Update monitoring.md and remove Ganglia (#180)

Co-authored-by: Bernt Popp <bernt.popp@googlemail.com>

bih-cluster/docs/admin/getting-access.md

@@ -122,7 +122,7 @@ Additional members (cluster user names):
 
 !!! note "Notes"
     - All projects must have one owner and may have one delegate.
-    - Please note that we will enforce [kebab case]([url](https://en.wikipedia.org/wiki/Letter_case#Kebab_case)) for all project names and folders.
+    - Please note that we will enforce [kebab case](https://en.wikipedia.org/wiki/Letter_case#Kebab_case) for all project names and folders.
     - Tier 1 project storage will be supplemented with 10 TB of T1 scratch by default.
     - Users can be associated with multiple projects.
     - Project membership does not grant cluster access. A primary group affiliation is still required.

bih-cluster/docs/overview/monitoring.md

@@ -1,59 +1,7 @@
 # Monitoring
 
-We currently provide you only with Ganglia for monitoring the cluster status.
+We currently provide a Grafana dashboard for monitoring various aspects of the cluster's status:
 
-## Using Ganglia
+https://metrics.cubi.bihealth.org/public-dashboards/dc3e4d5b1ea049429abf39e412c47302
 
-Go to the following address and login with your home organization (Charite or MDC):
-
-- https://hpc-ganglia.cubi.bihealth.org
-
-
-!!! cite "Ganglia does not know about Slurm"
-    Ganglia will not show you anything about the Slurm job schedulign system.
-    If a job uses a whole node but uses no CPUs then this will be displayed as unused in Ganglia.
-    However, Slurm would not schedule another job on this node.
-
-You will be show a screen as shown below.
-This allows you to get a good idea of what is going on on the HPC.
-
-![](figures/Ganglia_Example.png)
-
-By default you will be shown the cluster usage of the last day.
-You can quickly switch to report for two or four hours as well, etc.
-
-In the first row of pictures you see the number of total CPUs (actually hardware threads), number of hosts seen as up and down by Ganglia, and cluster load/utilization.
-You will then see the overall cluster load, memory usage, CPU usage, and network utilization across the selected time period.
-
-!!! cite "Linux load is not intuitive"
-    Note that the technical details behind Linux **load** is not very interactive.
-    It is incorporating much more than just the CPU usage.
-    You can find a quite comprehensive [treatement of Linux Load here](https://www.brendangregg.com/blog/2017-08-08/linux-load-averages.html).
-
-We are using a fast shared storage system and almost no local storage (except in `/tmp`).
-Also, almost no jobs use MPI or other heavy network communication.
-Thus, the network utilization is a good measure of the I/O on the cluster.
-
-Below, you can drill down into various metrics and visualize them historically.
-Just try it out and find your way around, you cannot break anything.
-Sadly, there is no good documentation of Ganglia online.
-
-## Aggregate GPU Utilization Visualization
-
-Ganglia allows you to obtain metrics in several interesting and useful ways.
-If you click on "Aggregate Graphs" then you could enter the following values to get an overview of the live GPU utilization.
-
-- Title: `Aggreate GPU Utilization`
-- Host Regular expression: `hpc-gpu-.*`
-- Metric Regular Expressions: `gpu._util`
-- Graph Type: `Stacked`
-- Legend Options: `Hide legend`
-
-Then click `Create Graph`.
-
-![](figures/Ganglia_Aggregate_GPUs.png)
-
-If a GPU is fully used, it will contribute 100 points on the vertical axis.
-See above for an example, and here is a direct link:
-
-- [Aggregate GPU Utilization](https://hpc-ganglia.cubi.bihealth.org/ganglia/graph_all_periods.php?title=Aggregate+GPU+Utilization&cs=&ce=&vl=&x=&n=&hreg%5B%5D=hpc-gpu-.*&mreg%5B%5D=gpu._util&gtype=stack&glegend=hide&aggregate=1)
+![](figures/metrics_dashboard.png)