name Surname e-mail address Last Login Distinguished Name Display Name 18 months (db) for the Unique user Identifier, User Name, Name, Surname, e-mail address, Last Login, Distinguished Name, Display Name will be deleted on user request","s":"G. Personal data retention periods","u":"/argo-monitoring/docs/policies/Privacy","h":"#g-personal-data-retention-periods","p":157},{"i":172,"t":"The processing of personal data by GRNET SA is performed in a manner that ensures both confidentiality and security thereof. All appropriate organisational and technical measures shall be taken to safeguard data against any accidental or unlawful destruction, accidental loss, alteration, prohibited dissemination or access or any other form of unfair processing. The services provided by GRNET SA are constantly evaluated to be in line with the safety requirements of international standards. GRNET's Information Security Management System (ISMS) has been certified by the accredited certification body, EUROCERT SA In particular: Access to technical log data is restricted and can only be accessed in a secure way by the Argo Service Monitoring service staff. When accessing the Argo Service Monitoring service adequate security controls are in place to keep your personal data safe in accordance with the classification of the personal data we have collected from you. We use encryption (HTTPS) to keep data private while in transit. Data sent using HTTPS is secured via Transport Layer Security protocol (TLS), which provides: Encryption---encrypting the exchanged data to keep it secure from droppers. Data integrity---data cannot be modified or corrupted during transfer, intentionally or otherwise, without being detected. Authentication---proves that your users communicate with the intended website. The implementation of the Argo Service Monitoring service ensures that no unauthorized user can log into the service. An authorised user means a service user, who has an active account with the Federated AAI service, having passed the authentication process mentioned above. We review our information collection, storage, and processing practices, including physical security measures, to prevent unauthorized access to our systems Although we follow best security practices to ensure your personal data remains secure, there is no absolute guarantee of security when using services online. While we strive to protect your personal data, you acknowledge that: There are security and privacy limitations on the internet which are beyond our control and can have a negative impact on the confidentiality, integrity and availability of the information. We cannot be held accountable for activity that results from your own neglect to safeguard the security of your login credentials and equipment which results in a loss of your personal data. If you feel this not enough, then please do not provide any personal data. Your personal data will be protected according to the Code of Conduct for Service Providers , a common standard for the research and higher education sector to protect your privacy.","s":"H. Privacy and Security of Information:","u":"/argo-monitoring/docs/policies/Privacy","h":"#h-privacy-and-security-of-information","p":157},{"i":174,"t":"For any questions or clarifications regarding the present Privacy Statement and as well as in the event of any violation related to personal data issues, \"users\" may contact the Competent Department of GRNET SA at the e-mail address mentioned hereinabove. They may also contact the Data Protection Officer (DPO) of GRNET S.A., Ms. Vera Meleti, and/or the deputy DPO, Ms. Vasiliki Konstantinopoulou at the e-mail address: dpo@grnet.gr.","s":"I. Contact:","u":"/argo-monitoring/docs/policies/Privacy","h":"#i-contact","p":157},{"i":176,"t":"In the event that any Argo Service Monitoring \"user\" request is not satisfied by the processor, the \"user\" may at any time address to/ file recourse with the Competent Supervisory Authority, namely the Data Protection Authority https://www.dpa.gr .","s":"K. Recourse/Complaint:","u":"/argo-monitoring/docs/policies/Privacy","h":"#k-recoursecomplaint","p":157},{"i":178,"t":"This document describes the technical and organisational measures established by National Infrastructures for Research and Technology S.A. (GRNET S.A.) to meet legal and contractual requirements when processing personal data, conducting a higher level of security and protection. The definitions in Article 32 of the GDPR apply.","s":"Technical and organisational measures (TOM)","u":"/argo-monitoring/docs/policies/tom","h":"","p":177},{"i":181,"t":"Actions suitable for providing physical and environmental security of data centers, server room facilities, and working areas are adapted, while precautions against environmental threats and power disruptions are also granted. Access is limited by job role and subject to authorised approval. Technical and organisational measures that are taken into account involve security guard personnel, reception, doorbell systems, manual locking systems, and video surveillance of entrances. Entrance to the building is only possible with keycards and keys provided to authorised employees or by visitors accompanied by employees, preventing unauthorised persons from accessing secured areas. Additionally, Information on security policy, work instructions for operational safety, and access control are provided.","s":"1.a. Physical Access Control","u":"/argo-monitoring/docs/policies/tom","h":"#1a-physical-access-control","p":177},{"i":183,"t":"Operations sufficient for preventing data processing systems from being used by unauthorised persons are applied. Logical access controls are designed based on authority levels and job functions. Granting access is gained on a need-to-know and least privilege basis, where it is restricted to authorised employees responsible for the job. The use of unique IDs -identified through Active Directory- and passwords for all users is adapted, including a periodic review and revoking access when employment terminates or changes in job functions occur. Technical and organisational measures that are taken into account involve; username and password protected systems, intrusion detection facilities, use of Virtual Private Networks (VPNs) for remote access, firewalls, intrusion Detection System (IDS), user permission management, information security policy, work instruction of IT user regulations, operation security and access control.","s":"1.b. Logical Access Control","u":"/argo-monitoring/docs/policies/tom","h":"#1b-logical-access-control","p":177},{"i":185,"t":"Actions to ensure that those authorized to use a data processing system can only access the data subject to their access authorization -based on their rule- and that personal data cannot be read, copied, modified, or removed without authorization during processing, use and after storage. Technical operations incorporate physical deletion of data carriers, logging of accesses to applications, specifically when entering, changing, and deleting data, SSH encrypted access, and certified SSL encryption. At the organisational level, a minimum number of administrators is applied, management of user rights are controlled by administrators, work instruction communication security and handling of information and values are also claimed.","s":"1.c. Authorization Control","u":"/argo-monitoring/docs/policies/tom","h":"#1c-authorization-control","p":177},{"i":187,"t":"It is ensured that personal data collected for different purposes can be processed separately. Multi-tenancy of relevant applications is performed, or systems are physically or logically separated. The development sheet is separated for each product, and the services have their own line of environments. All environments, documents and other data are shared for the members of that project/product, while operational, information and data protection securities and policies are applied.","s":"1.d. Separation Control","u":"/argo-monitoring/docs/policies/tom","h":"#1d-separation-control","p":177},{"i":189,"t":"Operations for pseudonymization or anonymization of personal data are implemented to the extent necessary. Internal instruction to pseudonymize or anonymize personal data as far as possible in the event of disclosure or even after the statutory deletion period has expired. Specific internal regulations on cryptography, while operational, information and data protection securities and policies are applied.","s":"1.e. Pseudonymization","u":"/argo-monitoring/docs/policies/tom","h":"#1e-pseudonymization","p":177},{"i":192,"t":"Measures are taken into account to ensure that personal data cannot be read, copied, altered or removed by unauthorized persons during electronic transmission or while being transported or stored on data media. As technical and organizational actions are the use of Virtual Private Networks (VPNs) and firewalls, the provision via encrypted connections and techniques such as SSH, SFTP, HTTPS and secure cloudstores, the logging of accesses and retrievals, while operational, information and data protection securities and policies are also applied.","s":"2.a. Transfer Control","u":"/argo-monitoring/docs/policies/tom","h":"#2a-transfer-control","p":177},{"i":194,"t":"Operations that ensure that it is possible to check and establish retrospectively whether and by whom personal data has been entered into, modified or removed from data processing systems are implemented to the extent necessary. Input control is achieved through logging, which can take place at various levels (e.g., operating system, network, firewall, database, application). Traceability of data entry, modification and deletion through individual user names, assignment of rights to enter, change and delete data on the basis of an authorisation concept, while information security policy and work instruction of IT user regulations are engaged.","s":"2.b. Input Control","u":"/argo-monitoring/docs/policies/tom","h":"#2b-input-control","p":177},{"i":197,"t":"Actions to ensure that personal data is protected against accidental destruction or loss have been implemented to the required extent. Measures comprise fire and smoke detection systems, fire extinguishers, air-conditioning, temperature and humidity monitoring and video surveillance in server rooms, UPS system and emergency diesel generators deployment, RAID system and hard disk mirroring for data backup, information security policy and work instruction operational security.","s":"3.a. Availability Control","u":"/argo-monitoring/docs/policies/tom","h":"#3a-availability-control","p":177},{"i":199,"t":"Data backups of databases and operating system images are taken to the extent required and with the aim of preventing the loss of personal data in the event of physical or technical incident. Backups are performed for network drives and servers in productive operation, where the process is being recorded (logged). The backup concept is applied according to criticality and customer specifications. When applicable storage of backup media obtained in a safe place outside the server room. Information security policy and work instruction of IT user regulations are also engaged.","s":"3.b. Recoverability Control","u":"/argo-monitoring/docs/policies/tom","h":"#3b-recoverability-control","p":177},{"i":202,"t":"Technical and organizational measures that are taken into account are; central documentation of all data protection regulations with access for employees, security certification according to ISO 27001. Updates and reviews of the effectiveness of the TOMs are carried out periodically. Data protection checkpoints are consistently implemented, while data processing systems (IT systems) are checked regularly to the extent required and after changes to ensure that they are functioning properly. A Data Protection Officer (DPO) group is appointed and notified of physical or technical incidents, and staff is trained and obliged to confidentiality and data secrecy. Data Protection Impact Assessment (DPIA) is carried out as required, whereas processes regarding information obligations according to Art. 13 and 14 GDPR are established.","s":"4.a. Data Protection Management","u":"/argo-monitoring/docs/policies/tom","h":"#4a-data-protection-management","p":177},{"i":204,"t":"Technical and organizational actions have been established to the extent required for security breach response and data breach process. The use and the regular updating of firewall, spam filters, virus scanning, Intrusion Detection System (IDS), and Intrusion Prevention System (IPS) for customer systems on order, are served. The process for detecting and reporting security incidents and data breaches is being documented via ticket system, with regard to reporting obligation to the supervisory authority. Formalized procedure for handling security incidents, including the involvement of DPO and ISO in security incidents and data breaches is available, while operational, information, data protection and IT user regulations, securities and policies are also applied.","s":"4.b Incident Response Management","u":"/argo-monitoring/docs/policies/tom","h":"#4b-incident-response-management","p":177},{"i":206,"t":"Measures pursuant to Art 25 GDPR comply with the principles of data protection by design and by default. No more personal data is collected than is necessary for the respective purpose. Data Protection Policy (includes principles \"privacy by design and by default\").","s":"4.c Data Protection by Design and by Default","u":"/argo-monitoring/docs/policies/tom","h":"#4c-data-protection-by-design-and-by-default","p":177},{"i":208,"t":"Actions to ensure that personal data processed on behalf of the client can only be processed in accordance with the client's instructions. Technical and organizational measures have been established to the required extent. Measures involve monitoring of remote access by external parties, in the context of remote support and work instruction supplier management and supplier evaluation. Moreover, a prior review of the security measures taken by the contractor and their documentation is applied. Selection of the contractor under due diligence aspects (especially with regard to data protection and data security) is achieved. Conclusion of the necessary data processing agreement on commissioned processing or EU standard contractual clauses and a framework agreement on contractual data processing within the group of companies, where written instructions to the contractor and obligation of the contractor's employees to maintain data secrecy. Additionally, an agreement on effective control rights over the contractor and regulations on the use of further subcontractors is maintained, ensuring also the destruction of data after termination of the contract or in the case of longer collaboration, ongoing review of the contractor and its level of protection.","s":"4.d Order Control (outsourcing, subcontractors, and order processing)","u":"/argo-monitoring/docs/policies/tom","h":"#4d-order-control-outsourcing-subcontractors-and-order-processing","p":177},{"i":210,"t":"The National Infrastructures for Research and Technology S.A. (GRNET S.A.), based on Its Quality and Information Security Policies has set itself the goal of providing products and services to be delivered at the highest possible level of information security in compliance with the law. In this context GRNET S.A. has established, the roles of Information Security Officer (ISO), Data Protection Officer (DPO), Quality Officer (QO), and Legal Compliance Officer (LCO) as well as a Corporate Binding Rules (a set of internal guidelines and regulations) on information security and data protection, that are contractually binding for all employees, that defines secure information and data handling formed in secrecy and confidentiality. Employees are continuously informed and trained in the area of data protection, while third parties who may come into contact with personal data in the course of their work for GRNET S.A. are obligated to comply with data protection and data secrecy by means of a so-called NDA (Non-Disclosure Agreement) before they begin their work. Any subcontractors entrusted with further processing are only used after approval by the clients and after the conclusion of a Data Processing Agreement (DPA) in accordance with Art 28 GDPR, with which they are fully bound by all data protection obligations to which GRNET S.A. itself is subject. Current high technical security standards at GRNET S.A. are periodically reviewed and confirmed for adequacy and effectiveness in the course of ongoing internal audits and annually by Independent, External, Accredited Certification Bodies.","s":"5. Organization and Data Protection","u":"/argo-monitoring/docs/policies/tom","h":"#5-organization-and-data-protection","p":177},{"i":212,"t":"The Quality Management System (QMS) as well as the Information Security Management System (ISMS) of GRNET S.A. are both certified by Independent Accredited Certification Bodies according to ISO 9001 and ISO 27001.","s":"6. Certifications","u":"/argo-monitoring/docs/policies/tom","h":"#6-certifications","p":177},{"i":215,"t":"An aggregation profile defines how to aggregate service statuses into higher hierarchical grouping (i.e. a service_group) status results. They are actually used to define logical rules on how to aggregate individual status computations into groups.","s":"Description","u":"/argo-monitoring/docs/profiles/aggregation-profile","h":"#description","p":213},{"i":217,"t":"ARGO allows you to combine your monitored items into hierarchies of groups giving you the ability to represent real world structures of your data centers, organizations, service offerings, federations etc. The most basic level that everything else is built upon is the level of the service endpoint. A service endpoint is actually the host plus the service instance that runs on that host. For example you might have a bare metal machine (host) named db01.example.com that hosts an instance of a mysql database on port 3306. In this example the service endpoint being the combination of the hostname plus the type of the service running on the host gives: service endpoint = db01.infra.example.com(mysql)","s":"Grouping of monitored items","u":"/argo-monitoring/docs/profiles/aggregation-profile","h":"#grouping-of-monitored-items","p":213},{"i":219,"t":"You might offer mysql as a cluster which actually depends on the following service endpoints such as: db01.infra.example.com(mysql) db02.infra.example.com(mysql) db03.infra.example.com(mysql) Now you want to have a combined view for the service offering (mysql cluster) as a whole that includes a daily timeline of the status that your mysql offering and the corresponding availability / reliability score results. The mysql cluster might be deployed in an distributed way so that every host must be in a working OK condition in order to consider that the general mysql offering is OK. Or it might be deployed in a high availability fashion so even if one of the service endpoints is in working condition (OK state) the whole mysql offering is considered to be working (OK). As mentioned previously, operation profiles describe the ways that we combine items into groups based on the way they are working together (distributed/ha). Usually an operation profile declares possible states that monitored items might have and how these states are combined through combine operations/actions (namely “AND”, “OR” logical operations between items as described here: link Important: If operations profile describe the available states and the combination operations possible upon them, the aggregation profile describes where those operation take place in the hierarchy of groups we are trying to create In the previous example of mysql service offering the aggregation profile will include a declaration that endpoints of mysql service types are combined into service groups of mysql offerings through an ‘OR’ combination operation because our mysql clusters are deployed in a highly available way.","s":"Combining endpoints to service offerings","u":"/argo-monitoring/docs/profiles/aggregation-profile","h":"#combining-endpoints-to-service-offerings","p":213},{"i":221,"t":"You might have another service offering in your infrastructure that provides along with the database a cloud storage platform such as nextcloud. Similar to the database you might have the following endpoints: cloud01.infra.example.com(nextcloud) cloud02.infra.example.com(nextcloud) And you want to combine them in a single nextcloud offering that actually is distributed among them so you must combine them in an “AND” fashion (again see link) The aggregation profile in this case will include another entry that defines that the nextcloud endpoints are combined through an ‘AND’ operation to a higher level nextcloud service offering. Finally you might want to provide a high level group of your infrastructure that includes all service offerings (mysql and nextcloud). In this case you might have something like: infra.example.com (my infrastructure) | | (*offers) | |________ nextcloud service | | | | | (*has HA components) | | | |__ db01.infra.example.com | |__ db02.infra.example.com | |__ db03.infra.example.com | |_________mysql service | | (*has distributed components) | |__ cloud01.infra.example.com |__ cloud02.infra.example.com So the case might be that the nextcloud service and the mysql service must be combined in an ‘AND’ fashion in order to provide a general picture for the whole infrastructure (infra.example.com). This is also something that we define in the aggregation profile. To sum it up, the aggregation profile comes along with the operation profile and defines what kind of levels and groups our monitored items are going to be combined to and with what kind of operations (AND/OR etc…). The operations are declared and named on the operations profile and they are referenced by name in the aggregations profile. In the aggregation profile you cannot have references to operations that don’t exist in the accompanied aggregation profile.","s":"Combining service offerings to higher groups","u":"/argo-monitoring/docs/profiles/aggregation-profile","h":"#combining-service-offerings-to-higher-groups","p":213},{"i":223,"t":"The aggregation profile has the following information: A name (obviously) A reference to a metric profile attached to it (to know what kind of service types are relevant) The type of high level group representation that our service offerings are organized to (for example: DATACENTER, INFRASTRUCTURE, ORGANIZATION, SITE, SERVICEGROUP etc…) Some general types of combination operations applied globally such as: How are the individual metrics/checks are going to be combined for each endpoint How are the different high level groups are going to be combined to a final group etc… A detailed list of the high level groups we want to construct (representing as mentioned before data centers or infrastructures, or sites, or service groups etc…) and with what kind of operations each individual service type is combined to these groups The JSON format representation of an aggregation profile is provided in the following example: { \"name\": \"Infra_aggregation\", \"endpoint_group\": \"DATACENTER\", \"metric_operation\": \"AND\", \"profile_operation\": \"AND\", \"metric_profile\": { \"name\": \"my_infra_metrics\", \"id\": \"uuid-reference-here\" }, \"groups\": [ { \"name\": \"database\", \"operation\": \"OR\", \"services\": [ { \"name\": \"mysql\", \"operation\": \"OR\" } ] }, { \"name\": \"storage\", \"operation\": \"OR\", \"services\": [ { \"name\": \"nextcloud\", \"operation\": \"AND\" } ] } ] }","s":"Aggregation profile anatomy (JSON format)","u":"/argo-monitoring/docs/profiles/aggregation-profile","h":"#aggregation-profile-anatomy-json-format","p":213},{"i":226,"t":"An infrastructure may offer various services. These services need to be checked periodically in order to decide their operational state. The various functionalities of a given service are checked by metrics (a chunk of code). For example a metric such as Web-Site.Portal-WebCheck runs on a site and checks if the http connection responds or not. The results of the metrics are computed, into ARGO Monitoring Service calculations, in order to conclude into the operational state of the service, during a specific period. In order to conclude about the operational state of the service, all or part of the metrics that check the service’s functionality should be taken into account. In Metrics Profiles are included, for each service, these metrics whose results are considered to the computations of the service’s state. Example 1 - Metrics Profile for a Site service:​ A service of type Site runs on host1.example.com. The Site service should operate properly, be accessible and some actions should be available such as downloading or uploading material (documents, images etc). Three metrics can apply on the service to check it’s functionalities: Portal-WebCheck is a metric to check if the http responds http.download is a metric to check if download functionality operates well http.upload is a metric to check if upload functionality operates well The site is assumed to operate properly if it is accessible and can support downloading material. Uploading material does not affect the state of the service (whether it is working properly or not). So in the Metrics Profile, the metrics Portal-WebCheck and http.download will be defined in order to be taken into account for concluding the status of the Site. Example 2 - Metrics Profile for a Repository service:​ A service of type Repository runs on host2.example.com. The repository is considered to operate properly if it is accessible and validates the provided certificates. Two metrics can apply on the service to check it’s functionalities: Portal-WebCheck is a metric to check if the http responds CertValidity is a metric to check if the certification is valid In order to conclude the operational state of the repository both functionalities should operate properly. So in the Metrics Profile both metrics will be defined in order to be taken into account for concluding the status of the Repository. The above examples could be represented by the following Metrics Profile definition: \"services\": [ { \"service\": \"WEB-SITE\", \"metrics\": [ \"http.download\", \"Portal-WebCheck\" ] }, { \"service\": \"www.example-repository.com\", \"metrics\": [ \"Portal-WebCheck\", \"CertValidity\" ] } ]","s":"Description","u":"/argo-monitoring/docs/profiles/metrics-profile","h":"#description","p":224},{"i":229,"t":"I would like to know the percentage of metrics that appear CRITICAL status (a.k.a failure) due to network problems. Is this possible? . This was a question we had to reply to, some time ago. And now yes it is possible. In order to support this functionality, some semantics (tags) are added to metrics to categorize them. A metric could be characterized by multiple tags. By this categorization it is easy to conclude into statistics about each metric category. An infrastructure may offer various services, of which functionality is checked periodically by metrics. Each metric can be characterized / grouped via different ways. We could say that they could be grouped : by the functionality they check the reason for failure or any other characteristic","s":"Description","u":"/argo-monitoring/docs/profiles/metrics-tags","h":"#description","p":227},{"i":231,"t":"For example a metric can be a metric that has to deal with a network or with an authentication check. This means that we may characterize that the service or service component may fail due to network problems or due to authentication problems etc. At the same time, this helps the monitoring service to characterize and organize the metrics in groups and provide insights and trends for the different levels of topology (Infrastructure / Groups / Services / Service components) . This helps us easily to conclude into statistics about each metric category. It is useful to acknowledge statistics of each metric category or each metric failure reason, or any other characteristic. http.download is a metric to check if download functionality operates well http.upload is a metric to check if upload functionality operates well The two metrics can fail due to network problems CertValidity is a metric to check if the certification is valid, it is an authentication check and can fail due to invalid certificate or connection problems the metric tags profile for these metrics could be: { \"name\": \"http.download\", \"tags\": [ \"network\" ] }, { \"name\": \"http.upload\", \"tags\": [ \"network\" ] }, { \"name\": \"CertValidity\", \"tags\": [ \"auth\", \"invalid\",\"internal\" ] } During the computations the tag information about each metric check is preserved and added to the results when needed. This information can be used for further computations applied on metric tags.","s":"Example - Metric Tags","u":"/argo-monitoring/docs/profiles/metrics-tags","h":"#example---metric-tags","p":227},{"i":233,"t":"The connection of the Metric Tags profiles with the other components of ARGO They are: defined in POEM stored in ARGO Web API Used for the computations in the Analytics Engine Presented in the ARGO Web UI.","s":"Technical part","u":"/argo-monitoring/docs/profiles/metrics-tags","h":"#technical-part","p":227},{"i":236,"t":"The ARGO Monitoring Service is generating Status and A/R reports based on the metric results that it gathers from the execution of the monitoring probes. Each metric result includes a status and performance data that typically contain values related to the provided status. Currently the ARGO Monitoring Service relies solely on the statuses returned by the probes in order to generate the Status and A/R reports. Each probe has a hard-coded built-in static logic in order to compute the probe status. Although this have been proven sufficient for the purposes of infrastructure monitoring up to now, it does not give us any flexibility in providing different SLA targets customers. For example, let’s say that a probe check the average response time of the tickets in helpdesk system. With the current implementation, the acceptable response time is part of the probe configuration. If we want to have different acceptable response time for a specific customer, then we will have to create a new probe configuration and execute a new test. So in order to have different acceptable response time for each customer, we have to easily define these hardcoded values and use them as parameters. So actually we have to move the metric status computation to something more dynamic like the ARGO analytics engine. So the monitoring probes executed will return the actual data (e.g. the average response time) and then on the ARGO Analytics Engine we can have use multiple threshold profiles, which will be used in order to generate reports based on the customer needs.","s":"Description","u":"/argo-monitoring/docs/profiles/thresholds-profile","h":"#description","p":234},{"i":238,"t":"Let's take the check_ping as an example which returns the packet loss and lets assume that it has been enhanced to return average round trip time as a response. Sample output from the metric check might look like this: PING ok - Packet loss = 0%, response=0.80 | response=20ms;0;300;299;1000 This is the default result of the metric. In our example we have 2 hosts webserver01.example.com webserver02.example.com The SLA defines a different response times for each of them. In order to achieve that we have to define 2 different thresholds one for each host. The way to define the thresholds follow the following format. 'label'=value[UOM];[warn];[crit];[min];[max] where label : can contain alphanumeric characters but must always begin with a letter value : is a float or integer uom : is a string unit of measurement (accepted values: s,us,ms,B,KB,MB,TB,%,c) warning: is a range defining the warning threshold limits critical: is a range defining the critical threshold limits So based on the SLA we define the following 2 thresholds host: webserver01.example.com thresholds: response=20ms;0:200;199:300 host: webserver02.example.com thresholds: response=20ms;0:500;499:1000 BY using the threshold profiles, we managed to have different Warning and Critical limits for webserver01.example.com and webserver02.example.com and we support them for their SLA.","s":"Example","u":"/argo-monitoring/docs/profiles/thresholds-profile","h":"#example","p":234},{"i":240,"t":"The connection of the Threshold profiles with the other components of ARGO They are: defined in POEM stored in ARGO Web API part of a report and the correlation is also configured in POEM Used for the computations in the Analytics Engine Presented in the ARGO Web UI.","s":"Technical part","u":"/argo-monitoring/docs/profiles/thresholds-profile","h":"#technical-part","p":234},{"i":243,"t":"Flapping occurs when a service or host changes state too frequently, resulting in a storm of problems and recovery notifications. Flapping can be indicative of configuration problems (i.e. wrong configuration between the monitored item and the monitoring host), troublesome services, or real network problems. This causes a lot of alarms and notifications. ARGO Monitoring service analyzes the status timelines in different levels, detects the flapping patterns and creates a report with the list of the most problematic monitored items. It actually analyzes the stream of collected status data (monitoring results) in a big data friendly platform (analytics engine) and traces flapping patterns almost immediately. It uncovers hidden patterns, correlations and other insights and informs the user.","s":"Description","u":"/argo-monitoring/docs/reports/flapping-trends","h":"#description","p":241},{"i":245,"t":"Flapping can occur due to network problems between monitoring host and monitored item for example:","s":"Examples","u":"/argo-monitoring/docs/reports/flapping-trends","h":"#examples","p":241},{"i":247,"t":"ARGO Monitoring service monitors HTTP activity in host1.example.com using the check_http check. Due to network issues between the ARGO Monitoring service and host1.example.com a pattern arises that some http checks are successful (OK) and some are critical (CRITICAL) (in successive order) as shown in picture: Result​ Based on this behaviour, during the data computations, the service is flagged as a flapping service, and it is included in the list of flapping services presented in the ARGO Monitoring UI.","s":"Example 1: Flapping due to network issue","u":"/argo-monitoring/docs/reports/flapping-trends","h":"#example-1-flapping-due-to-network-issue","p":241},{"i":249,"t":"ARGO Monitoring service monitors the file upload functionality in host2.example.com (object storage) using the file upload check. Due to an internal error of the service, the check uploads a file successfully (OK), then issues a deletion request on it but the deletion takes too long. In a second attempt to re-upload the file the check receives a warning (WARNING) until the deletion of the original is completed. This results in a repeating pattern of status being OK then WARNING, then again OK etc as shown in the following picture: Result​ Based on this behaviour, during the data computations, the service is flagged as a flapping service, and it is included in the list of flapping services presented in the ARGO Monitoring UI.","s":"Example 2: Flapping due to internal problem of the service","u":"/argo-monitoring/docs/reports/flapping-trends","h":"#example-2-flapping-due-to-internal-problem-of-the-service","p":241},{"i":252,"t":"In many cases we need to provide results for top level items that are being monitored. For example if a database service is offered that relies on 2 different hosts, then we need to present a timeline with the status of the service offering itself during the day. To do that we need to combine appropriately the status timelines observed for the hosts. There many ways to combine them but the usual cases are the following: Service is deployed in a high availability fashion among hosts, so we need one of them to be ok for the general service offering to be working. In this case we say that the timelines are combined in an “OR” fashion. E.g. if host1 = OK, host2= CRITICAL the database service will be OK (see figure 1) Service is deployed in a distributed fashion among hosts, so all of them are needed to be in a working state so as the service to be considered in working state. In this case we say that the timelines are combined in an “AND” fashion. E.g. if host1 = OK, host2 = CRITICAL the service offered will be CRITICAL (see figure 2) Figure 1: Service deployed in a high availability fashion Figure 2: Service deployed in a distributed fashion","s":"Combining timelines","u":"/argo-monitoring/docs/profiles/operations-profile","h":"#combining-timelines","p":250},{"i":254,"t":"Operations profiles are used in ARGO platform to declare ways in which the status timelines can be combined. Each operation profile is actually a configuration file in json format that consists of the following parts: Α section to declare and enumerate all available statuses produced by monitoring checks. ARGO is agnostic on the names and number of statuses that can be produced by monitoring checks and they can be declared here. The default profile includes the usual array of statuses used in most monitoring systems (such as nagios) and that includes the following: OK, WARNING, CRITICAL, UNKNOWN, MISSING and DOWNTIME A section to define some default states. For example here we can define that OK state means a working state etc. A section to declare all the available ways (operations) that these statuses can be combined to produce a top result. Here we have a list of operation names mapped to truth tables that contain all the available combinations of statuses and the produced results (see table 1, table 2) Table 1 - the operations profile for AND operations is given in the following tabular: AND OK WARNING UNKNOWN MISSING CRITICAL DOWNTIME OK OK WARNING UNKNOWN MISSING CRITICAL DOWNTIME WARNING WARNING WARNING UNKNOWN MISSING CRITICAL DOWNTIME UNKNOWN UNKNOWN UNKNOWN UNKNOWN MISSING CRITICAL DOWNTIME MISSING MISSING MISSING MISSING MISSING CRITICAL DOWNTIME CRITICAL CRITICAL CRITICAL CRITICAL CRITICAL CRITICAL CRITICAL DOWNTIME DOWNTIME DOWNTIME DOWNTIME DOWNTIME CRITICAL DOWNTIME As can be seen the most prominent status in the case of the “AND” operation is the CRITICAL, while the least prominent is the “OK” status. Table 2 - the operations profile for “OR” operations is given in the following tabular: OR OK WARNING UNKNOWN MISSING CRITICAL DOWNTIME OK OK OK OK OK OK OK WARNING OK WARNING WARNING WARNING WARNING WARNING UNKNOWN OK WARNING UNKNOWN UNKNOWN CRITICAL UNKNOWN MISSING OK WARNING UNKNOWN MISSING CRITICAL DOWNTIME CRITICAL OK WARNING CRITICAL CRITICAL CRITICAL CRITICAL DOWNTIME OK WARNING UNKNOWN DOWNTIME CRITICAL DOWNTIME In the case of “OR” the most prominent status result is the “OK”.","s":"The use of operation profiles","u":"/argo-monitoring/docs/profiles/operations-profile","h":"#the-use-of-operation-profiles","p":250},{"i":256,"t":"ARGO provides a default operation profile capable for being used in most monitoring requirements that includes 6 monitoring states: OK, WARNING, CRITICAL, UNKNOWN, MISSING, DOWNTIME and two available operations on combining them: OR and AND Below is the default operation profile used in JSON Format: { \"id\": \"profile_uuid\", \"date\": \"2015-01-01\", \"name\": \"profile_name\", \"available_states\": [ \"OK\", \"WARNING\", \"UNKNOWN\", \"MISSING\", \"CRITICAL\", \"DOWNTIME\" ], \"defaults\": { \"down\": \"DOWNTIME\", \"missing\": \"MISSING\", \"unknown\": \"UNKNOWN\" }, \"operations\": [ { \"name\": \"AND\", \"truth_table\": [ { \"a\": \"OK\", \"b\": \"OK\", \"x\": \"OK\" }, { \"a\": \"OK\", \"b\": \"WARNING\", \"x\": \"WARNING\" }, { \"a\": \"OK\", \"b\": \"UNKNOWN\", \"x\": \"UNKNOWN\" }, { \"a\": \"OK\", \"b\": \"MISSING\", \"x\": \"MISSING\" }, { \"a\": \"OK\", \"b\": \"CRITICAL\", \"x\": \"CRITICAL\" }, { \"a\": \"OK\", \"b\": \"DOWNTIME\", \"x\": \"DOWNTIME\" }, { \"a\": \"WARNING\", \"b\": \"WARNING\", \"x\": \"WARNING\" }, { \"a\": \"WARNING\", \"b\": \"UNKNOWN\", \"x\": \"UNKNOWN\" }, { \"a\": \"WARNING\", \"b\": \"MISSING\", \"x\": \"MISSING\" }, { \"a\": \"WARNING\", \"b\": \"CRITICAL\", \"x\": \"CRITICAL\" }, { \"a\": \"WARNING\", \"b\": \"DOWNTIME\", \"x\": \"DOWNTIME\" }, { \"a\": \"UNKNOWN\", \"b\": \"UNKNOWN\", \"x\": \"UNKNOWN\" }, { \"a\": \"UNKNOWN\", \"b\": \"MISSING\", \"x\": \"MISSING\" }, { \"a\": \"UNKNOWN\", \"b\": \"CRITICAL\", \"x\": \"CRITICAL\" }, { \"a\": \"UNKNOWN\", \"b\": \"DOWNTIME\", \"x\": \"DOWNTIME\" }, { \"a\": \"MISSING\", \"b\": \"MISSING\", \"x\": \"MISSING\" }, { \"a\": \"MISSING\", \"b\": \"CRITICAL\", \"x\": \"CRITICAL\" }, { \"a\": \"MISSING\", \"b\": \"DOWNTIME\", \"x\": \"DOWNTIME\" }, { \"a\": \"CRITICAL\", \"b\": \"CRITICAL\", \"x\": \"CRITICAL\" }, { \"a\": \"CRITICAL\", \"b\": \"DOWNTIME\", \"x\": \"CRITICAL\" }, { \"a\": \"DOWNTIME\", \"b\": \"DOWNTIME\", \"x\": \"DOWNTIME\" } ] }, { \"name\": \"OR\", \"truth_table\": [ { \"a\": \"OK\", \"b\": \"OK\", \"x\": \"OK\" }, { \"a\": \"OK\", \"b\": \"WARNING\", \"x\": \"OK\" }, { \"a\": \"OK\", \"b\": \"UNKNOWN\", \"x\": \"OK\" }, { \"a\": \"OK\", \"b\": \"MISSING\", \"x\": \"OK\" }, { \"a\": \"OK\", \"b\": \"CRITICAL\", \"x\": \"OK\" }, { \"a\": \"OK\", \"b\": \"DOWNTIME\", \"x\": \"OK\" }, { \"a\": \"WARNING\", \"b\": \"WARNING\", \"x\": \"WARNING\" }, { \"a\": \"WARNING\", \"b\": \"UNKNOWN\", \"x\": \"WARNING\" }, { \"a\": \"WARNING\", \"b\": \"MISSING\", \"x\": \"WARNING\" }, { \"a\": \"WARNING\", \"b\": \"CRITICAL\", \"x\": \"WARNING\" }, { \"a\": \"WARNING\", \"b\": \"DOWNTIME\", \"x\": \"WARNING\" }, { \"a\": \"UNKNOWN\", \"b\": \"UNKNOWN\", \"x\": \"UNKNOWN\" }, { \"a\": \"UNKNOWN\", \"b\": \"MISSING\", \"x\": \"UNKNOWN\" }, { \"a\": \"UNKNOWN\", \"b\": \"CRITICAL\", \"x\": \"CRITICAL\" }, { \"a\": \"UNKNOWN\", \"b\": \"DOWNTIME\", \"x\": \"UNKNOWN\" }, { \"a\": \"MISSING\", \"b\": \"MISSING\", \"x\": \"MISSING\" }, { \"a\": \"MISSING\", \"b\": \"CRITICAL\", \"x\": \"CRITICAL\" }, { \"a\": \"MISSING\", \"b\": \"DOWNTIME\", \"x\": \"DOWNTIME\" }, { \"a\": \"CRITICAL\", \"b\": \"CRITICAL\", \"x\": \"CRITICAL\" }, { \"a\": \"CRITICAL\", \"b\": \"DOWNTIME\", \"x\": \"CRITICAL\" }, { \"a\": \"DOWNTIME\", \"b\": \"DOWNTIME\", \"x\": \"DOWNTIME\" } ] } ] }","s":"Default operation profile","u":"/argo-monitoring/docs/profiles/operations-profile","h":"#default-operation-profile","p":250},{"i":258,"t":"The connection of the Operations profiles with the other components of ARGO They are: defined in POEM stored in ARGO Web API Used for the computations in the Analytics Engine","s":"Technical part","u":"/argo-monitoring/docs/profiles/operations-profile","h":"#technical-part","p":250},{"i":260,"t":"Status Timeline is a report of the status of the monitored item/group of items, during the monitoring time. Knowing the timeline, provides information about the condition of the monitored item , helps to spot the most problematic metrics and decide about them. It is of major significance especially knowing when the monitored item is in a CRITICAL status, or it is in OK status The calculations of the ARGO Monitoring service apply to all levels of the topology, grouping the monitored items based on the topology’s characteristics. Only items that are contained in the topology are included in the calculations, as they are defined by Topology Group, Topology Endpoint.","s":"Status Timelines","u":"/argo-monitoring/docs/reports/status_timelines","h":"#status-timelines","p":259},{"i":262,"t":"The first step of calculations of the ARGO Monitoring service is concluding results in the level of the metric checks. Example:​ The metric check applies on a monitoring item with the following topology’s characteristics: \"metric\": \"http.check\", \"hostname\": \"host1.example.com\", \"service_type\": \"Web-Site\", \"group\": \"group1\" The Metric Data records for this item could give information about the status as : timestamp status 2021-05-02T00:00:00Z OK 2021-05-02T03:00:00Z OK 2021-05-02T06:00:00Z OK 2021-05-02T09:00:00Z OK 2021-05-02T12:00:00Z WARNING 2021-05-02T15:00:00Z WARNING 2021-05-02T18:00:00Z CRITICAL 2021-05-02T21:00:00Z OK The timeline result would be as shown in picture:","s":"Metric Level - Monitoring a single check","u":"/argo-monitoring/docs/reports/status_timelines","h":"#metric-level----monitoring-a-single-check","p":259},{"i":264,"t":"The next level of the calculations is the endpoint level, producing results for a single host. A host includes multiple metric checks, so the Metric Data are grouped by the host. But not all metric checks of the host need to be included into the calculations. The ARGO Monitoring Service retrieves a Metric Profile report that defines the significant metric check. The Metric Data are filtered based on the given information and computations apply only to the metric checks defined in the Metric Profile reports. The Argo Monitoring service will combine the timelines of the metric checks and will combine the time interval and statuses into a new timeline. In order to combine the different statuses of a time interval and conclude into one status the ARGO Monitoring service retrieves an Operation Profile that defines all the possible status combinations. As Operation Profile includes a defined operation with a truth table of possible status combinations, the ARGO Monitoring service retrieves the operation that corresponds to the endpoint level from the Aggregation Profile Example:​ Here are three metric checks for the same host: \"metric\": \"http.check\", \"hostname\":\"host1.example.com, \"service_type\": \"Web-Site\", \"group\": \"group1\" ` \"metric\": \"http.download\", \"hostname\":\"host1.example.com\", \"service_type\":\"Web-Site\", \"group\": \"group1\" \"metric\": \"http.upload\", \"hostname\": \"host1.example.com\", \"service_type\": \"Web-Site\", \"group\": \"group1\" But from the metric profile report only http.download and http.upload are defined. As a result the ARGO Monitoring service will filter the Metric Data and will ignore the ones of the http.check metric check. The timelines of http.download and http.upload will combine with each other and produce the timeline of the endpoint host1.example.com, as shown in picture:","s":"Endpoint Level - Monitoring a single host","u":"/argo-monitoring/docs/reports/status_timelines","h":"#endpoint-level----monitoring-a-single-host","p":259},{"i":266,"t":"The next level of the calculations is the service level, producing results for a single service. A service runs under multiple hosts, so the Metric Data are grouped by the service. The Argo Monitoring service will combine the timelines of the hosts that run the service into a new timeline. Not all services are included into the calculations. ARGO Monitoring service filters the data to retrieve explicitly these services, as they are defined in Aggregation Profiles. In order to combine the different statuses of a time interval and conclude into one status, the ARGO Monitoring service retrieves from the Aggregation Profile the operation for each service and knowing this, retrieves the status combination of this operation from the Operation Profile. Example :​ The monitored service Web-Site operates under 3 hosts : host1.example.com, host2.example.com, host3.example.com. In order to decide that the service operates successfully it should run successfully to all hosts. ARGO Monitoring Service groups the timelines by the service Web-Site and would create status timelines for the service by combining the individual host status timelines. The way that the individual hosts’ status timelines are combined to produce the final result for the service is described in the Aggregation Profile. The Aggregation Profile defines the AND or OR way to aggregate the individual hosts’ status timelines in order to compute the final timelines. The function AND, OR and the way they are used for the computations are defined in the Operations Profile. The timeline result would be as shown in picture:","s":"Service Level -Monitoring an entire service","u":"/argo-monitoring/docs/reports/status_timelines","h":"#service-level---monitoring-an-entire-service","p":259},{"i":268,"t":"A group might contain a number of service offerings, such as a Web-Site, a mysql-db, a NextCloud etc. The services’ timelines can be combined and concluded into a status timeline for the group. A group may represent a whole project or a group of services that work together to offer an operational solution to the users. This kind of grouping could also represent data infrastructures with geographical designation, such as a specific data center etc. The way that these services are combined to produce the final result for the group is described in the Aggregation Profile. Example :​ In the previous example we described how the ARGO Monitoring Service is monitoring the service Web-Site . Let’s assume we have the mysql-db service for storing data, and the NextCloud service for storing files. A project is using these 3 services for its users. In order for the service offering to be operational, all of these 3 services should run without problems. In order to monitor them we put them in a group named by the project they belong to. ARGO Monitoring Service would create status timelines for the project by combining the individual service status timelines. The way that the individual service status timelines are combined to produce the final result for the group is described in the Aggregation Profile. The Aggregation Profile defines the AND or OR way to aggregate the individual service status timelines in order to compute the final timelines. The function AND, OR and the way they are used for the computations are defined in the Operations Profile. The timeline result would be as shown in picture:","s":"Monitoring an entire group","u":"/argo-monitoring/docs/reports/status_timelines","h":"#monitoring-an-entire-group","p":259},{"i":271,"t":"The ARGO Monitoring Service is checking the services at regular intervals. It actually runs explicit tests (checks) in order to assess the status of the service. The result of the checks decides on the state of the service. Based on that each service may have a state : OK: the check succeeds CRITICAL: the check does not succeed WARNING: the check succeeds but performs unusually MISSING: the check’s state is not recorded UNKNOWN: the check could not apply on the monitoring item and as a result the check’s state is unknown As configuration problems, troublesome services, or other service internal problems occur, the checks on the monitoring items can result in a problematic state (critical, warning or unknown state), for a time period. ARGO Monitoring service analyzes the status timelines in different levels, detects the CRITICAL, WARNING, UNKNOWN states and calculates the duration (in minutes) as well as the number of appearances of each state in the daily timelines. ARGO Monitoring service creates a report, for each of the problematic states, with the list of the monitored items which remain in the state for the longest time period. It actually analyzes the stream of collected status data (monitoring results) using its analytics engine (a big data friendly platform) and traces the problematic states almost in real time, calculating their presence and duration. It uncovers hidden patterns, correlations and other insights and informs the user.","s":"Description","u":"/argo-monitoring/docs/reports/status-critical-warning-unknown","h":"#description","p":269},{"i":273,"t":"State changes can occur due to network problems between monitoring host and monitored item for example:","s":"Examples","u":"/argo-monitoring/docs/reports/status-critical-warning-unknown","h":"#examples","p":269},{"i":275,"t":"We have a monitoring service that monitors HTTP activity in host2.example.com using the check_http probe. Due to network issues between monitoring box and host2.example.com we have a pattern that some HTTP checks are successful (OK) some are critical (CRITICAL), some are warning (WARNING) and some are unknown (UNKNOWN) as shown in picture: Result​ ARGO Monitoring Service applies calculations on the recorded status timeline and counts the appearance and duration of CRITICAL, WARNING, UNKNOWN state. The duration of the status is calculated by aggregating the interval duration of each status appearance in the timeline. In the above example, as the timeline is divided in 20 equal slots, each slot has a duration of 36 minutes. The ARGO Monitoring Service detects that : WARNING appears 2 times, with duration 72 minutes (2 X 36 minutes) CRITICAL appears 5 times, with duration 180 minutes (5 X 36 minutes) UNKNOWN appears 1 time,, with duration 36 minutes (1 X 36 minutes)","s":"Example 1: Counting CRITICAL,WARNING,UNKNOWN status daily appearance and duration","u":"/argo-monitoring/docs/reports/status-critical-warning-unknown","h":"#example-1-counting-criticalwarningunknown-status-daily-appearance-and-duration","p":269},{"i":278,"t":"ARGO Monitoring service, by generating status timelines for each level of the topology, can produce useful conclusions about the monitoring item. One very useful conclusion is to decide if the item is available for usage and if it is considered as reliable. To succeed this, availability/reliability rates need to be calculated on the timelines.","s":"Availability Reliability","u":"/argo-monitoring/docs/reports/ar","h":"#availability-reliability","p":276},{"i":280,"t":"Availability: Service Availability is the fraction of time a service was in the UP Period during the known interval in a given period. Availability rate is useful to know, as it provides information of the time the monitored item is available for use. Availability is calculated as follows: Availability = UP period / KNOWN period where KNOWN = Total period / UNKNOWN period and UP period : The duration the status of the monitored item is OK or WARNING UNKNOWN period: The duration the status of the monitored item is UNKNOWN Total period : The duration of the monitoring (usually a day)","s":"Availability","u":"/argo-monitoring/docs/reports/ar","h":"#availability","p":276},{"i":282,"t":"Reliability : Service Reliability is the ratio of the time interval a service was UP over the time interval it was supposed (scheduled) to be UP in the given period. Reliability rate is also useful to know, as it provides information about the quality of monitored item during the monitoring time, whereas it is reliable of usage or not. Reliability is calculated as follows: Reliability = UP period / (KNOWN period – Scheduled Downtime) where UP period : The duration the status of the monitored item is OK or WARNING UNKNOWN period: The duration the status of the monitored item is UNKNOWN Scheduled Downtime period: The duration the status of the monitored item is defined to be DOWNTIME Total period : The duration of the monitoring (usually a day)","s":"Reliability","u":"/argo-monitoring/docs/reports/ar","h":"#reliability","p":276},{"i":284,"t":"Let’s assume we have a timeline for 15-09-2021 with the following status/timestamp timestamp status 2021-09-15T00:00:00Z OK 2021-09-15T03:00:00Z CRITICAL 2021-09-15T12:00:00Z UNKNOWN 2021-09-15T18:00:00Z DOWNTIME 2021-09-15T22:00:00Z OK Based on these timestamps each status lasts as: OK Status: From 00:00 to 03:00 and from 22:00 till the end of the day CRITICAL Status: From 03:00 to 12:00 UNKNOWN Status: From 12:00 to 18:00 The Service owner has informed the monitoring service for a scheduled downtime from 18:00 to 22:00 Calculating the duration for each status in seconds is: Status Duration Total seconds of a day 86400 seconds /24h OK 18000 seconds /5h CRITICAL 32400 seconds /9h UNKNOWN 21600 seconds /6h DOWNTIME 14400 seconds /4h Availability = UP period / KNOWN period = UP period / (Total period – UNKNOWN period) where: UP period =OK period + WARNING period=18000 seconds UNKNOWN period: UNKNOWN period + MISSING period=21600 seconds Total period : 86400 seconds Availability = 18000/(86400-21600)=0.2777, and converting to the scale of 100 the availability is 27.777 Reliability = UP period / (KNOWN period – Scheduled Downtime) = UP period / (Total period – UNKNOWN period – ScheduledDowntime) where: UP period =OK period +WARNING period. This in numbers means 18000 seconds UNKNOWN period: UNKNOWN period+MISSING period. This in numbers means 21600 seconds ScheduledDowntime period: 14400 seconds Total period : 86400 seconds Reliability =18000/(86400-21600-14400)=0.3571, and converting to the scale of 100 the reliability is 35.771 ARGO Monitoring Service also calculates results of up period, downtime period, unknown period as: UP = UP period / Total period. This in numbers mean 18000/86400 =0.20833 UNKNOWN=UNKNOWN period +MISSING period / Total period. | this in numbers mean 21600/86400=0.25 DOWNTIME= DOWNTIME period / Total period. This in numbers mean 14400/86400=0.16667","s":"Example","u":"/argo-monitoring/docs/reports/ar","h":"#example","p":276},{"i":286,"t":"Training Material EOSC Provider Days : Presentation https://eoscfuture.eu/wp-content/uploads/2022/04/EOSC-Core.pdf recording https://www.youtube.com/watch?v=NpH9fwhFYl8&list=PLbISfqJh3TsvQ8QxYFViGxWRcHzcqpvqD&index=3","s":"Training Material","u":"/argo-monitoring/docs/training/","h":"","p":285},{"i":289,"t":"The ARGO Monitoring Service is checking the services at regular intervals. It actually runs explicit tests (checks) in order to assess the status of the service. The result of the checks decides on the state of the service. Based on that each service may have a state : OK: the check succeeds CRITICAL: the check does not succeed WARNING: the check succeeds but performs unusually MISSING: the check’s state is not recorded UNKNOWN: the check could not apply on the monitoring item and as a result the check’s state is unknown As configuration problems, troublesome services, or other service internal problems occur, the checks on the monitoring items can result in a problematic state (critical, warning or unknown state), for a time period. The monitored item is part of a multi-level hierarchy, a.k.a topology. A topology is organized as following: |--group |--service |--endpoint |--metric The results of these daily checks a.k.a Metric Data, are ingested and stored in HDFS. Each Metric Data record includes information about the timestamp and the status of the monitored metric check, also information about the topology and some extra information regarding the check . An example metric result in is shown below: { \"timestamp\": \"2021-05-02T10:53:38Z\", \"metric\": \"http.check\", \"service_type\": \"Web-Site\", \"hostname\": \"host1.example.com\", \"status\": \"OK\" \"summary\":\"\" \"description\": \"\" } ARGO Monitoring service using its analytics engine (a big data friendly platform), analyzes the stream of collected Metric Data, and is able to apply calculations on all the levels of the topology. It provides timeline results and availability/reliability results of the monitored item or a group of monitored 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use case covers the scenario to monitor a service Onboarded to EOSC via the Providers Portal. The results of this process will become available via the EOSC Exchange Monitoring WebUI (https://argo.eosc-portal.eu). In order to start monitoring an onboarded service, several requirements should be met. In addition to the basic information provided during the onboarding process, the service provider needs to provide some extra information needed by the ARGO monitoring service, described in the section below.","s":"Introduction","u":"/argo-monitoring/docs/guides/case1","h":"#introduction","p":1},{"i":5,"t":"In order to start monitoring a service, a customer should follow the steps described below.","s":"Solution","u":"/argo-monitoring/docs/guides/case1","h":"#solution","p":1},{"i":7,"t":"Before the service can be monitored, it should be onboarded into the EOSC Portal. The procedure for service on-boarding is described in detail in the EOSC portal onboarding process wiki page.","s":"Step 1 Onboard the service","u":"/argo-monitoring/docs/guides/case1","h":"#step-1-onboard-the-service","p":1},{"i":9,"t":"When the service has been successfully onboarded, the ARGO monitoring service requires some additional information. First and foremost, the monitoring service requires the probes and metrics to be associated with the service. Once the service provider decides on the probes/metrics they wish to use, the metrics should be mapped to the service they wish to monitor in EOSC-Exchange Metric Profile. After the metric profile, aggregation and thresholds profiles should also be updated.","s":"Step 2 Provide additional info for monitoring","u":"/argo-monitoring/docs/guides/case1","h":"#step-2-provide-additional-info-for-monitoring","p":1},{"i":11,"t":"Once all the information has been provided, the monitoring of the service starts and the ARGO monitoring Computation and Analytics component calculates availability and reliability of the service, and creates a report. The Service Provider can have a look at the A/R and status results from the EOSC-Exchange Monitoring UI.","s":"Step 3 Start monitoring","u":"/argo-monitoring/docs/guides/case1","h":"#step-3-start-monitoring","p":1},{"i":14,"t":"Use case 2 covers the scenario when infrastructure monitoring requirements cannot be met by EOSC-Exchange Monitoring. For example, one the following are required: defining custom topology and aggregation of monitored endpoints selecting from existing range of probes and adding custom ones managing profiles and metrics for different services","s":"Introduction","u":"/argo-monitoring/docs/guides/case2","h":"#introduction","p":12},{"i":16,"t":"In order to start monitoring an infrastructure, an Infrastructure Manager should follow the steps described below.","s":"Solution","u":"/argo-monitoring/docs/guides/case2","h":"#solution","p":12},{"i":18,"t":"The Infrastructure Manager opens a ticket on EOSC Helpdesk requesting creation of an ARGO Monitoring instance for monitoring new infrastructure. Minimum information that should be provided in ticket: Infrastructure topology Personnel responsible for managing profiles URLs for POEM and UI components","s":"Step 1 EOSC helpdesk request","u":"/argo-monitoring/docs/guides/case2","h":"#step-1-eosc-helpdesk-request","p":12},{"i":20,"t":"ARGO team will create a new tenant based on provided information and reply to the initial request that all instances are ready for use.","s":"Step 2 ARGO team initial actions","u":"/argo-monitoring/docs/guides/case2","h":"#step-2-argo-team-initial-actions","p":12},{"i":22,"t":"Minimum set of profiles that must be defined before monitoring can start: List of metrics must be selected from the metric repository Metric Profile Aggregation Profile","s":"Step 3 Define initial monitoring profiles","u":"/argo-monitoring/docs/guides/case2","h":"#step-3-define-initial-monitoring-profiles","p":12},{"i":24,"t":"Once all the information has been provided, the monitoring of the service starts and the ARGO monitoring Computation and Analytics component calculates availability and reliability of the service, and creates a report. The Infrastructure Manager can have a look at the A/R and status results from the dedicated UI. Monitoring new services is described in Use Case 1.","s":"Step 4 Start monitoring","u":"/argo-monitoring/docs/guides/case2","h":"#step-4-start-monitoring","p":12},{"i":26,"t":"All the events that compromise the produced alerts of the monitored services travel through The Argo Messaging Service. Through its supplementary tool, the argo-ams-library a client can access the source directly and inspect the events, process them and even create its own downward syncs.Although its recommended to use the library to interact with the messaging service, you can also use plain HTTP requests.","s":"Process events/alerts directly from the source(AMS)","u":"/argo-monitoring/docs/guides/AMS-consume-publish-events","h":"","p":25},{"i":28,"t":"# set up the ams client ams_host = \"{0}:{1}\".format(\"example.com\", str(443)) ams = ArgoMessagingService(endpoint=ams_host, project=\"test\", token=\"secr3t\")","s":"Initialising a connection","u":"/argo-monitoring/docs/guides/AMS-consume-publish-events","h":"#initialising-a-connection","p":25},{"i":30,"t":"Topics are collections in the messaging service, that group events logically. THe clients indicate which message goes to which topic.In order to consume events from a topic an assigned subscription to the desired topic is required. A topic can habe multiple subscriptions and the events will be replicated across all the attached subscriptions, meaning that no race data conditions may ever happen. while True: try: # consume alerts consumed_messages = ams.pull_sub(sub=\"test-sub\", return_immediately=True, verify=True) if len(consumed_messages) == 0: continue payload = consumed_messages[0][1].get_data() ack_id = consumed_messages[0][0] # if we can't parse the message body we should ack the message and move to the next try: payload = json.loads(payload) LOGGER.info(\"Examining new message {0} . . .\".format(ack_id)) # here we can implement any filtering functionality # after we ave successfully parsed the message payload if !has_desired_payload(payload): continue except Exception as e: # in case we cannot parse the payload, we should ACK the message # in order for the consumtion mechanism to bring us the next one LOGGER.error(\"Cannot parse payload for message {0}.{1}.Skipping . . .\".format(ack_id, str(e))) try: ams.ack_sub(sub=args.sub, ids=[ack_id], verify=True) continue except AmsException as e: LOGGER.error(\"Could not skip message {0}.{1}\".format(ack_id, str(e))) continue","s":"Consume Events from a Subscription","u":"/argo-monitoring/docs/guides/AMS-consume-publish-events","h":"#consume-events-from-a-subscription","p":25},{"i":32,"t":"# after we filtered messages with the appropriate payload # we can reformat our message and send it to another topic # for example to archive some specific info about the event formatted_message = format_message(payload) try: ams.publish(topic=\"test-topic\", msg=[AmsMessage(data=formatted_message)], verify=True) except AmsException as e: LOGGER.error(\"Could not publish to topic.{0}\".format(str(e))) continue # ack the original event in order for the consumption # mechanism to bring the next event try: ams.ack_sub(sub=args.sub, ids=[ack_id], verify=true) except AmsException as e: LOGGER.error(\"Could not ack original event {0}.{1}\".format(ack_id, str(e))) except AmsException as e: LOGGER.error(\"Cannot pull from subscription.{0}\".format(str(e)))","s":"Publishing Events to a Topic","u":"/argo-monitoring/docs/guides/AMS-consume-publish-events","h":"#publishing-events-to-a-topic","p":25},{"i":35,"t":"In order to be able to scale-out and take advantage of existing Monitoring systems, the EOSC Monitoring service is capable of accepting data from external sources. When referring to external sources we mean other monitoring engines that want to connect with the EOSC Monitoring Service. This use case is split in two different sections as follows: Case 3.1: Supported Monitoring Engine and Operating System (Nagios on Centos 7 or Debian 8). Case 3.2 Other Monitoring Engine and Operating System","s":"Introduction","u":"/argo-monitoring/docs/guides/case3","h":"#introduction","p":33},{"i":37,"t":"The connection of a monitoring system with EOSC is based mainly on the data that have the necessary information to create the final report. In this use case an external monitoring system replaces the internal monitoring engine and is thus reliable for the validity of the monitoring data that is published.","s":"Solution","u":"/argo-monitoring/docs/guides/case3","h":"#solution","p":33},{"i":39,"t":"The interested party opens a ticket on EOSC Helpdesk requesting to start the process to connect to the EOSC Monitoring Service. During the preparation of its request they need to prepare their systems to be able to provide the following information: The type of system used Infrastructure topology Personnel responsible for managing the necessary profiles URLs for POEM and UI components.","s":"Step 1: EOSC helpdesk","u":"/argo-monitoring/docs/guides/case3","h":"#step-1-eosc-helpdesk","p":33},{"i":41,"t":"The monitoring team creates a new tenant on the monitoring service and at the same time requests from the messaging team to create the necessary configuration on the EOSC Messaging service. As a result the team will then send to the customer the necessary instructions and access tokens to connect to the Monitoring Service.","s":"Step 2: The Monitoring team creates a new Tenant.","u":"/argo-monitoring/docs/guides/case3","h":"#step-2-the-monitoring-team-creates-a-new-tenant","p":33},{"i":43,"t":"The profiles that need to be defined Metric Profile Aggregation Profile.","s":"Step 3: The monitoring team assists the interested party to create the necessary profiles.","u":"/argo-monitoring/docs/guides/case3","h":"#step-3-the-monitoring-team-assists-the-interested-party-to-create-the-necessary-profiles","p":33},{"i":45,"t":"The customer will need to make the necessary configuration on their monitoring engine in order to start publishing metric data via the EOSC messaging service. The EOSC Monitoring Service supports two options Case 3.1: Supported monitoring Engine and Operating System (Nagios on Centos 7 or Debian 8).​ If the customers uses Nagios as its monitoring tool, EOSC Monitoring offers the argo-nagios-ams-publisher tool that is currently supported on Centos-7 and Debian-8. argo-nagios-ams-publisher is a component acting as a bridge from Nagios to ARGO Messaging system and finally to the ARGO Monitoring Engine. It is responsible for forming and dispatching messages that wrap up results from the monitoring engine. In order to use the this solution the customer will need to : a) Install argo-nagios-ams-publisher and ams-library b) Configure argo-nagios-ams-publisher c) Enable OCSP in Nagios: In /etc/nagios/nagios.cfg add this configuration obsess_over_services=1 ocsp_command=argo_service_check ocsp_timeout=15 d) Add OCSP command: should add an OCSP command in /etc/nagios/objects/commands.cfg define command { command_name argo_service_check command_line /usr/bin/ams-metric-to-queue --queue /var/spool/argo-nagios-ams-publisher/metrics/ --hostname \"$HOSTNAME$\" --status \"$SERVICESTATE$\" --summary \"$SERVICEOUTPUT$\" --message \"$LONGSERVICEOUTPUT$\" --servicestatetype \"$SERVICESTATETYPE$\" --actual_data \"$SERVICEPERFDATA$\" --service \"$_SERVICESERVICE_FLAVOUR$\" --metric \"$_SERVICEMETRIC_NAME$\" } e) All the Services to be published must have following attributes set: define service { use generic-service; Name of service template to use host_name grnet.gr service_description HTTP check_command check_http check_interval 5 _service_flavour WebPortal //the service _metric_name org.nagios.WebCheck } f) Start argo-nagios-ams-publisher by executing: service ams-publisherd start Case 3.2 Other monitoring systems​ In this solution - use case the client cannot or doesn't want to use the solution described in the case 3.1 . Then the external monitoring system should find a way to send the monitoring data (metric data) to the EOSC Monitoring . These data should follow a predefined format. The data should be stamped with their source and timestamp. Every metric should be prefixed with [source_type], following the metric naming best practises. Every metric is also labelled with the hostname and service description. These predefined messages should be sent to the EOSC Messaging service which is the service responsible to pass them to the computations engine which performs the necessary calculations to produce the reports. { \"hostname\": \"host101.example.com\", \"service\": \"eu.eosc.portal.services.url\", \"metric\": \"org.nagios.WebCheck\", \"timestamp\": \"2022-01-02T00:24:38Z\", \"status\": \"OK\", \"tags\": { \"endpoint_group\": \"GroupA\" }, \"summary\": \"200 OK\", \"actual_data\": \"time=0.085796s;;;0.000000 size=1126B;;;0\", \"monitoring_host\": \"monbox.example.com\",//name of the external monitoring box \"message\": \"a more detailed message about the monitoring result\" } Metric data comes in the form of avro files, (json files support currently in development ) and contains timestamped status information about the hostname, service and specific checks (metrics) that are being monitored. A typical item of information in the metric data contains the field listed in the snippet below. {\"namespace\": \"argo.avro\", \"type\": \"record\", \"name\": \"metric_data\", \"fields\": [ {\"name\": \"timestamp\", \"type\": \"string\"}, {\"name\": \"service\", \"type\": \"string\"}, {\"name\": \"hostname\", \"type\": \"string\"}, {\"name\": \"metric\", \"type\": \"string\"}, {\"name\": \"status\", \"type\": \"string\"}, {\"name\": \"monitoring_host\", \"type\": [\"null\", \"string\"]}, {\"name\": \"summary\", \"type\": [\"null\", \"string\"]}, {\"name\": \"message\", \"type\": [\"null\", \"string\"]}, {\"name\": \"tags\", \"type\" : [\"null\", {\"name\" : \"Tags\", \"type\" : \"map\", \"values\" : [\"null\", \"string\"] }] }] } Snippet: Accepted Avro schema The monitoring team will validate the published metric data against the supplied topology and perform a number of dry runs to ensure that there is no issue with the supplied data. As soon as the metric data is validated by the Monitoring Team these will be the main data to compute A/R and status results.","s":"Step 4: Publish Metric Data","u":"/argo-monitoring/docs/guides/case3","h":"#step-4--publish-metric-data","p":33},{"i":47,"t":"Once information has been provided, the monitoring of the service starts and the ARGO monitoring Computation and Analytics component calculates availability and reliability of the service, and creates a report. The Infrastructure Manager can have a look at the A/R and status results from the dedicated UI. Monitoring new services is described in Use Case 1.","s":"Step 5: Start Monitoring","u":"/argo-monitoring/docs/guides/case3","h":"#step-5-start-monitoring","p":33},{"i":50,"t":"This use case covers the scenarios where the topology and the results of multiple tenants need to be combined in a number of reports.","s":"Introduction","u":"/argo-monitoring/docs/guides/case4","h":"#introduction","p":48},{"i":52,"t":"In order to combine results from tenants A, B (example names), those tenants should be already monitored by ARGO Monitoring service complete with the following definitions for each tenant: Latest Data available: Each tenant should be checked that has an active stream of incoming monitoring data. Topology: Each tenant should already have a well defined source of topology that includes lists of groups, endpoints and services. Metric Profile: In simple terms, a list of all services to be checked along with all relevant metrics per service","s":"Prerequisites","u":"/argo-monitoring/docs/guides/case4","h":"#prerequisites","p":48},{"i":54,"t":"Step 1: Open a ticket to helpdesk​ In order to have results, the customer should create a ticket on the helpdesk describing: Tenants to be used in the combined report Services and metrics Aggregation profile. For each tenant that is going to take part in producing the combined results check that all of the prerequisites (mentioned in the previous section) do apply. Step 2: Creation of the Combined Tenant.​ Create a new tenant that will host the combined report. This tenant will act as a host tenant for the combined results and will rely on the data of the other tenants as input for the computations of the availability, reliability and status results. Step 3 Start monitoring​ Once all the information has been provided, the monitoring of the service starts and the ARGO monitoring Computation and Analytics component calculates availability and reliability of the services, and creates a report. The User can have a look at the A/R and status results from the combined reports from the UI.","s":"Solution","u":"/argo-monitoring/docs/guides/case4","h":"#solution","p":48},{"i":57,"t":"This use case covers the scenario according to which the customer needs to use the results of the EOSC Monitoring Service in an external service/dashboard. The customer can access the following information via an API: A/R information about the service and its service components Status information about the service and its service components The topology and grouping of the service","s":"Introduction","u":"/argo-monitoring/docs/guides/case5","h":"#introduction","p":55},{"i":60,"t":"Τhe user that wants to gain access to this type of monitoring information will get a token with read-only access to the A/R and status results. The user via the EOSC helpdesk may send his request to the monitoring team by sending: The name of the service that wants the information An email to create the user The type of information (A/R results, status results, both)","s":"Step 1: EOSC helpdesk","u":"/argo-monitoring/docs/guides/case5","h":"#step-1-eosc-helpdesk","p":55},{"i":62,"t":"The monitoring team will provide the required token and information, guidance on how to retrieve the information.","s":"Step 2: Start Ingesting the data.","u":"/argo-monitoring/docs/guides/case5","h":"#step-2-start-ingesting-the-data","p":55},{"i":64,"t":"Retrieve availability, reliability and status results of a service​ In this example we are going to present how the user can get the availability, the reliability values and the status of the AMS (Messaging Service) (endpoint: https://msg.argo.grnet.gr) of the Organisation GRNET. The Monitoring Service Monitoring Service is checking the services at regular intervals. It actually runs explicit tests (checks) in order to assess the status of the service. The result of the checks decides on the status of the service. In order to display status information it uses reports where it keeps all the necessary information. At the same time it produces useful conclusions about the monitoring item via the monitoring analytics engine. One very useful conclusion is to decide if the item is available for usage and if it is considered as reliable. To succeed this, availability/reliability values (hourly, daily, monthly) are calculated. These different types of information are also encapsulated in a report. The EOSC monitoring service monitors the Messaging Service and it performs the following checks cert_validity_check : a metric that checks the validity of the certificate used by the service ams_check: a metric that checks a list of functionalities provided by the messaging service. Based on the explanation provided above, the information about the service follows: Definition Value Description GROUP GRNET A collection of services SERVICE AMS The type of one of the services of the collection SERVICE endpoint msg.argo.grnet.gr(AMS) is defined as the combination of a hostname and Service Type. (a Service Type of AMS listening on port/s on the host msg.argo.grnet.gr is a service endpoint) Grouping used in the report SERVICEGROUPS the way the services are organized (e.g. in groups of sites, in groups of services) in the monitoring engine A/R report Default The place where the A/R results are provided. Status report Default The place where status results are provided. This is the configuration that the user will have to use to use the api calls. API call examples for A/R reports​ The api authenticates the user using the api-key within the x-api-key header. Users can specify time granularity (monthly or daily) for retrieved results and also format using the Accept header. Depending on the form of the request the user can request a group, service or service endpoint. Detailed documentation: ARGO web api v3 a/r results Example: For the AMS the corresponding api call to get the A/R of the service group GRNET is: Request for A/R results for service group GRNET: $ curl -X GET -H \"Accept: application/json\" -H \"Content-Type: application/json\" -H \"x-api-key: secret-token\" https://api.argo.grnet.gr/api/v3/results/Default/SERVICEGROUPS/GRNET?start_time=2021-08-05T00:00:00Z&end_time=2021-08-05T23:59:59Z API call examples for status reports​ The api authenticates the user using the api-key within the x-api-key header. Users can specify time granularity (monthly or daily) for retrieved results and also format using the Accept header. Depending on the form of the request the user can request a group, service or service endpoint. Detailed documentation: ARGO web api docsARGO web api v3 status results Example: For the AMS the corresponding api call to get the status of the service group GRNET is: Request for status results for service group GRNET: $ curl -X GET -H \"Accept: application/json\" -H \"Content-Type: application/json\" -H \"x-api-key: secret-token\" https://api.argo.grnet.gr/api/v3/status/Default/SERVICEGROUPS/GRNET?start_time=2021-08-05T00:00:00Z&end_time=2021-08-05T23:59:59Z","s":"Examples","u":"/argo-monitoring/docs/guides/case5","h":"#examples","p":55},{"i":67,"t":"This use case covers the scenario of getting (A/R) Availability and Reliability data from the EOSC-Monitoring Service based on the resource-id. One scenario is to get the A/R data of a service Onboarded to EOSC via the Providers Portal. Based on the Service-ID of the service from the Providers Portal you can get the A/R from the monitoring service. Before we start Availability: Service Availability is the fraction of time a service was in the UP Period during the known interval in a given period. Availability rate is useful to know, as it provides information of the time the monitored item is available for use. Reliability: Service Reliability is the ratio of the time interval a service was UP over the time interval it was supposed (scheduled) to be UP in the given period. Reliability rate is also useful to know, as it provides information about the quality of monitored item during the monitoring time, whereas it is reliable of usage or not. More information about Availability/Reliability can be found from here","s":"Introduction","u":"/argo-monitoring/docs/guides/EOSC-getARData","h":"#introduction","p":65},{"i":69,"t":"When a resource is on-boarded in the Providers Portal is automatically gets a resource-id. By the time it is on-boarded, it is also integrated with EOSC-Core services like Monitoring. The Monitoring Service based on the data defined in the Providers Portal, starts monitoring the resource and creates near real time status reports, and availability and reliability reports. This is the information a customer can get for a resource. In this guide we describe how the customer can get the A/R data for a specific resource-id. In order to start getting A/R monitoring data for a service or a list of services, a customer should follow the steps described below.","s":"Solution","u":"/argo-monitoring/docs/guides/EOSC-getARData","h":"#solution","p":65},{"i":71,"t":"The first step to start using/testing the service is to request an account via the EOSC helpdesk and from the unit monitoring service. Just create a ticket with the title Account request to fetch the status of the services. In the description of the ticket please describe the use case and the service that needs this type of monitoring data. Example Title: Account request to fetch monitoring data of a service Description: I am the service owner of EOSC Marketplace and i would like to display the monitoring data. I would like to request an account to get access to the onboarded resources. If you already have an account and you are fetching the status data you can just ask access for the A/R monitoring data.","s":"Step 1: Request an account","u":"/argo-monitoring/docs/guides/EOSC-getARData","h":"#step-1-request-an-account","p":65},{"i":73,"t":"In the response you will get the following information Name Description report_name The Name of the report that contains information about the status of the resource id. URL The URL where you may find the api account details Your account details. We usually send them via another service (dnote) for security reasons","s":"Step 2 The response","u":"/argo-monitoring/docs/guides/EOSC-getARData","h":"#step-2-the-response","p":65},{"i":75,"t":"By the time you have the data described in the previous step, you can start using the API. The API method supports the following parameters ?granularity=monthly|daily: to view monthly of daily A/R results for the requested resource-id. (start and end_time are required) start_time: a parameter to view the A/R results for this specific resource-id under a certain period of time end_time: the end_time of the period requested You may test the API call in the following links. Details of the API Call Test it online: AR Results (v3): GET /v3/results/{report_name}/id/{resource_id} Example Request 1: default daily granularity with specific resource-id​ Request​ Method​ HTTP GET Path​ /api/v3/results/Report_A/id/simple-queue?start_time=2015-06-20T12:00:00Z&end_time=2015-06-26T23:00:00Z Headers​ x-api-key: \"tenant_key_value\" Accept: \"application/json\" Response​ Code​ Status: 200 OK Body​ { \"id\": \"simple-queue\", \"endpoints\": [ { \"name\": \"host01.example\", \"service\": \"service.queue\", \"group\": \"Infra-01\", \"info\": { \"URL\": \"http://submit.queue01.example.com\" }, \"results\": [ { \"date\": \"2015-06-22\", \"availability\": \"99.99999900000002\", \"reliability\": \"99.99999900000002\", \"unknown\": \"0\", \"uptime\": \"1\", \"downtime\": \"0\" }, { \"date\": \"2015-06-23\", \"availability\": \"99.99999900000002\", \"reliability\": \"99.99999900000002\", \"unknown\": \"0\", \"uptime\": \"1\", \"downtime\": \"0\" } ] ] }","s":"Step 3 Start using the api","u":"/argo-monitoring/docs/guides/EOSC-getARData","h":"#step-3-start-using-the-api","p":65},{"i":77,"t":"The term downtime is used to refer to periods when a service is unavailable. Downtime can be caused by failure in hardware (physical equipment), (logic controlling equipment), interconnecting equipment (such as cables, facilities, routers,...), transmission (wireless, microwave, satellite), and/or capacity (system limits). Apart from a downtime due to an unplanned event there is also downtime as a planned event due to a routing maintenance. Scheduling downtime is an effective way to prevent unnecessary or unwanted notifications from being received during a period of expected service interruption.","s":"Downtimes","u":"/argo-monitoring/docs/information_feeds/downtimes","h":"","p":76},{"i":79,"t":"ARGO Monitoring Service takes into consideration the scheduled downtime to calculate the Reliability of a service or a group of services. It also affects the uptime value. At the same time the Monitoring Service doesn't send unnecessary notifications during periods of expected service interruption.","s":"How Downtimes are used in the computations","u":"/argo-monitoring/docs/information_feeds/downtimes","h":"#how-downtimes-are-used-in-the-computations","p":76},{"i":81,"t":"A scheduled downtime is a combination of the endpoint, the service type and the start and end time of the downtime . \"hostname\": \"www.grnet.gr\", \"service\": \"WEBSITE\", \"start_time\": \"2021-09-04T00:00:00Z\", \"end_time\": \"2021-09-04T23:59:00Z\" Monitoring Service has a number of connectors for well-known configuration databases and sources to get the downtimes like: DPMT (Data Project Management Tool, that also manages topology and resources information) GOCDB (Repository for storing and presenting topology and resources information) CSV files (predefined format) Json files (predefined format) xml files (predefined format)","s":"How can I define a Downtime","u":"/argo-monitoring/docs/information_feeds/downtimes","h":"#how-can-i-define-a-downtime","p":76},{"i":84,"t":"This use case covers the scenario of getting status data from the EOSC-Monitoring Service based on the resource-id. One scenario is to get the status data of a service Onboarded to EOSC via the Providers Portal. Based on the Service-ID of the service from the Providers Portal you can get the status from the monitoring service.","s":"Introduction","u":"/argo-monitoring/docs/guides/EOSC-getStatusData","h":"#introduction","p":82},{"i":86,"t":"When a resource is on-boarded in the Providers Portal is automatically gets a resource-id. By the time it is on-boarded, it is also integrated with EOSC-Core services like Monitoring. The Monitoring Service based on the data defined in the Providers Portal, starts monitoring the resource and creates near real time status reports, and availability and reliability reports. This is the information a customer can get for a resource. In this guide we describe how the customer can get the Status data for a specific resource-id. In order to start getting status monitoring data for a service or a list of services, a customer should follow the steps described below.","s":"Solution","u":"/argo-monitoring/docs/guides/EOSC-getStatusData","h":"#solution","p":82},{"i":88,"t":"The first step to start using/testing the service is to request an account via the EOSC helpdesk and from the unit monitoring service. Just create a ticket with the title Account request to fetch the status of the services. In the description of the ticket please describe the use case and the service that needs this type of monitoring data. Example Title: Account request to fetch the status of the services Description: I am the service owner of EOSC Marketplace and i would like to display the status monitoring data. I would like to request an account to get access to the onboarded resources.","s":"Step 1: Request an account","u":"/argo-monitoring/docs/guides/EOSC-getStatusData","h":"#step-1-request-an-account","p":82},{"i":90,"t":"In the response you will get the following information Name Description report_name The Name of the report that contains information about the status of the resource id. URL The URL where you may find the api account details Your account details. We usually send them via another service (dnote) for security reasons","s":"Step 2 The response","u":"/argo-monitoring/docs/guides/EOSC-getStatusData","h":"#step-2-the-response","p":82},{"i":92,"t":"By the time you have the data described in the previous step, you can start using the API. The API method supports 2 different methods a simple form: It will return the latest status result for the requested resource-id. With view=details the user can examine a detailed timeline for the current day, or specify a different period of time (using start_time and end_time) an advanced form: This form supports a number of filters which help the customer get more information about the requested resource-id. ?view=details: to view the most recent timeline of results for the requested resource-id start_time: a parameter to view the detailed timeline of results for this specific resource-id under a certain period of time end_time: the end_time of the period requested You may test the API call or get detailed information about the API method in the following links. Details of the API Call Test it online: Status Results (v3): GET /v3/status/{report_name}/id/{resource_id} Example Request 1: Latest status result for endpoint with id: simple-queue​ Request​ Method​ HTTP GET Path​ /api/v2/status/Report_A/id/simple-queue Headers​ x-api-key: \"tenant_key_value\" Accept: \"application/json\" Response​ Code​ Status: 200 OK Body​ { \"id\": \"simple-queue\", \"endpoints\": [ { \"hostname\": \"queue01.example.com\", \"service\": \"compute.queue\", \"group\": \"Infra-01\", \"info\": { \"URL\": \"http://submit.queue01.example.com\" }, \"statuses\": [ { \"timestamp\": \"2022-10-12T13:25:26Z\", \"value\": \"OK\" } ] } ] }","s":"Step 3 Start using the api","u":"/argo-monitoring/docs/guides/EOSC-getStatusData","h":"#step-3-start-using-the-api","p":82},{"i":94,"t":"One of the main sources of truth used in the Monitoring Service is the topology. It helps to discover and map relationships between services / resources. Via the topology the owner may have in-depth visibility into the infrastructure, by enabling the Monitoring Service to categorize, classify, and finally monitor the services in it. Topology includes all the necessary information about how an infrastructure is structured and organized. ARGO Monitoring Service via the connectors (components used to connect to well known Configuration Databases (DPMT, GOCDB, csv files, json) retrieves information about the infrastructure, the hierarchy of the services that will be monitored, and the service owners. Topology information includes : the monitored services the way they are organized (ex. in groups of sites, in groups of services, in projects). The Service can model different types of infrastructure architectures the service actors (owners, admins) The ways the services are organized (sites, services, projects) can be part of a bigger structure, that gathers a number of groups. Organisations offer services that can be grouped based on the location (SITES), or based on the project they are used by (PROJECT) . This can be one more level to the topology hierarchy. The topology should also provide information about this bigger group, it's type and the services it contains. The ARGO Monitoring Service allows the users to model their infrastructure by defining multiple level of groups, starting from groups of Service Endpoints and moving to higher level groups of groups. In this way it is easy to model different infrastructure architectures. We have to mention here that the levels of the topology is something that can be updated and depends on the requirements of each infrastructure. But before we start lets explain a few acronyms. Type Description Example Grouping A way to organize and group the services SITE An organization responsible for the service PROJECT When you offer services on behalf of a project SERVICE GROUPS A group of related services SITE GRNET PROJECT MyProject SERVICE GROUP Cluster of databases Service Type Each service type can have a defined sets of metrics, which are explicit tests when we check repository Endpoint the combination of hostname and Service Type, defining where the service runs a repository at www.example-repository.com uses port 4333 Service actors the people responsible for the service operation Administrator : John Smith jsmith [AT] grnet.gr Site Owner: John Doe jDoe [AT] grnet.gr Security: George Papadopoulos jpapad [AT] grnet.gr","s":"Topology","u":"/argo-monitoring/docs/information_feeds/topology","h":"","p":93},{"i":96,"t":"Via a Topology the structure of a Project, an Organization, a SITE, can be monitored. For example:","s":"Examples","u":"/argo-monitoring/docs/information_feeds/topology","h":"#examples","p":93},{"i":98,"t":"When we participate at a Project we offer a number of services. Based on this a project gathers the services to offer to a higher level and creates one more level of hierarchy. Project acts as a group, at the top level of the infrastructure definition. Project |---Service or Group of services |--Service Endpoints As an example, we may say that we have a project (MyProject) which offers an AAI Service and a Document Management Service. The information about the topology includes the group (MyProject), the services (AAI service, Document Management Service) that combine the service endpoints (aai.myproject.org, aai1.myproject.org) and (docu.myproject.org, database.myproject.org) . The following image is trying to represent the hierarchy of the topology. MyProject |---AAI service |---Document Management Service |------aai.myproject.org |------docu.myproject.org |------aai1.myproject.org |------database.myproject.org","s":"Example 1: Monitoring the services of a Project- The topology:","u":"/argo-monitoring/docs/information_feeds/topology","h":"#example-1-monitoring-the-services-of-a-project--the-topology","p":93},{"i":100,"t":"Another way to organise the topology is to add a new layer of group which is the Organisations. An Organisation usually has a number of Sites where it hosts the services used by the users. In the following example the hierarchy of this type of topology is represented. ORGANINATION |----SITE |---Service or Group of services |------Service Endpoints As an example, we may say that we have an organization, such as GRNET, which has a number of Sites like HEBLAB,IASA,EKT. Each Site gathers a number of services like SRM and WEBDAV. These services combine a number of like service-endpoints grid02.physics.uoi.gr, se01.marie.hellasgrid.gr, se01.athena.hellasgrid.gr. The following image is trying to represent the hierarchy of the topology. GRNET |---- HEBLAB |-- SRM |-- grid02.physics.uoi.gr |---- IASA |-- WEBDAV |-- se01.marie.hellasgrid. |---- EKT |-- SRM |-- se01.athena.hellasgrid.gr A visual representation of the above topology example can be represented from the image below: Monitoring Service has a number of connectors for well-known configuration databases and sources like: DPMT (Data Project Management Tool, that also manages topology and resources information) GOCDB (Repository for storing and presenting topology and resources information) CSV files (predefined format) Json files (predefined format) An example of the Json file is as follows: [ { \"Service Description (Alphanumeric and basic punctuation)\": \"My service\", \"URL\": \"https://example.com\", \"SITENAME-SERVICEGROUP\": \"MY_SITE\", \"Service Unique ID\": \"1234\", \"COUNTRY_NAME\": \"Greece\", \"notification flag?\": \"Yes\", \"CONTACT_EMAIL\": \"address@example.com\", \"Status \": \"Development\", \"SERVICE_TYPE\": \"my.service.type\" } … ] xml files (predefined format)","s":"Example 2: Monitoring the services of 1 or more Organisations - The topology:","u":"/argo-monitoring/docs/information_feeds/topology","h":"#example-2-monitoring-the-services-of-1-or-more-organisations---the-topology","p":93},{"i":102,"t":"Monitoring is the key service needed to gain insights into an infrastructure. It needs to be continuous and on-demand to quickly detect, correlate, and analyse data for a fast reaction to anomalous behaviour. The challenge of this type of monitoring is how to quickly identify and correlate problems before they affect end-users and ultimately the productivity of the organisation. Management teams can monitor the availability and reliability of the services from a high level view down to individual system metrics and monitor the conformance of multiple SLAs. The key functional requirements are: Monitoring of services Reporting availability and reliability, Visualisation of the services status, Provide dashboard interfaces, Sending real-time alerts. The dashboard design should enable easy access and visualisation of data for end-users. APIs should also be supported so as to allow third parties to gather monitoring data from the system through them. The key requirements of a monitoring system are: Support for multiple entry points (different types of systems can work together) Interoperable High availability of the different components of the system Loosely coupled: support API's in the full stack so that components are independent in their development cycles Support for Multiple Tenants, Configurations, Metrics and profiles to add flexibility and ease of customisation. For EOSC there are two monitoring services already in place: EOSC CORE and the EOSC Exchange Monitoring Service. These two services are responsible to monitor the Core services (EOSC Core Monitoring) and the services onboarded to the Marketplace (EOSC-Exchange Monitoring).","s":"Introduction","u":"/argo-monitoring/docs/guides/intro","h":"","p":101},{"i":104,"t":"The service collects status (metrics) results from one or more monitoring engine(es) and delivers daily and/or monthly availability (A) and reliability (R) results of distributed services. Both status results and A/R metrics are presented through a Web UI, with the ability for a user to drill-down from the availability of a site to individual test results that contributed to the computed figure. Figure 1. High level architecture of a Monitoring service The main components of a monitoring service are depicted in the high-level architecture diagram and described below. Monitoring Engine(s): This service component executes the service checks against the infrastructure and delivers the metric data (probe check results) to the Messaging Service. Sources of Truth: The Monitoring system should support a number of connector plugins that are able to fetch topology, Metrics and Factors from various sources such as the CMDB and the Providers Portal. It also offers a Metric and Profile Management Component which is used in order to define checks (probes) and associate them to service types. Each grouping of checks and service types forms a profile. Messaging: The monitoring system depends on a Pub/Sub Messaging Service to be in place, in order to facilitate the communication between its components. Computations & Analytics: This component of the system should include computational job definitions for ingesting data, calculating status and availability/reliability and a management service to automatically configure, deploy and execute those jobs on a distributed processing engine for stateful computations. At the same time this component analyzes the monitoring results and sends notifications based on a set of rules, to inform the users (operators, NGIs) about the status of their services. WEB API: Rest-like HTTP API service that provides access to status and availability/reliability results. It supports token based authentication and authorization with established roles. Results are provided in JSON Format. WEB UI: The Web UI is the component used to store, consolidate and \"feed\" data into the web application. The global information from the primary and heterogeneous data sources is retrieved by means of the different plugins. The collected information is structured and organized within configuration files in the service and, finally, made available to the web application without the need for any further computations. This modular architecture is conceived in order to make it easy to add new data sources and to use cached information if a primary source is unavailable. The resulting data is exposed through a RESTful web service interface.","s":"High-level Service Reference Architecture","u":"/argo-monitoring/docs/guides/intro","h":"#high-level-service-reference-architecture","p":101},{"i":106,"t":"In this section we explain the basic concepts of EOSC Monitoring. A Tenant is an isolated instance of the ARGO Monitor service that relies on common components and provides the user with its own environment. ARGO provides default UI and POEM URLs in following form: UI: https://.ui.argo.grnet.gr POEM: https://.ui.argo.grnet.gr In case custom ones are to be used, the customer is responsible for providing valid certificates and DNS aliases. ARGO Monitoring service requires following topology information in order to monitor services: the services and service endpoints they are running, the way they are organised (e.g. groups of sites, groups of services), the service actors (owners, admins, contact points). Topology can be further extended with attributes needed for individual probes (e.g. service port or URL, path to be used in case of storage services, e.g.). Supported topology sources are: EOSC Resource Registry (Providers Portal): Need to be extended to hold the following information for Monitoring. Service unique Id the service endpoints, the way they are organised (service, service components), the service actors (owners, admins, contact points). EGI Configuration Database (GOCDB) EUDAT DPMT JSON feed in the predefined format. A Metric is a chunk of code that checks specific functionality of a given service. For example a metric such as Portal-WebCheck runs on a site and checks if the HTTP connection responds correctly or not. A Probe is a piece of code that implements single or multiple tests. The probe must comply with the guidelines for monitoring probes. ARGO provides a registry of probes and metrics. New probes and metrics can be added to the registry with the support of the ARGO monitoring team. A Metric Profile is used to associate a Service with the corresponding metrics. An Aggregation Profile defines how to aggregate service statuses into higher hierarchical grouping (i.e. a service_group) status results. They are actually used to define logical rules on how to aggregate individual service status computations into groups. The results of the metrics are computed, into EOSC Monitoring Service calculations, in order to conclude into the operational state of the service, during a specific period. In order to conclude about the operational state of the service, all or part of the metrics that check the service's functionality should be taken into account. In Metrics Profiles are included, for each service, these metrics whose results are considered to the computations of the service's state. For example, a service WebSite runs on host1.example.com. The WebSite service should operate properly, be accessible and some actions should be available such as downloading or uploading material (documents, images etc). Three metrics can apply on the service to check it's functionalities: Portal-WebCheck is a metric to check if the http responds http.download is a metric to check if download functionality operates well http.upload is a metric to check if upload functionality operates well The service is assumed to operate properly if it is accessible and can support downloading material. Uploading material does not affect the state of the service (whether it is working properly or not). So in the Metrics Profile, the metrics Portal-WebCheck and http.download will be defined in order to be taken into account for concluding the status of the service. Adopted Standards REST (https://www.ics.uci.edu/~fielding/pubs/) SAML2 (https://wiki.oasis-open.org/security/FrontPage) X509 (https://www.rfc-editor.org/info/rfc5280) Apache Avro (http://avro.apache.org/) Adopted Protocols HTTPS (https://tools.ietf.org/html/rfc2818) Nagios Plugin API (https://nagios-plugins.org/doc/guidelines.html) ARGO API over REST API (http://argoeu.github.io/guides/api/)","s":"Definitions","u":"/argo-monitoring/docs/guides/intro","h":"#definitions","p":101},{"i":108,"t":"In ARGO you may combine top level A/R results (such as results referring to you data center, institution as a whole) into a higher level of abstraction such as organisations, projects, federation. In this level each member contributes to the final A/R score based on its resource capacity. This contribution is expressed as a weighted average, which is obtained by various ways such us by running benchmark on the infrastructure (ex. hep spec 06)","s":"Weights","u":"/argo-monitoring/docs/information_feeds/weights","h":"","p":107},{"i":110,"t":"ARGO Monitoring Service takes into consideration the weights to combine top level A/R results.","s":"How weights are used in the computations","u":"/argo-monitoring/docs/information_feeds/weights","h":"#how-weights-are-used-in-the-computations","p":107},{"i":112,"t":"In ARGO we actually define sets of weights applied to top level items (as we've mentioned, those are groups that represent data centers, institutions etc..). The definition includes: a name the type of top level group items that the weights are applied to the type of weights (related to computational cores, benchmark scores, TFLOPS, storage capacity, etc...) And the list of weighted items (tuples of item names along with the weight assigned to them which is usually a float number) The Json definition of a weight set is described in the example below: { \"name\": \"Example_Weightset\", \"weight_type\": \"HEPSPEC06_score\", \"group_type\": \"DATACENTERS\", \"groups\": [ { \"name\": \"DC_01_AMSTERDAM\", \"value\": 12356.4 }, { \"name\": \"DC_02_LONDON\", \"value\": 16791.5 }, { \"name\": \"DC_03_FRANKFURT\", \"value\": 18791.5 } ] } Monitoring Service has a number of connectors for setting the weights: VAPOR CSV files (predefined format) Json files (predefined format) xml files (predefined format)","s":"How can I define the weights","u":"/argo-monitoring/docs/information_feeds/weights","h":"#how-can-i-define-the-weights","p":107},{"i":116,"t":"The electronic infrastructure availability / reliability monitoring service is designed for Service Level Monitoring, for medium and large infrastructures. It monitors the status, availability and reliability of services provided by electronic infrastructures with moderate to high complexity. It supports flexible development models and modular design, allowing easy communication with external systems (such as CMDBs, Service Catalogs, etc.). The service allows the creation of multiple reports using profiles (profiles are different ways and filters of organizing and displaying the services and their service components), which are defined by the client (e.g. for managing SLAs, operations, etc.). When calculating reports (using big data management technologies) the service takes into account a number of external factors, such as specific service parameters, scheduled or unscheduled downtime, etc.","s":"Measuring and Monitoring the Availability and Reliability of Electronic Infrastructures","u":"/argo-monitoring/docs/intro","h":"#measuring-and-monitoring-the-availability-and-reliability-of-electronic-infrastructures","p":113},{"i":118,"t":"There are several things to consider when monitoring a Service. The more complex a system gets, the harder it gets to monitor. The ARGO Monitoring follows a plan for solving these kinds of challenges and provides an easy path to gain powerful insights. The ARGO Monitoring service starts monitoring the service by checking its liveness /health of the service. The main focus though is to check the availability and reliability of the services as well as groups of services by simulating the actions that the respective user would do interacting with it. For instance, in the case of a file transfer server (FTP), the service tries to transfer, save and delete a file in the server. These tests are performed at regular random intervals (e.g. every hour or 15 minutes) and their results are recorded to be included in the measuring of the availability and reliability of the service. The service supports different profiles for creating the topology and grouping of services and the algorithm for calculating the availability and reliability of services. The calculations are done in big data management and processing infrastructures (use of apache flink platform) which provide results both in real time and their correction at regular intervals. The service publishes the results of its calculations in real time, thus allowing the creation of a control panel of the status of the services (through a special interface that has been created) and provides the possibility of timely notification (alerts via email as well as SMS and slack messages) of administrators in case to detect an error. Argo monitoring provides a modern and comprehensive web-ui in which users can easily view details and results (status results and a/r scores) on items monitored. Users can navigate through the different layers of topology (groups, services, endpoints) and with various levels of granularity (monthly, daily, etc…)","s":"How it works","u":"/argo-monitoring/docs/intro","h":"#how-it-works","p":113},{"i":121,"t":"The ARGO Monitoring service provides a flexible and scalable framework for monitoring status, availability and reliability of a wide range of services provided by infrastructures with medium to high complexity. ARGO generates reports using customer defined profiles (e.g. for SLA management, operations, etc.). During the report generation, ARGO takes into account custom factors such as the importance of a specific service endpoint and scheduled or unscheduled downtimes.","s":"Overview","u":"/argo-monitoring/docs/monitoring/SP_guide","h":"#overview","p":119},{"i":123,"t":"Topology database is actually a central registry for e-Infrastructure topology.","s":"Topology","u":"/argo-monitoring/docs/monitoring/SP_guide","h":"#topology","p":119},{"i":125,"t":"Monitoring service relies on topology database to provide the following information: the monitored service(s), the service types they are running (e.g. wiki), the service endpoints of the service (e.g. endpoint), the way they are organized (e.g. in groups of sites, in groups of services), the service actors (owners, admins, contact points).","s":"Topology information","u":"/argo-monitoring/docs/monitoring/SP_guide","h":"#topology-information","p":119},{"i":127,"t":"A metric is a procedure that checks specific functionality of a given service, i.e. a single measurement. For example: generic.http.connect: checks the http if it responds; generic.certificate.validity: checks the validity of a certificate.","s":"Metrics & probes","u":"/argo-monitoring/docs/monitoring/SP_guide","h":"#metrics--probes","p":119},{"i":129,"t":"Probe is piece of code which implements single or multiple tests. All the probes intended to be used for monitoring must comply with the guidelines for monitoring probes. The owners of the service are the ones that know exactly how the service is working. The service development team with the support of the monitoring team is responsible to implement the probe that checks and at the same time mimics the actual end user behaviour without requiring special privileges or special configurations. Before you start implementing your probe, please check in the POEM library if appropriate probe is already used for monitoring services.","s":"Service probe","u":"/argo-monitoring/docs/monitoring/SP_guide","h":"#service-probe","p":119},{"i":133,"t":"This Website uses technologies such as \"cookies\" and \"pixel tags\". By browsing the webpage, the User agrees to the creation and use of cookies. If User does not wish to consent to the use of cookies, User may either disable them or discontinue browsing this webpage. For the purpose of this Policy, the following terms shall have the following meaning: \"Cookie\" or \"Cookies\": Cookies are small text or message files sent from the server of an organization and stored on your computer. Cookies do not have access to data stored on your computer's hard disk or to Cookies placed by other websites, and they may not harm or damage your system. \"Persistence cookies\" remain during multiple website visits and get stored on your hard disk. \"Session Cookies\" are temporary cookies that disappear automatically after you leave a website; \"Third Party Cookies\" are cookies used by the websites of our partners, as integrated in our own Website or used by websites we link to.","s":"1. Purpose of this cookie policy","u":"/argo-monitoring/docs/policies/CookiePolicy","h":"#1-purpose-of-this-cookie-policy","p":131},{"i":135,"t":"When you access and/or use the Website, we place one or more Cookies on your device for the purposes described herein. The following table and relevant information set out the cookies used for the Website.It also provides details of third parties setting cookies: Cookie Type Cookie Provider Cookie Name Third party cookie Persistent or session Cookie Purpose of cookie Session State WEBUI URL JSESSIONID No Session Preserve user session information","s":"2. Which cookies are placed on your device when using our Website?","u":"/argo-monitoring/docs/policies/CookiePolicy","h":"#2-which-cookies-are-placed-on-your-device-when-using-our-website","p":131},{"i":137,"t":"The duration for which a cookie will be stored on your browsing device depends on whether it is a \"persistence\" or a \"session\" cookie. Session cookies will be stored on a device until you turn off your web browser. \"Persistence cookies\" shall remain on your device after you have finished browsing until they expire or until they are deleted by you.","s":"3. How long are cookies stored on your device?","u":"/argo-monitoring/docs/policies/CookiePolicy","h":"#3-how-long-are-cookies-stored-on-your-device","p":131},{"i":139,"t":"You can usually use your web browser to enable, disable, or delete cookies. To do so, follow the instructions provided for by your web browser (usually located in the \"Help\", \"Tools\" or \"Edit\" settings). You can also set your web browser to reject all cookies or to indicate when a cookie is being sent.","s":"4. How can you disable cookies that have been placed on your device?","u":"/argo-monitoring/docs/policies/CookiePolicy","h":"#4-how-can-you-disable-cookies-that-have-been-placed-on-your-device","p":131},{"i":142,"t":"This document describes the policy to develop, package and integrate new probes into the ARGO Monitoring Engine.","s":"Overview","u":"/argo-monitoring/docs/monitoring/guidelines","h":"#overview","p":140},{"i":144,"t":"Before starting with development, check if probe already exists on Nagios Exchange. Please refer to the official Nagios documentation for probe development guidelines: Nagios Development Guidelines, Nagios Plugin API. Probes can be developed in any of these languages: Python, Perl - in case of Perl use of module Nagios::Plugin is highly recommended, C/C++, shell scripting (Bash, Bourne). ARGO Monitoring engine currently supports RHEL 7 and derivatives, so probes should use language versions and libraries provided for these distributions. List of existing probes can be found in POEM. Some other conditions: Each probe must provide the following arguments: -h help (--help) -t timeout (--timeout) -H hostname (--hostname) The following arguments can also be used if applicable: -p port (--port) -u url (--url) -v verbose (--verbose) -w warning threshold (--warning) -c critical threshold (--critical) -u username (--username) -p password (--password) Maximum output size for test/plugin output is 16KB. Above that limit the output will be truncated.","s":"Development","u":"/argo-monitoring/docs/monitoring/guidelines","h":"#development","p":140},{"i":146,"t":"Actual data is additional information about service behaviour that can be used in combination with threshold mechanisms to generate new metrics. Probes can report actual data by following the Nagios guidelines for performance data. Some other conditions: This is the expected format of actual data: 'label'=value[UOM];[warn];[crit];[min];[max]","s":"Actual Data","u":"/argo-monitoring/docs/monitoring/guidelines","h":"#actual-data","p":140},{"i":148,"t":"Probes must be provided in the form of RPM packages, where a single package may contain multiple probes. Please refer to the official EPEL documentation for packaging: EPEL Guidelines And Policies. Some considerations about naming: Package should ensure a unique namespace by using tenant, project (e.g. egi, eudat, argo) or product team (e.g. cream, htcondor) name. Package name should use \"argo-probe--\" form where is the name of the service probes are testing (e.g. argo-probe-grnet-agora). For more generic probes (not project specific) name \"argo-probe-\" is also acceptable (e.g. argo-probe-webdav). Some considerations about structure: Probes should be stored in directory: /usr/libexec/argo/probes/ (For more generic probes (not project specific) directory used by EPEL nagios probes (/usr/lib64/nagios/plugins/) is also acceptable.) If probes create temporary files, package should create directory: /var/spool/argo/probes// with ownership nagios:nagios and permissions 750. If probes package contains configuration files, they should be stored in directory: /etc/argo/probes//. Some considerations about dependencies management: Each probe is responsible for handling its dependencies. The environment needed to execute each probe must be defined by the probe.","s":"Packaging","u":"/argo-monitoring/docs/monitoring/guidelines","h":"#packaging","p":140},{"i":150,"t":"Each develops and tests its own probes in their development environments. Pre-requirements for the integration and testing of probes are: Each publishes probe(s) on an accessible: Git repository with a valid RPM spec file; Yum repository with RPM packages. Each probe provides an accessible web page with the relevant documentation. Integration of new probes starts with adding above information into POEM.","s":"Integration, Testing and Deployment","u":"/argo-monitoring/docs/monitoring/guidelines","h":"#integration-testing-and-deployment","p":140},{"i":152,"t":"Testing consists of the following steps: If the probe is provided in Git repository ARGO will clone it and attempt to build the package. ARGO will deploy the RPM package, test and validate the new probe.","s":"Testing","u":"/argo-monitoring/docs/monitoring/guidelines","h":"#testing","p":140},{"i":154,"t":"Deployment consists of the following steps: ARGO in cooperation with the Service owner defines metric templates performed by the new probe in POEM. ARGO in cooperation with the Service owner adds mappings between service flavours and metrics in POEM. ARGO in cooperation with the Service owner follows project’s procedures for deployment to production.","s":"Deployment","u":"/argo-monitoring/docs/monitoring/guidelines","h":"#deployment","p":140},{"i":156,"t":"Controller details Α public limited company (societe anonyme) under the corporate name \"National Infrastructures for Technology and Research S.A.\" and the distinctive title \"GRNET S.A.\" Controller's Contact Details dpo at grnet.gr Processor Details ARGO Support Team Processor's Contact Details argo at grnet.gr Scope of this Privacy Statement National Infrastructures for Technology and Research S.A. (hereinafter referred to as \"GRNET SA\") is bound by European Regulation 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of individuals with regard to the processing of personal data and on the free movement of such data (General Data Protection Regulation -- hereinafter referred to as \"the GDPR\") and Law 4624/2019 (Government Gazette 137/A/2019) on \"Data Protection Authority, measures for the implementation of Regulation(EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of individuals with regard to the processing of personal data and for the incorporation into national law of Directive(EU) 2016/680 of the European Parliament and of the Council of 27 April 2016 and other provisions\", as in force at any time (hereinafter referred to as \"the Law\"). This Privacy Statement details all information necessary for the processing of personal data carried out in the context of Argo Service Monitoring., as well as the policies and procedures implemented by GRNET SA for the protection of the Argo Service Monitoring users privacy. This Privacy Statement sets out the criteria as well as the terms and conditions under which GRNET SA collects, processes, uses, stores and transmits the personal data of the service users, how it ensures the confidentiality of such information, including any law and/or regulation implemented or enacted in accordance with Union and national laws on personal data protection and electronic privacy, as well as any law and/or regulation amending, replacing, issuing or consolidating any of the latter, including any other applicable Union and national laws on the processing of personal data and privacy, which may exist in accordance with applicable law. GRNET SA reserves the right to amend and update this Privacy Statement whenever necessary, whereas any such updates shall become effective five (5) days after they have been posted on the Argo Service Monitoring website. For the purposes of this Privacy Statement, the terms \"processor\", \"controller\", \"third party\", \"supervising authority\", \"personal data\", \"processing\", \"data subject\" shall have the meaning ascribed to them by applicable legislation on the protection of personal data. In addition, for the purposes of the present, the following definitions shall also apply: \"Website\" -- the website accessible via domain name web-ui-url including the entirety of the web pages thereof. \" Argo Service Monitoring Service\" - web-ui-url \"User\"- the Argo Service Monitoring online service user, whom the data refers to, whose identity is known or may be verified, namely it may be directly or indirectly determined.","s":"Privacy Policy","u":"/argo-monitoring/docs/policies/Privacy","h":"","p":155},{"i":158,"t":"i. GRNET SA-- as processor -- processes its \"users\" personal data as referred to in the following section, for the following purposes: Authentication of Argo Service Monitoring service users \"Users\" authentication is carried out through the login service Federated AAI Providing the Argo Service Monitoring service Seamless operation of the \"website\" and the Argo Service Monitoring service. Technical support to the \"coordinators\" of the Argo Service Monitoring service Easy and user friendly operation of the \"website\". Enhancement of the online experience in providing Argo Service Monitoring services Proof of Acceptance of the Terms of Use and the Privacy Statement Creation of statistical reports and charts to monitor the Argo Service Monitoring service Statistical reports and charts data do not contain any \"users\" personal data, as they result from anonymized information. ii. GRNET S.A. -- as the processor -- collects and processes personal data of \"users\" using its infrastructure for the purpose of providing the Argo Service Monitoring.","s":"A. Purpose/s for processing the data collected:","u":"/argo-monitoring/docs/policies/Privacy","h":"#a-purposes-for-processing-the-data-collected","p":155},{"i":160,"t":"i. For the Authentication of Argo Service Monitoring \"users\" The authentication of the service \"users\" is carried out through the Federated AAI service, the local login of individual components. For the sole purpose of the authentication of the service \"users\", GRNET SA collects through the aforementioned authentication procedure, and processes -- as processor- the following personal data per component: ARGO MONITORING - WEB UI Name Surname e-mail address Affiliation, in broad categories such as student, faculty, staff, alum, etc, within a particular security domain representing the organisation or sub-organisation of the affiliation Group membership and role information for the sole purpose of their authorised access to the service In addition to the personal data retrieved through the aforementioned authentication procedure, the service collects the following personal data: Name Surname e-mail address Unique identifier for the sole purpose of their authentication in the service (Persistent Id). *( Analysis of usage data (Google Analytics): Our website uses Google Analytics, a web analysis service provided by Google Inc., 1600 Amphitheatre Parkway Mountain View, CA 94043, USA (\"Google\"). Google Analytics uses cookies (text files which are stored on your computer and which enable an analysis of your use of the website). The information generated by the cookie about your use of our website will generally be transmitted to and stored by Google on servers in the United States. With the activation of IP anonymization on our website (see below), your IP address will be shortened by Google within member states of the European Union or in other contracting states of the Agreement on the European Economic Area. Only in exceptional cases will the full IP address be transmitted to a Google server in the USA and shortened there. Google will use this information on our behalf to evaluate your use of our website, to compile reports on website activity and to provide us with other services relating to website activity and internet usage. The IP address transmitted by your browser as part of Google Analytics is not combined with other data from Google. You can prevent the collection of the data generated by the cookie and related to your use of our website (including your IP address) and transmission to Google as well as the processing of this data by Google by downloading and installing the browser extension (plug-in) available under this link. For more information about privacy at Google Analytics, please see Google's privacy policy. ARGO MONITORING - POEM User Name Name Surname e-mail address Last Login Group membership and role information for the sole purpose of their authorised access to the service In addition to the personal data retrieved through the aforementioned authentication procedure, the service collects the following personal data: Distinguished Name Display Name Unique identifier for the sole purpose of their authentication in the service (Persistent Id). ARGO MONITORING - Monitoring box Unique identifier for the sole purpose of their authentication in the service (Persistent Id). In addition to the personal data retrieved through the X509 authentication procedure, the service collects the following personal data: Distinguished Name Display Name ii. For providing the Argo Service Monitoring service For the use of the Argo Service Monitoring service as well as for the efficient and lawful provision of this service, GRNET SA processes -- as processor -- the following personal data: The IP address wherefrom the \"user \"connects to the Argo Service Monitoring service The X509 certificates Service use timestamp \"Users\" e-mail address. iii. For communicating with Argo Service Monitoring service \"users\" For communicating with Argo Service Monitoring service \"users\", GRNET SA processes - as processor - the following personal data: E-mail address iv. Special categories of personal data GRNET SA does not collect, process or gain access in any way to specific data categories, as set forth in the provisions of the legislation in force (in particular data relating to racial or ethnic origin, religion, health data, etc.). In the event that a \"user\" posts any such special category data on the \"website\" or on the Argo Service Monitoring, such data will be removed as soon as the management team become aware thereof.","s":"B. Categories of personal data processed:","u":"/argo-monitoring/docs/policies/Privacy","h":"#b-categories-of-personal-data-processed","p":155},{"i":162,"t":"The processing of \"users\" personal data is necessary for the performance of the Agreement on the provision of Argo Service Monitoring services, in accordance with the needs (technical and organisational) to provide the best possible services, to serve the \"users\".","s":"C. Legal bases for processing","u":"/argo-monitoring/docs/policies/Privacy","h":"#c-legal-bases-for-processing","p":155},{"i":164,"t":"For providing Argo Service Monitoring services and the seamless operation of such services, access to the \"users\" personal data shall be granted to the following: To the Argo Service Monitoring service support team, consisting of personnel engaged in a contractual relationship of either a project or an independent service agreement with GRNET SA. hereinafter referred to as \"GRNET associates\". From SRCE, CNRS / IN2P3 hereinafter referred to as \"GRNET Project Partners\". The processing of Argo Service Monitoring service \"users\" personal data by the aforementioned, is carried out under the supervision and only at the request of GRNET SA, within the scope of the mission and the role of each associate. Such associates undertake to comply with the same privacy and personal data requirements as GRNET SA itself in accordance to the present Privacy Statement","s":"D. Access to personal data:","u":"/argo-monitoring/docs/policies/Privacy","h":"#d-access-to-personal-data","p":155},{"i":166,"t":"GRNET SA shall in no way transmit or in any way disclose the Argo Service Monitoring service \"users\" personal data to any third-party entities, private businesses, natural persons or legal entities, public authorities, agencies or other organizations, other than as expressly set out herein. The Argo Service Monitoring service \"users\" personal data may be disclosed or transmitted to governmental authorities and/or law enforcement officials, only if necessary for the abovementioned purposes, in the context of enforcement of a court decision or a provision of law or if necessary to secure the legitimate interests of GRNET SA in its capacity as processor, in compliance with the terms and conditions of applicable law.","s":"E. Recipients of collected personal data:","u":"/argo-monitoring/docs/policies/Privacy","h":"#e-recipients-of-collected-personal-data","p":155},{"i":168,"t":"The Argo Service Monitoring service users personal data shall be retained no longer than it is necessary for the needs of the service and the audits the service is subjected to. More specifically: Categories of personal data collected Time and place of retention of personal data IP address Data from website navigation through Cookies 18 months (log retention) Unique User Identifier User Name Name Surname e-mail address Last Login Distinguished Name Display Name 18 months (db) for the Unique user Identifier, User Name, Name, Surname, e-mail address, Last Login, Distinguished Name, Display Name will be deleted on user request","s":"G. Personal data retention periods","u":"/argo-monitoring/docs/policies/Privacy","h":"#g-personal-data-retention-periods","p":155},{"i":170,"t":"The processing of personal data by GRNET SA is performed in a manner that ensures both confidentiality and security thereof. All appropriate organisational and technical measures shall be taken to safeguard data against any accidental or unlawful destruction, accidental loss, alteration, prohibited dissemination or access or any other form of unfair processing. The services provided by GRNET SA are constantly evaluated to be in line with the safety requirements of international standards. GRNET's Information Security Management System (ISMS) has been certified by the accredited certification body, EUROCERT SA In particular: Access to technical log data is restricted and can only be accessed in a secure way by the Argo Service Monitoring service staff. When accessing the Argo Service Monitoring service adequate security controls are in place to keep your personal data safe in accordance with the classification of the personal data we have collected from you. We use encryption (HTTPS) to keep data private while in transit. Data sent using HTTPS is secured via Transport Layer Security protocol (TLS), which provides: Encryption---encrypting the exchanged data to keep it secure from droppers. Data integrity---data cannot be modified or corrupted during transfer, intentionally or otherwise, without being detected. Authentication---proves that your users communicate with the intended website. The implementation of the Argo Service Monitoring service ensures that no unauthorized user can log into the service. An authorised user means a service user, who has an active account with the Federated AAI service, having passed the authentication process mentioned above. We review our information collection, storage, and processing practices, including physical security measures, to prevent unauthorized access to our systems Although we follow best security practices to ensure your personal data remains secure, there is no absolute guarantee of security when using services online. While we strive to protect your personal data, you acknowledge that: There are security and privacy limitations on the internet which are beyond our control and can have a negative impact on the confidentiality, integrity and availability of the information. We cannot be held accountable for activity that results from your own neglect to safeguard the security of your login credentials and equipment which results in a loss of your personal data. If you feel this not enough, then please do not provide any personal data. Your personal data will be protected according to the Code of Conduct for Service Providers , a common standard for the research and higher education sector to protect your privacy.","s":"H. Privacy and Security of Information:","u":"/argo-monitoring/docs/policies/Privacy","h":"#h-privacy-and-security-of-information","p":155},{"i":172,"t":"For any questions or clarifications regarding the present Privacy Statement and as well as in the event of any violation related to personal data issues, \"users\" may contact the Competent Department of GRNET SA at the e-mail address mentioned hereinabove. They may also contact the Data Protection Officer (DPO) of GRNET S.A., Ms. Vera Meleti, and/or the deputy DPO, Ms. Vasiliki Konstantinopoulou at the e-mail address: dpo@grnet.gr.","s":"I. Contact:","u":"/argo-monitoring/docs/policies/Privacy","h":"#i-contact","p":155},{"i":174,"t":"In the event that any Argo Service Monitoring \"user\" request is not satisfied by the processor, the \"user\" may at any time address to/ file recourse with the Competent Supervisory Authority, namely the Data Protection Authority https://www.dpa.gr .","s":"K. Recourse/Complaint:","u":"/argo-monitoring/docs/policies/Privacy","h":"#k-recoursecomplaint","p":155},{"i":176,"t":"By registering as a user you declare that you have read, understood and will abide by the following conditions of use: You shall only use the resources/services to perform work, or transmit or store data consistent with the stated goals, policies and conditions of use as defined by the body or bodies granting you access. You shall provide appropriate acknowledgement of support or citation for your use of the resources/services provided as required by the body or bodies granting you access. You shall not use the resources/services for any purpose that is unlawful and not (attempt to) breach or circumvent any administrative or security controls. You shall respect intellectual property and confidentiality agreements. You shall protect your access credentials (e.g. private keys or passwords). You shall keep all your registered information correct and up to date. You shall immediately report any known or suspected security breach or misuse of the resources/services or access credentials to the specified incident reporting locations and to the relevant credential issuing authorities. You use the resources/services at your own risk. There is no guarantee that the resources/services will be available at any time or that their integrity or confidentiality will be preserved or that they will suit any purpose. You agree that logged information, including personal data provided by you for registration purposes, may be used for administrative, operational, accounting, monitoring and security purposes. You agree that this logged information may be disclosed to other authorised participants via secured mechanisms, only for the same purposes and only as far as necessary to provide the services. You agree that the body or bodies granting you access and resource/service providers are entitled to regulate, suspend or terminate your access without prior notice and without compensation, within their domain of authority, and you shall immediately comply with their instructions. You are liable for the consequences of your violation of any of these conditions of use, which may include but are not limited to the reporting of your violation to your home institute and, if the activities are thought to be illegal, to appropriate law enforcement agencies.","s":"Terms Of Use","u":"/argo-monitoring/docs/policies/Terms","h":"","p":175},{"i":178,"t":"This document describes the technical and organisational measures established by National Infrastructures for Research and Technology S.A. (GRNET S.A.) to meet legal and contractual requirements when processing personal data, conducting a higher level of security and protection. The definitions in Article 32 of the GDPR apply.","s":"Technical and organisational measures (TOM)","u":"/argo-monitoring/docs/policies/tom","h":"","p":177},{"i":181,"t":"Actions suitable for providing physical and environmental security of data centers, server room facilities, and working areas are adapted, while precautions against environmental threats and power disruptions are also granted. Access is limited by job role and subject to authorised approval. Technical and organisational measures that are taken into account involve security guard personnel, reception, doorbell systems, manual locking systems, and video surveillance of entrances. Entrance to the building is only possible with keycards and keys provided to authorised employees or by visitors accompanied by employees, preventing unauthorised persons from accessing secured areas. Additionally, Information on security policy, work instructions for operational safety, and access control are provided.","s":"1.a. Physical Access Control","u":"/argo-monitoring/docs/policies/tom","h":"#1a-physical-access-control","p":177},{"i":183,"t":"Operations sufficient for preventing data processing systems from being used by unauthorised persons are applied. Logical access controls are designed based on authority levels and job functions. Granting access is gained on a need-to-know and least privilege basis, where it is restricted to authorised employees responsible for the job. The use of unique IDs -identified through Active Directory- and passwords for all users is adapted, including a periodic review and revoking access when employment terminates or changes in job functions occur. Technical and organisational measures that are taken into account involve; username and password protected systems, intrusion detection facilities, use of Virtual Private Networks (VPNs) for remote access, firewalls, intrusion Detection System (IDS), user permission management, information security policy, work instruction of IT user regulations, operation security and access control.","s":"1.b. Logical Access Control","u":"/argo-monitoring/docs/policies/tom","h":"#1b-logical-access-control","p":177},{"i":185,"t":"Actions to ensure that those authorized to use a data processing system can only access the data subject to their access authorization -based on their rule- and that personal data cannot be read, copied, modified, or removed without authorization during processing, use and after storage. Technical operations incorporate physical deletion of data carriers, logging of accesses to applications, specifically when entering, changing, and deleting data, SSH encrypted access, and certified SSL encryption. At the organisational level, a minimum number of administrators is applied, management of user rights are controlled by administrators, work instruction communication security and handling of information and values are also claimed.","s":"1.c. Authorization Control","u":"/argo-monitoring/docs/policies/tom","h":"#1c-authorization-control","p":177},{"i":187,"t":"It is ensured that personal data collected for different purposes can be processed separately. Multi-tenancy of relevant applications is performed, or systems are physically or logically separated. The development sheet is separated for each product, and the services have their own line of environments. All environments, documents and other data are shared for the members of that project/product, while operational, information and data protection securities and policies are applied.","s":"1.d. Separation Control","u":"/argo-monitoring/docs/policies/tom","h":"#1d-separation-control","p":177},{"i":189,"t":"Operations for pseudonymization or anonymization of personal data are implemented to the extent necessary. Internal instruction to pseudonymize or anonymize personal data as far as possible in the event of disclosure or even after the statutory deletion period has expired. Specific internal regulations on cryptography, while operational, information and data protection securities and policies are applied.","s":"1.e. Pseudonymization","u":"/argo-monitoring/docs/policies/tom","h":"#1e-pseudonymization","p":177},{"i":192,"t":"Measures are taken into account to ensure that personal data cannot be read, copied, altered or removed by unauthorized persons during electronic transmission or while being transported or stored on data media. As technical and organizational actions are the use of Virtual Private Networks (VPNs) and firewalls, the provision via encrypted connections and techniques such as SSH, SFTP, HTTPS and secure cloudstores, the logging of accesses and retrievals, while operational, information and data protection securities and policies are also applied.","s":"2.a. Transfer Control","u":"/argo-monitoring/docs/policies/tom","h":"#2a-transfer-control","p":177},{"i":194,"t":"Operations that ensure that it is possible to check and establish retrospectively whether and by whom personal data has been entered into, modified or removed from data processing systems are implemented to the extent necessary. Input control is achieved through logging, which can take place at various levels (e.g., operating system, network, firewall, database, application). Traceability of data entry, modification and deletion through individual user names, assignment of rights to enter, change and delete data on the basis of an authorisation concept, while information security policy and work instruction of IT user regulations are engaged.","s":"2.b. Input Control","u":"/argo-monitoring/docs/policies/tom","h":"#2b-input-control","p":177},{"i":197,"t":"Actions to ensure that personal data is protected against accidental destruction or loss have been implemented to the required extent. Measures comprise fire and smoke detection systems, fire extinguishers, air-conditioning, temperature and humidity monitoring and video surveillance in server rooms, UPS system and emergency diesel generators deployment, RAID system and hard disk mirroring for data backup, information security policy and work instruction operational security.","s":"3.a. Availability Control","u":"/argo-monitoring/docs/policies/tom","h":"#3a-availability-control","p":177},{"i":199,"t":"Data backups of databases and operating system images are taken to the extent required and with the aim of preventing the loss of personal data in the event of physical or technical incident. Backups are performed for network drives and servers in productive operation, where the process is being recorded (logged). The backup concept is applied according to criticality and customer specifications. When applicable storage of backup media obtained in a safe place outside the server room. Information security policy and work instruction of IT user regulations are also engaged.","s":"3.b. Recoverability Control","u":"/argo-monitoring/docs/policies/tom","h":"#3b-recoverability-control","p":177},{"i":202,"t":"Technical and organizational measures that are taken into account are; central documentation of all data protection regulations with access for employees, security certification according to ISO 27001. Updates and reviews of the effectiveness of the TOMs are carried out periodically. Data protection checkpoints are consistently implemented, while data processing systems (IT systems) are checked regularly to the extent required and after changes to ensure that they are functioning properly. A Data Protection Officer (DPO) group is appointed and notified of physical or technical incidents, and staff is trained and obliged to confidentiality and data secrecy. Data Protection Impact Assessment (DPIA) is carried out as required, whereas processes regarding information obligations according to Art. 13 and 14 GDPR are established.","s":"4.a. Data Protection Management","u":"/argo-monitoring/docs/policies/tom","h":"#4a-data-protection-management","p":177},{"i":204,"t":"Technical and organizational actions have been established to the extent required for security breach response and data breach process. The use and the regular updating of firewall, spam filters, virus scanning, Intrusion Detection System (IDS), and Intrusion Prevention System (IPS) for customer systems on order, are served. The process for detecting and reporting security incidents and data breaches is being documented via ticket system, with regard to reporting obligation to the supervisory authority. Formalized procedure for handling security incidents, including the involvement of DPO and ISO in security incidents and data breaches is available, while operational, information, data protection and IT user regulations, securities and policies are also applied.","s":"4.b Incident Response Management","u":"/argo-monitoring/docs/policies/tom","h":"#4b-incident-response-management","p":177},{"i":206,"t":"Measures pursuant to Art 25 GDPR comply with the principles of data protection by design and by default. No more personal data is collected than is necessary for the respective purpose. Data Protection Policy (includes principles \"privacy by design and by default\").","s":"4.c Data Protection by Design and by Default","u":"/argo-monitoring/docs/policies/tom","h":"#4c-data-protection-by-design-and-by-default","p":177},{"i":208,"t":"Actions to ensure that personal data processed on behalf of the client can only be processed in accordance with the client's instructions. Technical and organizational measures have been established to the required extent. Measures involve monitoring of remote access by external parties, in the context of remote support and work instruction supplier management and supplier evaluation. Moreover, a prior review of the security measures taken by the contractor and their documentation is applied. Selection of the contractor under due diligence aspects (especially with regard to data protection and data security) is achieved. Conclusion of the necessary data processing agreement on commissioned processing or EU standard contractual clauses and a framework agreement on contractual data processing within the group of companies, where written instructions to the contractor and obligation of the contractor's employees to maintain data secrecy. Additionally, an agreement on effective control rights over the contractor and regulations on the use of further subcontractors is maintained, ensuring also the destruction of data after termination of the contract or in the case of longer collaboration, ongoing review of the contractor and its level of protection.","s":"4.d Order Control (outsourcing, subcontractors, and order processing)","u":"/argo-monitoring/docs/policies/tom","h":"#4d-order-control-outsourcing-subcontractors-and-order-processing","p":177},{"i":210,"t":"The National Infrastructures for Research and Technology S.A. (GRNET S.A.), based on Its Quality and Information Security Policies has set itself the goal of providing products and services to be delivered at the highest possible level of information security in compliance with the law. In this context GRNET S.A. has established, the roles of Information Security Officer (ISO), Data Protection Officer (DPO), Quality Officer (QO), and Legal Compliance Officer (LCO) as well as a Corporate Binding Rules (a set of internal guidelines and regulations) on information security and data protection, that are contractually binding for all employees, that defines secure information and data handling formed in secrecy and confidentiality. Employees are continuously informed and trained in the area of data protection, while third parties who may come into contact with personal data in the course of their work for GRNET S.A. are obligated to comply with data protection and data secrecy by means of a so-called NDA (Non-Disclosure Agreement) before they begin their work. Any subcontractors entrusted with further processing are only used after approval by the clients and after the conclusion of a Data Processing Agreement (DPA) in accordance with Art 28 GDPR, with which they are fully bound by all data protection obligations to which GRNET S.A. itself is subject. Current high technical security standards at GRNET S.A. are periodically reviewed and confirmed for adequacy and effectiveness in the course of ongoing internal audits and annually by Independent, External, Accredited Certification Bodies.","s":"5. Organization and Data Protection","u":"/argo-monitoring/docs/policies/tom","h":"#5-organization-and-data-protection","p":177},{"i":212,"t":"The Quality Management System (QMS) as well as the Information Security Management System (ISMS) of GRNET S.A. are both certified by Independent Accredited Certification Bodies according to ISO 9001 and ISO 27001.","s":"6. Certifications","u":"/argo-monitoring/docs/policies/tom","h":"#6-certifications","p":177},{"i":215,"t":"An aggregation profile defines how to aggregate service statuses into higher hierarchical grouping (i.e. a service_group) status results. They are actually used to define logical rules on how to aggregate individual status computations into groups.","s":"Description","u":"/argo-monitoring/docs/profiles/aggregation-profile","h":"#description","p":213},{"i":217,"t":"ARGO allows you to combine your monitored items into hierarchies of groups giving you the ability to represent real world structures of your data centers, organizations, service offerings, federations etc. The most basic level that everything else is built upon is the level of the service endpoint. A service endpoint is actually the host plus the service instance that runs on that host. For example you might have a bare metal machine (host) named db01.example.com that hosts an instance of a mysql database on port 3306. In this example the service endpoint being the combination of the hostname plus the type of the service running on the host gives: service endpoint = db01.infra.example.com(mysql)","s":"Grouping of monitored items","u":"/argo-monitoring/docs/profiles/aggregation-profile","h":"#grouping-of-monitored-items","p":213},{"i":219,"t":"You might offer mysql as a cluster which actually depends on the following service endpoints such as: db01.infra.example.com(mysql) db02.infra.example.com(mysql) db03.infra.example.com(mysql) Now you want to have a combined view for the service offering (mysql cluster) as a whole that includes a daily timeline of the status that your mysql offering and the corresponding availability / reliability score results. The mysql cluster might be deployed in an distributed way so that every host must be in a working OK condition in order to consider that the general mysql offering is OK. Or it might be deployed in a high availability fashion so even if one of the service endpoints is in working condition (OK state) the whole mysql offering is considered to be working (OK). As mentioned previously, operation profiles describe the ways that we combine items into groups based on the way they are working together (distributed/ha). Usually an operation profile declares possible states that monitored items might have and how these states are combined through combine operations/actions (namely “AND”, “OR” logical operations between items as described here: link Important: If operations profile describe the available states and the combination operations possible upon them, the aggregation profile describes where those operation take place in the hierarchy of groups we are trying to create In the previous example of mysql service offering the aggregation profile will include a declaration that endpoints of mysql service types are combined into service groups of mysql offerings through an ‘OR’ combination operation because our mysql clusters are deployed in a highly available way.","s":"Combining endpoints to service offerings","u":"/argo-monitoring/docs/profiles/aggregation-profile","h":"#combining-endpoints-to-service-offerings","p":213},{"i":221,"t":"You might have another service offering in your infrastructure that provides along with the database a cloud storage platform such as nextcloud. Similar to the database you might have the following endpoints: cloud01.infra.example.com(nextcloud) cloud02.infra.example.com(nextcloud) And you want to combine them in a single nextcloud offering that actually is distributed among them so you must combine them in an “AND” fashion (again see link) The aggregation profile in this case will include another entry that defines that the nextcloud endpoints are combined through an ‘AND’ operation to a higher level nextcloud service offering. Finally you might want to provide a high level group of your infrastructure that includes all service offerings (mysql and nextcloud). In this case you might have something like: infra.example.com (my infrastructure) | | (*offers) | |________ nextcloud service | | | | | (*has HA components) | | | |__ db01.infra.example.com | |__ db02.infra.example.com | |__ db03.infra.example.com | |_________mysql service | | (*has distributed components) | |__ cloud01.infra.example.com |__ cloud02.infra.example.com So the case might be that the nextcloud service and the mysql service must be combined in an ‘AND’ fashion in order to provide a general picture for the whole infrastructure (infra.example.com). This is also something that we define in the aggregation profile. To sum it up, the aggregation profile comes along with the operation profile and defines what kind of levels and groups our monitored items are going to be combined to and with what kind of operations (AND/OR etc…). The operations are declared and named on the operations profile and they are referenced by name in the aggregations profile. In the aggregation profile you cannot have references to operations that don’t exist in the accompanied aggregation profile.","s":"Combining service offerings to higher groups","u":"/argo-monitoring/docs/profiles/aggregation-profile","h":"#combining-service-offerings-to-higher-groups","p":213},{"i":223,"t":"The aggregation profile has the following information: A name (obviously) A reference to a metric profile attached to it (to know what kind of service types are relevant) The type of high level group representation that our service offerings are organized to (for example: DATACENTER, INFRASTRUCTURE, ORGANIZATION, SITE, SERVICEGROUP etc…) Some general types of combination operations applied globally such as: How are the individual metrics/checks are going to be combined for each endpoint How are the different high level groups are going to be combined to a final group etc… A detailed list of the high level groups we want to construct (representing as mentioned before data centers or infrastructures, or sites, or service groups etc…) and with what kind of operations each individual service type is combined to these groups The JSON format representation of an aggregation profile is provided in the following example: { \"name\": \"Infra_aggregation\", \"endpoint_group\": \"DATACENTER\", \"metric_operation\": \"AND\", \"profile_operation\": \"AND\", \"metric_profile\": { \"name\": \"my_infra_metrics\", \"id\": \"uuid-reference-here\" }, \"groups\": [ { \"name\": \"database\", \"operation\": \"OR\", \"services\": [ { \"name\": \"mysql\", \"operation\": \"OR\" } ] }, { \"name\": \"storage\", \"operation\": \"OR\", \"services\": [ { \"name\": \"nextcloud\", \"operation\": \"AND\" } ] } ] }","s":"Aggregation profile anatomy (JSON format)","u":"/argo-monitoring/docs/profiles/aggregation-profile","h":"#aggregation-profile-anatomy-json-format","p":213},{"i":226,"t":"I would like to know the percentage of metrics that appear CRITICAL status (a.k.a failure) due to network problems. Is this possible? . This was a question we had to reply to, some time ago. And now yes it is possible. In order to support this functionality, some semantics (tags) are added to metrics to categorize them. A metric could be characterized by multiple tags. By this categorization it is easy to conclude into statistics about each metric category. An infrastructure may offer various services, of which functionality is checked periodically by metrics. Each metric can be characterized / grouped via different ways. We could say that they could be grouped : by the functionality they check the reason for failure or any other characteristic","s":"Description","u":"/argo-monitoring/docs/profiles/metrics-tags","h":"#description","p":224},{"i":228,"t":"For example a metric can be a metric that has to deal with a network or with an authentication check. This means that we may characterize that the service or service component may fail due to network problems or due to authentication problems etc. At the same time, this helps the monitoring service to characterize and organize the metrics in groups and provide insights and trends for the different levels of topology (Infrastructure / Groups / Services / Service components) . This helps us easily to conclude into statistics about each metric category. It is useful to acknowledge statistics of each metric category or each metric failure reason, or any other characteristic. http.download is a metric to check if download functionality operates well http.upload is a metric to check if upload functionality operates well The two metrics can fail due to network problems CertValidity is a metric to check if the certification is valid, it is an authentication check and can fail due to invalid certificate or connection problems the metric tags profile for these metrics could be: { \"name\": \"http.download\", \"tags\": [ \"network\" ] }, { \"name\": \"http.upload\", \"tags\": [ \"network\" ] }, { \"name\": \"CertValidity\", \"tags\": [ \"auth\", \"invalid\",\"internal\" ] } During the computations the tag information about each metric check is preserved and added to the results when needed. This information can be used for further computations applied on metric tags.","s":"Example - Metric Tags","u":"/argo-monitoring/docs/profiles/metrics-tags","h":"#example---metric-tags","p":224},{"i":230,"t":"The connection of the Metric Tags profiles with the other components of ARGO They are: defined in POEM stored in ARGO Web API Used for the computations in the Analytics Engine Presented in the ARGO Web UI.","s":"Technical part","u":"/argo-monitoring/docs/profiles/metrics-tags","h":"#technical-part","p":224},{"i":233,"t":"An infrastructure may offer various services. These services need to be checked periodically in order to decide their operational state. The various functionalities of a given service are checked by metrics (a chunk of code). For example a metric such as Web-Site.Portal-WebCheck runs on a site and checks if the http connection responds or not. The results of the metrics are computed, into ARGO Monitoring Service calculations, in order to conclude into the operational state of the service, during a specific period. In order to conclude about the operational state of the service, all or part of the metrics that check the service’s functionality should be taken into account. In Metrics Profiles are included, for each service, these metrics whose results are considered to the computations of the service’s state. Example 1 - Metrics Profile for a Site service:​ A service of type Site runs on host1.example.com. The Site service should operate properly, be accessible and some actions should be available such as downloading or uploading material (documents, images etc). Three metrics can apply on the service to check it’s functionalities: Portal-WebCheck is a metric to check if the http responds http.download is a metric to check if download functionality operates well http.upload is a metric to check if upload functionality operates well The site is assumed to operate properly if it is accessible and can support downloading material. Uploading material does not affect the state of the service (whether it is working properly or not). So in the Metrics Profile, the metrics Portal-WebCheck and http.download will be defined in order to be taken into account for concluding the status of the Site. Example 2 - Metrics Profile for a Repository service:​ A service of type Repository runs on host2.example.com. The repository is considered to operate properly if it is accessible and validates the provided certificates. Two metrics can apply on the service to check it’s functionalities: Portal-WebCheck is a metric to check if the http responds CertValidity is a metric to check if the certification is valid In order to conclude the operational state of the repository both functionalities should operate properly. So in the Metrics Profile both metrics will be defined in order to be taken into account for concluding the status of the Repository. The above examples could be represented by the following Metrics Profile definition: \"services\": [ { \"service\": \"WEB-SITE\", \"metrics\": [ \"http.download\", \"Portal-WebCheck\" ] }, { \"service\": \"www.example-repository.com\", \"metrics\": [ \"Portal-WebCheck\", \"CertValidity\" ] } ]","s":"Description","u":"/argo-monitoring/docs/profiles/metrics-profile","h":"#description","p":231},{"i":236,"t":"The ARGO Monitoring Service is generating Status and A/R reports based on the metric results that it gathers from the execution of the monitoring probes. Each metric result includes a status and performance data that typically contain values related to the provided status. Currently the ARGO Monitoring Service relies solely on the statuses returned by the probes in order to generate the Status and A/R reports. Each probe has a hard-coded built-in static logic in order to compute the probe status. Although this have been proven sufficient for the purposes of infrastructure monitoring up to now, it does not give us any flexibility in providing different SLA targets customers. For example, let’s say that a probe check the average response time of the tickets in helpdesk system. With the current implementation, the acceptable response time is part of the probe configuration. If we want to have different acceptable response time for a specific customer, then we will have to create a new probe configuration and execute a new test. So in order to have different acceptable response time for each customer, we have to easily define these hardcoded values and use them as parameters. So actually we have to move the metric status computation to something more dynamic like the ARGO analytics engine. So the monitoring probes executed will return the actual data (e.g. the average response time) and then on the ARGO Analytics Engine we can have use multiple threshold profiles, which will be used in order to generate reports based on the customer needs.","s":"Description","u":"/argo-monitoring/docs/profiles/thresholds-profile","h":"#description","p":234},{"i":238,"t":"Let's take the check_ping as an example which returns the packet loss and lets assume that it has been enhanced to return average round trip time as a response. Sample output from the metric check might look like this: PING ok - Packet loss = 0%, response=0.80 | response=20ms;0;300;299;1000 This is the default result of the metric. In our example we have 2 hosts webserver01.example.com webserver02.example.com The SLA defines a different response times for each of them. In order to achieve that we have to define 2 different thresholds one for each host. The way to define the thresholds follow the following format. 'label'=value[UOM];[warn];[crit];[min];[max] where label : can contain alphanumeric characters but must always begin with a letter value : is a float or integer uom : is a string unit of measurement (accepted values: s,us,ms,B,KB,MB,TB,%,c) warning: is a range defining the warning threshold limits critical: is a range defining the critical threshold limits So based on the SLA we define the following 2 thresholds host: webserver01.example.com thresholds: response=20ms;0:200;199:300 host: webserver02.example.com thresholds: response=20ms;0:500;499:1000 BY using the threshold profiles, we managed to have different Warning and Critical limits for webserver01.example.com and webserver02.example.com and we support them for their SLA.","s":"Example","u":"/argo-monitoring/docs/profiles/thresholds-profile","h":"#example","p":234},{"i":240,"t":"The connection of the Threshold profiles with the other components of ARGO They are: defined in POEM stored in ARGO Web API part of a report and the correlation is also configured in POEM Used for the computations in the Analytics Engine Presented in the ARGO Web UI.","s":"Technical part","u":"/argo-monitoring/docs/profiles/thresholds-profile","h":"#technical-part","p":234},{"i":243,"t":"In many cases we need to provide results for top level items that are being monitored. For example if a database service is offered that relies on 2 different hosts, then we need to present a timeline with the status of the service offering itself during the day. To do that we need to combine appropriately the status timelines observed for the hosts. There many ways to combine them but the usual cases are the following: Service is deployed in a high availability fashion among hosts, so we need one of them to be ok for the general service offering to be working. In this case we say that the timelines are combined in an “OR” fashion. E.g. if host1 = OK, host2= CRITICAL the database service will be OK (see figure 1) Service is deployed in a distributed fashion among hosts, so all of them are needed to be in a working state so as the service to be considered in working state. In this case we say that the timelines are combined in an “AND” fashion. E.g. if host1 = OK, host2 = CRITICAL the service offered will be CRITICAL (see figure 2) Figure 1: Service deployed in a high availability fashion Figure 2: Service deployed in a distributed fashion","s":"Combining timelines","u":"/argo-monitoring/docs/profiles/operations-profile","h":"#combining-timelines","p":241},{"i":245,"t":"Operations profiles are used in ARGO platform to declare ways in which the status timelines can be combined. Each operation profile is actually a configuration file in json format that consists of the following parts: Α section to declare and enumerate all available statuses produced by monitoring checks. ARGO is agnostic on the names and number of statuses that can be produced by monitoring checks and they can be declared here. The default profile includes the usual array of statuses used in most monitoring systems (such as nagios) and that includes the following: OK, WARNING, CRITICAL, UNKNOWN, MISSING and DOWNTIME A section to define some default states. For example here we can define that OK state means a working state etc. A section to declare all the available ways (operations) that these statuses can be combined to produce a top result. Here we have a list of operation names mapped to truth tables that contain all the available combinations of statuses and the produced results (see table 1, table 2) Table 1 - the operations profile for AND operations is given in the following tabular: AND OK WARNING UNKNOWN MISSING CRITICAL DOWNTIME OK OK WARNING UNKNOWN MISSING CRITICAL DOWNTIME WARNING WARNING WARNING UNKNOWN MISSING CRITICAL DOWNTIME UNKNOWN UNKNOWN UNKNOWN UNKNOWN MISSING CRITICAL DOWNTIME MISSING MISSING MISSING MISSING MISSING CRITICAL DOWNTIME CRITICAL CRITICAL CRITICAL CRITICAL CRITICAL CRITICAL CRITICAL DOWNTIME DOWNTIME DOWNTIME DOWNTIME DOWNTIME CRITICAL DOWNTIME As can be seen the most prominent status in the case of the “AND” operation is the CRITICAL, while the least prominent is the “OK” status. Table 2 - the operations profile for “OR” operations is given in the following tabular: OR OK WARNING UNKNOWN MISSING CRITICAL DOWNTIME OK OK OK OK OK OK OK WARNING OK WARNING WARNING WARNING WARNING WARNING UNKNOWN OK WARNING UNKNOWN UNKNOWN CRITICAL UNKNOWN MISSING OK WARNING UNKNOWN MISSING CRITICAL DOWNTIME CRITICAL OK WARNING CRITICAL CRITICAL CRITICAL CRITICAL DOWNTIME OK WARNING UNKNOWN DOWNTIME CRITICAL DOWNTIME In the case of “OR” the most prominent status result is the “OK”.","s":"The use of operation profiles","u":"/argo-monitoring/docs/profiles/operations-profile","h":"#the-use-of-operation-profiles","p":241},{"i":247,"t":"ARGO provides a default operation profile capable for being used in most monitoring requirements that includes 6 monitoring states: OK, WARNING, CRITICAL, UNKNOWN, MISSING, DOWNTIME and two available operations on combining them: OR and AND Below is the default operation profile used in JSON Format: { \"id\": \"profile_uuid\", \"date\": \"2015-01-01\", \"name\": \"profile_name\", \"available_states\": [ \"OK\", \"WARNING\", \"UNKNOWN\", \"MISSING\", \"CRITICAL\", \"DOWNTIME\" ], \"defaults\": { \"down\": \"DOWNTIME\", \"missing\": \"MISSING\", \"unknown\": \"UNKNOWN\" }, \"operations\": [ { \"name\": \"AND\", \"truth_table\": [ { \"a\": \"OK\", \"b\": \"OK\", \"x\": \"OK\" }, { \"a\": \"OK\", \"b\": \"WARNING\", \"x\": \"WARNING\" }, { \"a\": \"OK\", \"b\": \"UNKNOWN\", \"x\": \"UNKNOWN\" }, { \"a\": \"OK\", \"b\": \"MISSING\", \"x\": \"MISSING\" }, { \"a\": \"OK\", \"b\": \"CRITICAL\", \"x\": \"CRITICAL\" }, { \"a\": \"OK\", \"b\": \"DOWNTIME\", \"x\": \"DOWNTIME\" }, { \"a\": \"WARNING\", \"b\": \"WARNING\", \"x\": \"WARNING\" }, { \"a\": \"WARNING\", \"b\": \"UNKNOWN\", \"x\": \"UNKNOWN\" }, { \"a\": \"WARNING\", \"b\": \"MISSING\", \"x\": \"MISSING\" }, { \"a\": \"WARNING\", \"b\": \"CRITICAL\", \"x\": \"CRITICAL\" }, { \"a\": \"WARNING\", \"b\": \"DOWNTIME\", \"x\": \"DOWNTIME\" }, { \"a\": \"UNKNOWN\", \"b\": \"UNKNOWN\", \"x\": \"UNKNOWN\" }, { \"a\": \"UNKNOWN\", \"b\": \"MISSING\", \"x\": \"MISSING\" }, { \"a\": \"UNKNOWN\", \"b\": \"CRITICAL\", \"x\": \"CRITICAL\" }, { \"a\": \"UNKNOWN\", \"b\": \"DOWNTIME\", \"x\": \"DOWNTIME\" }, { \"a\": \"MISSING\", \"b\": \"MISSING\", \"x\": \"MISSING\" }, { \"a\": \"MISSING\", \"b\": \"CRITICAL\", \"x\": \"CRITICAL\" }, { \"a\": \"MISSING\", \"b\": \"DOWNTIME\", \"x\": \"DOWNTIME\" }, { \"a\": \"CRITICAL\", \"b\": \"CRITICAL\", \"x\": \"CRITICAL\" }, { \"a\": \"CRITICAL\", \"b\": \"DOWNTIME\", \"x\": \"CRITICAL\" }, { \"a\": \"DOWNTIME\", \"b\": \"DOWNTIME\", \"x\": \"DOWNTIME\" } ] }, { \"name\": \"OR\", \"truth_table\": [ { \"a\": \"OK\", \"b\": \"OK\", \"x\": \"OK\" }, { \"a\": \"OK\", \"b\": \"WARNING\", \"x\": \"OK\" }, { \"a\": \"OK\", \"b\": \"UNKNOWN\", \"x\": \"OK\" }, { \"a\": \"OK\", \"b\": \"MISSING\", \"x\": \"OK\" }, { \"a\": \"OK\", \"b\": \"CRITICAL\", \"x\": \"OK\" }, { \"a\": \"OK\", \"b\": \"DOWNTIME\", \"x\": \"OK\" }, { \"a\": \"WARNING\", \"b\": \"WARNING\", \"x\": \"WARNING\" }, { \"a\": \"WARNING\", \"b\": \"UNKNOWN\", \"x\": \"WARNING\" }, { \"a\": \"WARNING\", \"b\": \"MISSING\", \"x\": \"WARNING\" }, { \"a\": \"WARNING\", \"b\": \"CRITICAL\", \"x\": \"WARNING\" }, { \"a\": \"WARNING\", \"b\": \"DOWNTIME\", \"x\": \"WARNING\" }, { \"a\": \"UNKNOWN\", \"b\": \"UNKNOWN\", \"x\": \"UNKNOWN\" }, { \"a\": \"UNKNOWN\", \"b\": \"MISSING\", \"x\": \"UNKNOWN\" }, { \"a\": \"UNKNOWN\", \"b\": \"CRITICAL\", \"x\": \"CRITICAL\" }, { \"a\": \"UNKNOWN\", \"b\": \"DOWNTIME\", \"x\": \"UNKNOWN\" }, { \"a\": \"MISSING\", \"b\": \"MISSING\", \"x\": \"MISSING\" }, { \"a\": \"MISSING\", \"b\": \"CRITICAL\", \"x\": \"CRITICAL\" }, { \"a\": \"MISSING\", \"b\": \"DOWNTIME\", \"x\": \"DOWNTIME\" }, { \"a\": \"CRITICAL\", \"b\": \"CRITICAL\", \"x\": \"CRITICAL\" }, { \"a\": \"CRITICAL\", \"b\": \"DOWNTIME\", \"x\": \"CRITICAL\" }, { \"a\": \"DOWNTIME\", \"b\": \"DOWNTIME\", \"x\": \"DOWNTIME\" } ] } ] }","s":"Default operation profile","u":"/argo-monitoring/docs/profiles/operations-profile","h":"#default-operation-profile","p":241},{"i":249,"t":"The connection of the Operations profiles with the other components of ARGO They are: defined in POEM stored in ARGO Web API Used for the computations in the Analytics Engine","s":"Technical part","u":"/argo-monitoring/docs/profiles/operations-profile","h":"#technical-part","p":241},{"i":252,"t":"ARGO Monitoring service, by generating status timelines for each level of the topology, can produce useful conclusions about the monitoring item. One very useful conclusion is to decide if the item is available for usage and if it is considered as reliable. To succeed this, availability/reliability rates need to be calculated on the timelines.","s":"Availability Reliability","u":"/argo-monitoring/docs/reports/ar","h":"#availability-reliability","p":250},{"i":254,"t":"Availability: Service Availability is the fraction of time a service was in the UP Period during the known interval in a given period. Availability rate is useful to know, as it provides information of the time the monitored item is available for use. Availability is calculated as follows: Availability = UP period / KNOWN period where KNOWN = Total period / UNKNOWN period and UP period : The duration the status of the monitored item is OK or WARNING UNKNOWN period: The duration the status of the monitored item is UNKNOWN Total period : The duration of the monitoring (usually a day)","s":"Availability","u":"/argo-monitoring/docs/reports/ar","h":"#availability","p":250},{"i":256,"t":"Reliability : Service Reliability is the ratio of the time interval a service was UP over the time interval it was supposed (scheduled) to be UP in the given period. Reliability rate is also useful to know, as it provides information about the quality of monitored item during the monitoring time, whereas it is reliable of usage or not. Reliability is calculated as follows: Reliability = UP period / (KNOWN period – Scheduled Downtime) where UP period : The duration the status of the monitored item is OK or WARNING UNKNOWN period: The duration the status of the monitored item is UNKNOWN Scheduled Downtime period: The duration the status of the monitored item is defined to be DOWNTIME Total period : The duration of the monitoring (usually a day)","s":"Reliability","u":"/argo-monitoring/docs/reports/ar","h":"#reliability","p":250},{"i":258,"t":"Let’s assume we have a timeline for 15-09-2021 with the following status/timestamp timestamp status 2021-09-15T00:00:00Z OK 2021-09-15T03:00:00Z CRITICAL 2021-09-15T12:00:00Z UNKNOWN 2021-09-15T18:00:00Z DOWNTIME 2021-09-15T22:00:00Z OK Based on these timestamps each status lasts as: OK Status: From 00:00 to 03:00 and from 22:00 till the end of the day CRITICAL Status: From 03:00 to 12:00 UNKNOWN Status: From 12:00 to 18:00 The Service owner has informed the monitoring service for a scheduled downtime from 18:00 to 22:00 Calculating the duration for each status in seconds is: Status Duration Total seconds of a day 86400 seconds /24h OK 18000 seconds /5h CRITICAL 32400 seconds /9h UNKNOWN 21600 seconds /6h DOWNTIME 14400 seconds /4h Availability = UP period / KNOWN period = UP period / (Total period – UNKNOWN period) where: UP period =OK period + WARNING period=18000 seconds UNKNOWN period: UNKNOWN period + MISSING period=21600 seconds Total period : 86400 seconds Availability = 18000/(86400-21600)=0.2777, and converting to the scale of 100 the availability is 27.777 Reliability = UP period / (KNOWN period – Scheduled Downtime) = UP period / (Total period – UNKNOWN period – ScheduledDowntime) where: UP period =OK period +WARNING period. This in numbers means 18000 seconds UNKNOWN period: UNKNOWN period+MISSING period. This in numbers means 21600 seconds ScheduledDowntime period: 14400 seconds Total period : 86400 seconds Reliability =18000/(86400-21600-14400)=0.3571, and converting to the scale of 100 the reliability is 35.771 ARGO Monitoring Service also calculates results of up period, downtime period, unknown period as: UP = UP period / Total period. This in numbers mean 18000/86400 =0.20833 UNKNOWN=UNKNOWN period +MISSING period / Total period. | this in numbers mean 21600/86400=0.25 DOWNTIME= DOWNTIME period / Total period. This in numbers mean 14400/86400=0.16667","s":"Example","u":"/argo-monitoring/docs/reports/ar","h":"#example","p":250},{"i":261,"t":"Flapping occurs when a service or host changes state too frequently, resulting in a storm of problems and recovery notifications. Flapping can be indicative of configuration problems (i.e. wrong configuration between the monitored item and the monitoring host), troublesome services, or real network problems. This causes a lot of alarms and notifications. ARGO Monitoring service analyzes the status timelines in different levels, detects the flapping patterns and creates a report with the list of the most problematic monitored items. It actually analyzes the stream of collected status data (monitoring results) in a big data friendly platform (analytics engine) and traces flapping patterns almost immediately. It uncovers hidden patterns, correlations and other insights and informs the user.","s":"Description","u":"/argo-monitoring/docs/reports/flapping-trends","h":"#description","p":259},{"i":263,"t":"Flapping can occur due to network problems between monitoring host and monitored item for example:","s":"Examples","u":"/argo-monitoring/docs/reports/flapping-trends","h":"#examples","p":259},{"i":265,"t":"ARGO Monitoring service monitors HTTP activity in host1.example.com using the check_http check. Due to network issues between the ARGO Monitoring service and host1.example.com a pattern arises that some http checks are successful (OK) and some are critical (CRITICAL) (in successive order) as shown in picture: Result​ Based on this behaviour, during the data computations, the service is flagged as a flapping service, and it is included in the list of flapping services presented in the ARGO Monitoring UI.","s":"Example 1: Flapping due to network issue","u":"/argo-monitoring/docs/reports/flapping-trends","h":"#example-1-flapping-due-to-network-issue","p":259},{"i":267,"t":"ARGO Monitoring service monitors the file upload functionality in host2.example.com (object storage) using the file upload check. Due to an internal error of the service, the check uploads a file successfully (OK), then issues a deletion request on it but the deletion takes too long. In a second attempt to re-upload the file the check receives a warning (WARNING) until the deletion of the original is completed. This results in a repeating pattern of status being OK then WARNING, then again OK etc as shown in the following picture: Result​ Based on this behaviour, during the data computations, the service is flagged as a flapping service, and it is included in the list of flapping services presented in the ARGO Monitoring UI.","s":"Example 2: Flapping due to internal problem of the service","u":"/argo-monitoring/docs/reports/flapping-trends","h":"#example-2-flapping-due-to-internal-problem-of-the-service","p":259},{"i":269,"t":"Status Timeline is a report of the status of the monitored item/group of items, during the monitoring time. Knowing the timeline, provides information about the condition of the monitored item , helps to spot the most problematic metrics and decide about them. It is of major significance especially knowing when the monitored item is in a CRITICAL status, or it is in OK status The calculations of the ARGO Monitoring service apply to all levels of the topology, grouping the monitored items based on the topology’s characteristics. Only items that are contained in the topology are included in the calculations, as they are defined by Topology Group, Topology Endpoint.","s":"Status Timelines","u":"/argo-monitoring/docs/reports/status_timelines","h":"#status-timelines","p":268},{"i":271,"t":"The first step of calculations of the ARGO Monitoring service is concluding results in the level of the metric checks. Example:​ The metric check applies on a monitoring item with the following topology’s characteristics: \"metric\": \"http.check\", \"hostname\": \"host1.example.com\", \"service_type\": \"Web-Site\", \"group\": \"group1\" The Metric Data records for this item could give information about the status as : timestamp status 2021-05-02T00:00:00Z OK 2021-05-02T03:00:00Z OK 2021-05-02T06:00:00Z OK 2021-05-02T09:00:00Z OK 2021-05-02T12:00:00Z WARNING 2021-05-02T15:00:00Z WARNING 2021-05-02T18:00:00Z CRITICAL 2021-05-02T21:00:00Z OK The timeline result would be as shown in picture:","s":"Metric Level - Monitoring a single check","u":"/argo-monitoring/docs/reports/status_timelines","h":"#metric-level----monitoring-a-single-check","p":268},{"i":273,"t":"The next level of the calculations is the endpoint level, producing results for a single host. A host includes multiple metric checks, so the Metric Data are grouped by the host. But not all metric checks of the host need to be included into the calculations. The ARGO Monitoring Service retrieves a Metric Profile report that defines the significant metric check. The Metric Data are filtered based on the given information and computations apply only to the metric checks defined in the Metric Profile reports. The Argo Monitoring service will combine the timelines of the metric checks and will combine the time interval and statuses into a new timeline. In order to combine the different statuses of a time interval and conclude into one status the ARGO Monitoring service retrieves an Operation Profile that defines all the possible status combinations. As Operation Profile includes a defined operation with a truth table of possible status combinations, the ARGO Monitoring service retrieves the operation that corresponds to the endpoint level from the Aggregation Profile Example:​ Here are three metric checks for the same host: \"metric\": \"http.check\", \"hostname\":\"host1.example.com, \"service_type\": \"Web-Site\", \"group\": \"group1\" ` \"metric\": \"http.download\", \"hostname\":\"host1.example.com\", \"service_type\":\"Web-Site\", \"group\": \"group1\" \"metric\": \"http.upload\", \"hostname\": \"host1.example.com\", \"service_type\": \"Web-Site\", \"group\": \"group1\" But from the metric profile report only http.download and http.upload are defined. As a result the ARGO Monitoring service will filter the Metric Data and will ignore the ones of the http.check metric check. The timelines of http.download and http.upload will combine with each other and produce the timeline of the endpoint host1.example.com, as shown in picture:","s":"Endpoint Level - Monitoring a single host","u":"/argo-monitoring/docs/reports/status_timelines","h":"#endpoint-level----monitoring-a-single-host","p":268},{"i":275,"t":"The next level of the calculations is the service level, producing results for a single service. A service runs under multiple hosts, so the Metric Data are grouped by the service. The Argo Monitoring service will combine the timelines of the hosts that run the service into a new timeline. Not all services are included into the calculations. ARGO Monitoring service filters the data to retrieve explicitly these services, as they are defined in Aggregation Profiles. In order to combine the different statuses of a time interval and conclude into one status, the ARGO Monitoring service retrieves from the Aggregation Profile the operation for each service and knowing this, retrieves the status combination of this operation from the Operation Profile. Example :​ The monitored service Web-Site operates under 3 hosts : host1.example.com, host2.example.com, host3.example.com. In order to decide that the service operates successfully it should run successfully to all hosts. ARGO Monitoring Service groups the timelines by the service Web-Site and would create status timelines for the service by combining the individual host status timelines. The way that the individual hosts’ status timelines are combined to produce the final result for the service is described in the Aggregation Profile. The Aggregation Profile defines the AND or OR way to aggregate the individual hosts’ status timelines in order to compute the final timelines. The function AND, OR and the way they are used for the computations are defined in the Operations Profile. The timeline result would be as shown in picture:","s":"Service Level -Monitoring an entire service","u":"/argo-monitoring/docs/reports/status_timelines","h":"#service-level---monitoring-an-entire-service","p":268},{"i":277,"t":"A group might contain a number of service offerings, such as a Web-Site, a mysql-db, a NextCloud etc. The services’ timelines can be combined and concluded into a status timeline for the group. A group may represent a whole project or a group of services that work together to offer an operational solution to the users. This kind of grouping could also represent data infrastructures with geographical designation, such as a specific data center etc. The way that these services are combined to produce the final result for the group is described in the Aggregation Profile. Example :​ In the previous example we described how the ARGO Monitoring Service is monitoring the service Web-Site . Let’s assume we have the mysql-db service for storing data, and the NextCloud service for storing files. A project is using these 3 services for its users. In order for the service offering to be operational, all of these 3 services should run without problems. In order to monitor them we put them in a group named by the project they belong to. ARGO Monitoring Service would create status timelines for the project by combining the individual service status timelines. The way that the individual service status timelines are combined to produce the final result for the group is described in the Aggregation Profile. The Aggregation Profile defines the AND or OR way to aggregate the individual service status timelines in order to compute the final timelines. The function AND, OR and the way they are used for the computations are defined in the Operations Profile. The timeline result would be as shown in picture:","s":"Monitoring an entire group","u":"/argo-monitoring/docs/reports/status_timelines","h":"#monitoring-an-entire-group","p":268},{"i":280,"t":"The ARGO Monitoring Service is checking the services at regular intervals. It actually runs explicit tests (checks) in order to assess the status of the service. The result of the checks decides on the state of the service. Based on that each service may have a state : OK: the check succeeds CRITICAL: the check does not succeed WARNING: the check succeeds but performs unusually MISSING: the check’s state is not recorded UNKNOWN: the check could not apply on the monitoring item and as a result the check’s state is unknown As configuration problems, troublesome services, or other service internal problems occur, the checks on the monitoring items can result in a problematic state (critical, warning or unknown state), for a time period. ARGO Monitoring service analyzes the status timelines in different levels, detects the CRITICAL, WARNING, UNKNOWN states and calculates the duration (in minutes) as well as the number of appearances of each state in the daily timelines. ARGO Monitoring service creates a report, for each of the problematic states, with the list of the monitored items which remain in the state for the longest time period. It actually analyzes the stream of collected status data (monitoring results) using its analytics engine (a big data friendly platform) and traces the problematic states almost in real time, calculating their presence and duration. It uncovers hidden patterns, correlations and other insights and informs the user.","s":"Description","u":"/argo-monitoring/docs/reports/status-critical-warning-unknown","h":"#description","p":278},{"i":282,"t":"State changes can occur due to network problems between monitoring host and monitored item for example:","s":"Examples","u":"/argo-monitoring/docs/reports/status-critical-warning-unknown","h":"#examples","p":278},{"i":284,"t":"We have a monitoring service that monitors HTTP activity in host2.example.com using the check_http probe. Due to network issues between monitoring box and host2.example.com we have a pattern that some HTTP checks are successful (OK) some are critical (CRITICAL), some are warning (WARNING) and some are unknown (UNKNOWN) as shown in picture: Result​ ARGO Monitoring Service applies calculations on the recorded status timeline and counts the appearance and duration of CRITICAL, WARNING, UNKNOWN state. The duration of the status is calculated by aggregating the interval duration of each status appearance in the timeline. In the above example, as the timeline is divided in 20 equal slots, each slot has a duration of 36 minutes. The ARGO Monitoring Service detects that : WARNING appears 2 times, with duration 72 minutes (2 X 36 minutes) CRITICAL appears 5 times, with duration 180 minutes (5 X 36 minutes) UNKNOWN appears 1 time,, with duration 36 minutes (1 X 36 minutes)","s":"Example 1: Counting CRITICAL,WARNING,UNKNOWN status daily appearance and duration","u":"/argo-monitoring/docs/reports/status-critical-warning-unknown","h":"#example-1-counting-criticalwarningunknown-status-daily-appearance-and-duration","p":278},{"i":287,"t":"The ARGO Monitoring Service is checking the services at regular intervals. It actually runs explicit tests (checks) in order to assess the status of the service. The result of the checks decides on the state of the service. Based on that each service may have a state : OK: the check succeeds CRITICAL: the check does not succeed WARNING: the check succeeds but performs unusually MISSING: the check’s state is not recorded UNKNOWN: the check could not apply on the monitoring item and as a result the check’s state is unknown As configuration problems, troublesome services, or other service internal problems occur, the checks on the monitoring items can result in a problematic state (critical, warning or unknown state), for a time period. The monitored item is part of a multi-level hierarchy, a.k.a topology. A topology is organized as following: |--group |--service |--endpoint |--metric The results of these daily checks a.k.a Metric Data, are ingested and stored in HDFS. Each Metric Data record includes information about the timestamp and the status of the monitored metric check, also information about the topology and some extra information regarding the check . An example metric result in is shown below: { \"timestamp\": \"2021-05-02T10:53:38Z\", \"metric\": \"http.check\", \"service_type\": \"Web-Site\", \"hostname\": \"host1.example.com\", \"status\": \"OK\" \"summary\":\"\" \"description\": \"\" } ARGO Monitoring service using its analytics engine (a big data friendly platform), analyzes the stream of collected Metric Data, and is able to apply calculations on all the levels of the topology. It provides timeline results and availability/reliability results of the monitored item or a group of monitored items.","s":"Description","u":"/argo-monitoring/docs/reports/timelines_&_ar","h":"#description","p":285},{"i":289,"t":"Training Material EOSC Provider Days : Presentation https://eoscfuture.eu/wp-content/uploads/2022/04/EOSC-Core.pdf recording https://www.youtube.com/watch?v=NpH9fwhFYl8&list=PLbISfqJh3TsvQ8QxYFViGxWRcHzcqpvqD&index=3","s":"Training 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