{
"metadata": {
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.1-final"
},
"orig_nbformat": 2,
"kernelspec": {
"name": "Python 3.8.1 64-bit",
"display_name": "Python 3.8.1 64-bit",
"metadata": {
"interpreter": {
"hash": "c7a650d791d0a1d035b66682f8967f04fed3045153a1ba3c3bfeefd2541b18a6"
}
}
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},
"nbformat": 4,
"nbformat_minor": 2,
"cells": [
{
"source": [
"# Correlation Heatmap"
],
"cell_type": "markdown",
"metadata": {}
},
{
"source": [
""
],
"cell_type": "markdown",
"metadata": {}
},
{
"source": [
"In this notebook we will use the [netdata-pandas](https://github.com/netdata/netdata-pandas) Python package to pull some data from some demo Netdata servers and make some pretty looking correlation heatmaps, because we all love a good heatmap don't we. \n",
"\n",
"**Note**: you can click the \"Open in Colab\" button above to open this notebook in [Google Colab](https://colab.research.google.com/notebooks/intro.ipynb#recent=true) where you can just get going with it without having to set up python enviornments or any messy stuff like that."
],
"cell_type": "markdown",
"metadata": {}
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"# if you need to, uncomment below to install netdata-pandas and seaborn packages\n",
"#!pip install seaborn==0.11.0 netdata-pandas==0.0.27"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"import seaborn as sns\n",
"import matplotlib.pyplot as plt\n",
"from netdata_pandas.data import get_data"
]
},
{
"source": [
"Lets pull the data from three demo nodes for a subset of charts for the last 15 minutes."
],
"cell_type": "markdown",
"metadata": {}
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"# inputs\n",
"hosts = ['london.my-netdata.io', 'cdn77.my-netdata.io', 'octopuscs.my-netdata.io']\n",
"charts = ['system.cpu', 'system.load', 'system.io', 'system.ram', 'system.net', 'system.ip', 'system.processes', 'system.intr', 'system.softnet_stat']\n",
"before = 0\n",
"after = -60*15"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"(2700, 30)\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
" system.cpu|guest system.cpu|guest_nice \\\n",
"host time_idx \n",
"cdn77.my-netdata.io 1603460665 0.0 0.0 \n",
" 1603460666 0.0 0.0 \n",
" 1603460667 0.0 0.0 \n",
" 1603460668 0.0 0.0 \n",
" 1603460669 0.0 0.0 \n",
"\n",
" system.cpu|iowait system.cpu|irq \\\n",
"host time_idx \n",
"cdn77.my-netdata.io 1603460665 32.82828 0.0 \n",
" 1603460666 0.00000 0.0 \n",
" 1603460667 0.00000 0.0 \n",
" 1603460668 0.00000 0.0 \n",
" 1603460669 0.00000 0.0 \n",
"\n",
" system.cpu|nice system.cpu|softirq \\\n",
"host time_idx \n",
"cdn77.my-netdata.io 1603460665 0.0 0.0 \n",
" 1603460666 0.0 0.0 \n",
" 1603460667 0.0 0.0 \n",
" 1603460668 0.0 0.0 \n",
" 1603460669 0.0 0.0 \n",
"\n",
" system.cpu|steal system.cpu|system \\\n",
"host time_idx \n",
"cdn77.my-netdata.io 1603460665 0.0 2.020202 \n",
" 1603460666 0.0 1.507538 \n",
" 1603460667 0.0 1.515151 \n",
" 1603460668 0.0 1.015228 \n",
" 1603460669 0.0 2.000000 \n",
"\n",
" system.cpu|user system.intr|interrupts ... \\\n",
"host time_idx ... \n",
"cdn77.my-netdata.io 1603460665 0.505050 339.1384 ... \n",
" 1603460666 2.010050 366.6814 ... \n",
" 1603460667 0.505050 334.6279 ... \n",
" 1603460668 0.507614 307.5347 ... \n",
" 1603460669 1.000000 324.9979 ... \n",
"\n",
" system.processes|running system.ram|buffers \\\n",
"host time_idx \n",
"cdn77.my-netdata.io 1603460665 2.0 244.9961 \n",
" 1603460666 4.0 244.9961 \n",
" 1603460667 1.0 244.9961 \n",
" 1603460668 1.0 244.9961 \n",
" 1603460669 4.0 244.9961 \n",
"\n",
" system.ram|cached system.ram|free \\\n",
"host time_idx \n",
"cdn77.my-netdata.io 1603460665 2650.066 392.9688 \n",
" 1603460666 2650.066 389.1836 \n",
" 1603460667 2650.070 389.2617 \n",
" 1603460668 2650.070 389.2305 \n",
" 1603460669 2650.066 388.8750 \n",
"\n",
" system.ram|used system.softnet_stat|dropped \\\n",
"host time_idx \n",
"cdn77.my-netdata.io 1603460665 677.4180 0.0 \n",
" 1603460666 681.2031 0.0 \n",
" 1603460667 681.1211 0.0 \n",
" 1603460668 681.1523 0.0 \n",
" 1603460669 681.5117 0.0 \n",
"\n",
" system.softnet_stat|flow_limit_count \\\n",
"host time_idx \n",
"cdn77.my-netdata.io 1603460665 0.0 \n",
" 1603460666 0.0 \n",
" 1603460667 0.0 \n",
" 1603460668 0.0 \n",
" 1603460669 0.0 \n",
"\n",
" system.softnet_stat|processed \\\n",
"host time_idx \n",
"cdn77.my-netdata.io 1603460665 185.18660 \n",
" 1603460666 212.22230 \n",
" 1603460667 192.34850 \n",
" 1603460668 163.72629 \n",
" 1603460669 186.40330 \n",
"\n",
" system.softnet_stat|received_rps \\\n",
"host time_idx \n",
"cdn77.my-netdata.io 1603460665 0.0 \n",
" 1603460666 0.0 \n",
" 1603460667 0.0 \n",
" 1603460668 0.0 \n",
" 1603460669 0.0 \n",
"\n",
" system.softnet_stat|squeezed \n",
"host time_idx \n",
"cdn77.my-netdata.io 1603460665 0.0 \n",
" 1603460666 0.0 \n",
" 1603460667 0.0 \n",
" 1603460668 0.0 \n",
" 1603460669 0.0 \n",
"\n",
"[5 rows x 30 columns]"
],
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| \n | \n | system.cpu|guest | \nsystem.cpu|guest_nice | \nsystem.cpu|iowait | \nsystem.cpu|irq | \nsystem.cpu|nice | \nsystem.cpu|softirq | \nsystem.cpu|steal | \nsystem.cpu|system | \nsystem.cpu|user | \nsystem.intr|interrupts | \n... | \nsystem.processes|running | \nsystem.ram|buffers | \nsystem.ram|cached | \nsystem.ram|free | \nsystem.ram|used | \nsystem.softnet_stat|dropped | \nsystem.softnet_stat|flow_limit_count | \nsystem.softnet_stat|processed | \nsystem.softnet_stat|received_rps | \nsystem.softnet_stat|squeezed | \n
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| host | \ntime_idx | \n\n | \n | \n | \n | \n | \n | \n | \n | \n | \n | \n | \n | \n | \n | \n | \n | \n | \n | \n | \n | \n |
| cdn77.my-netdata.io | \n1603460665 | \n0.0 | \n0.0 | \n32.82828 | \n0.0 | \n0.0 | \n0.0 | \n0.0 | \n2.020202 | \n0.505050 | \n339.1384 | \n... | \n2.0 | \n244.9961 | \n2650.066 | \n392.9688 | \n677.4180 | \n0.0 | \n0.0 | \n185.18660 | \n0.0 | \n0.0 | \n
| 1603460666 | \n0.0 | \n0.0 | \n0.00000 | \n0.0 | \n0.0 | \n0.0 | \n0.0 | \n1.507538 | \n2.010050 | \n366.6814 | \n... | \n4.0 | \n244.9961 | \n2650.066 | \n389.1836 | \n681.2031 | \n0.0 | \n0.0 | \n212.22230 | \n0.0 | \n0.0 | \n|
| 1603460667 | \n0.0 | \n0.0 | \n0.00000 | \n0.0 | \n0.0 | \n0.0 | \n0.0 | \n1.515151 | \n0.505050 | \n334.6279 | \n... | \n1.0 | \n244.9961 | \n2650.070 | \n389.2617 | \n681.1211 | \n0.0 | \n0.0 | \n192.34850 | \n0.0 | \n0.0 | \n|
| 1603460668 | \n0.0 | \n0.0 | \n0.00000 | \n0.0 | \n0.0 | \n0.0 | \n0.0 | \n1.015228 | \n0.507614 | \n307.5347 | \n... | \n1.0 | \n244.9961 | \n2650.070 | \n389.2305 | \n681.1523 | \n0.0 | \n0.0 | \n163.72629 | \n0.0 | \n0.0 | \n|
| 1603460669 | \n0.0 | \n0.0 | \n0.00000 | \n0.0 | \n0.0 | \n0.0 | \n0.0 | \n2.000000 | \n1.000000 | \n324.9979 | \n... | \n4.0 | \n244.9961 | \n2650.066 | \n388.8750 | \n681.5117 | \n0.0 | \n0.0 | \n186.40330 | \n0.0 | \n0.0 | \n
5 rows × 30 columns
\n