From 6a7e04e70c9b55176ac4321f0063b71068f1a163 Mon Sep 17 00:00:00 2001 From: Tobias Peslalz Date: Tue, 23 Jul 2024 18:16:18 +0200 Subject: [PATCH] :sparkles: (analysis) adjust grid + generate container replica graph --- .../10-12/output/plt_container_replicas.png | Bin 0 -> 49887 bytes .../10-12/output/requests_by_stage.png | Bin 181727 -> 184080 bytes .../10-12/output/requests_time_by_stage.png | Bin 74350 -> 76678 bytes .../14-16/output/plt_container_replicas.png | Bin 0 -> 49823 bytes .../14-16/output/requests_by_stage.png | Bin 211830 -> 215652 bytes .../14-16/output/requests_time_by_stage.png | Bin 83366 -> 86760 bytes .../16-18/output/plt_container_replicas.png | Bin 0 -> 45502 bytes .../16-18/output/requests_by_stage.png | Bin 207868 -> 211598 bytes .../16-18/output/requests_time_by_stage.png | Bin 79636 -> 82161 bytes loadtesting/notebooks/locust.ipynb | 58 +++++++++++++++++- 10 files changed, 56 insertions(+), 2 deletions(-) create mode 100644 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zF3UT9{C5GrL!GtRvQd1yz=jRPd>_M~fTY0zo%>zOJr(t>VlNmXAjz_1`@fCvY~ z=K#N`yuT*v2p@sE3K^vA0!kj1#IgRl4pUOdHb$JWk8&~Tu>H&z`|>FGM3FhJ-TV^- z?R);>g#|!dsCGjNC1hk?BRUAGb^tBOf|VG^HGF1MHbn`5Qsw=1`JQNj$6Y!4VrVRw z%5Ly+!KTW=pB}Jwjtf~O7W=aTb(f`3B6&(>SXj=uFk@IIGH$;oe-Os*j@bv!x(Bsab diff --git a/loadtesting/notebooks/locust.ipynb b/loadtesting/notebooks/locust.ipynb index 46a7c12..fcf0836 100644 --- a/loadtesting/notebooks/locust.ipynb +++ b/loadtesting/notebooks/locust.ipynb @@ -10,7 +10,7 @@ "import pytz\n", "import plotly.graph_objects as go\n", "import os\n", - "from matplotlib.ticker import ScalarFormatter, LogLocator" + "import matplotlib.dates as mdates" ], "id": "f546290dcd056f13", "outputs": [], @@ -21,7 +21,7 @@ "id": "3d6de811535875d3", "metadata": {}, "source": [ - "basedir = \"../data/baseapp/2024-07-15/16-18/\"\n", + "basedir = \"../data/baseapp/2024-07-15/10-12/\"\n", "outputdir = basedir+\"output/\"\n", "os.makedirs(outputdir, exist_ok=True)\n", "locust_data_history_file = basedir + \"data_stats_history.csv\"\n", @@ -153,6 +153,8 @@ "ax1.tick_params(axis='y')\n", "ax1.legend(loc='upper left')\n", "ax1.grid(True)\n", + "ax1.xaxis.set_major_locator(mdates.MinuteLocator(interval=5))\n", + "ax1.xaxis.set_major_formatter(mdates.DateFormatter('%H:%M'))\n", "\n", "# Secondary Y-Axis\n", "ax2 = ax1.twinx()\n", @@ -182,6 +184,8 @@ "ax1.tick_params(axis='y')\n", "ax1.legend(loc='upper left')\n", "ax1.grid(True)\n", + "ax1.xaxis.set_major_locator(mdates.MinuteLocator(interval=5))\n", + "ax1.xaxis.set_major_formatter(mdates.DateFormatter('%H:%M'))\n", "\n", "# Secondary Y-Axis\n", "ax2 = ax1.twinx()\n", @@ -250,6 +254,56 @@ "outputs": [], "execution_count": null }, + { + "metadata": {}, + "cell_type": "code", + "source": [ + "# Load data from CSV\n", + "containers_data_file = \"../data/baseapp/2024-07-15/containers.csv\"\n", + "containers_df = pd.read_csv(containers_data_file)\n", + "\n", + "# Parse the time column and set it as the index\n", + "containers_df['Time'] = pd.to_datetime(containers_df['Time'])\n", + "containers_df.set_index('Time', inplace=True)\n", + "\n", + "# Format column names to display only container names\n", + "containers_df.columns = [col.split('=')[1].strip(' \"{}') for col in containers_df.columns]\n", + "\n", + "def plot_data(start_time, end_time):\n", + " # Filter data within the specified time range\n", + " mask = (containers_df.index >= start_time) & (containers_df.index <= end_time)\n", + " filtered_data = containers_df.loc[mask]\n", + " \n", + " # Plotting\n", + " plt.figure(figsize=(12, 8))\n", + " \n", + " for column in filtered_data.columns:\n", + " if column.endswith(\"service\") or column == \"gateway\":\n", + " plt.plot(filtered_data.index, filtered_data[column], label=column, linewidth=2.0)\n", + " else:\n", + " plt.plot(filtered_data.index, filtered_data[column], label='_nolegend_', linestyle='--') \n", + " \n", + " plt.xlabel('Time')\n", + " plt.ylabel('Value')\n", + " plt.title('Container Replicas Over Time')\n", + "\n", + " # Add legend for high variability columns only\n", + " plt.legend(loc='best', bbox_to_anchor=(1.05, 1), borderaxespad=0.)\n", + " \n", + " plt.grid(True)\n", + " xticks = pd.date_range(start=start_time, end=end_time, freq='5min') \n", + " plt.xticks(ticks=xticks, labels=[tick.strftime(\"%H:%M\") for tick in xticks], rotation=45)\n", + " plt.tight_layout()\n", + " plt.savefig(outputdir+'plt_container_replicas.png', bbox_inches='tight')\n", + " plt.show()\n", + "\n", + "# Plot data within the specified time range\n", + "plot_data(start_time, end_time)" + ], + "id": "f072d2575bf7a131", + "outputs": [], + "execution_count": null + }, { "cell_type": "code", "id": "11e7a30b897c45e7",