Leonardo Gregianin leogregianin

CPU: percentage of limit

A lot of people land when trying to find out how to calculate CPU usage metric correctly in prometheus, myself included! So I'll post what I eventually ended up using as I think it's still a little difficult trying to tie together all the snippets of info here and elsewhere.

This is specific to k8s and containers that have CPU limits set.

To show CPU usage as a percentage of the limit given to the container, this is the Prometheus query we used to create nice graphs in Grafana:

sum(rate(container_cpu_usage_seconds_total{name!~".*prometheus.*", image!="", container_name!="POD"}[5m])) by (pod_name, container_name) /

	import pandas as pd

	# Caminho do arquivo
	file_path = "/mnt/data/controle.xlsx"

	# Criando um arquivo Excel com múltiplas abas usando xlsxwriter
	with pd.ExcelWriter(file_path, engine="xlsxwriter") as writer:
	workbook = writer.book

	# Criando dados para a aba "Lançamentos"

	import time

	from typing import IO, Iterator


	import python_calamine
	def f_calamine(file: IO[bytes]) -> Iterator[dict[str, object]]:
	workbook = python_calamine.CalamineWorkbook.from_filelike(file)
	yield from iter(workbook.get_sheet_by_index(0).to_python())

	from xml.etree import ElementTree
	from lxml.etree import XML
	import xmltodict
	import untangle
	from benchmarker import Benchmarker

	N = 1000 * 1
	N = 1000 * 100

	xml_string = """<?xml version="1.0"?>

	# -- coding: utf-8 --
	from __future__ import unicode_literals

	from django.db import migrations, models
	from django_cryptography.fields import encrypt

	app_with_model = 'account'
	model_with_column = 'User'
	column_to_encrypt = 'email_address'
	column_field_class = models.CharField

	"""Turtle module http://cursodepython.com.br"""
	import turtle

	turtle.bgcolor("black")
	turtle = turtle.Turtle()
	turtle.shape("turtle")
	turtle.speed(3)
	turtle.width(10)
	turtle.color("blue", "yellow")
	turtle.pencolor("red")

	# Repo: https://github.com/leogregianin/BancosBrasileiros/blob/master/schemas/python.py

	import json
	import httpx

	req = httpx.get('https://raw.githubusercontent.com/guibranco/BancosBrasileiros/master/data/bancos.json')
	bank_json = req.text.replace("\n", "")

	with open(bank_json) as json_string:
	result = bank_from_dict(json.load(json_string))

	import timeit


	def so_numeros_filter_lambda(texto):
	return ''.join(filter(lambda c: ord(c) in range(48, 58), texto))

	def so_numeros_filter(texto):
	return ''.join(filter(str.isdigit, str(texto)))

	def so_numeros_listcomp(texto):

	$ python -c "import sys; print(sys.path)"
	[
	'',
	'/usr/local/lib/python3.7',
	'~/.local/lib/python3.7/site-packages',
	'/usr/local/lib/python3.7/site-packages'
	]