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如何計算Kubernetes容器CPU使用率

本文轉載自   查看原文   2022-01-05 16:37   7220    Prometheus/ docker

參數解釋

使用Prometheus配置kubernetes環境中Container的CPU使用率時，會經常遇到CPU使用超出100%，下面就來解釋一下

  1. container_spec_cpu_period

    當對容器進行CPU限制時，CFS調度的時間窗口，又稱容器CPU的時鍾周期通常是100，000微秒

  2. container_spec_cpu_quota

    是指容器的使用CPU時間周期總量，如果quota設置的是700，000，就代表該容器可用的CPU時間是7*100,000微秒，通常對應kubernetes的resource.cpu.limits的值

  3. container_spec_cpu_share

    是指container使用分配主機CPU相對值，比如share設置的是500m，代表窗口啟動時向主機節點申請0.5個CPU，也就是50，000微秒，通常對應kubernetes的resource.cpu.requests的值

  4. container_cpu_usage_seconds_total

    統計容器的CPU在一秒內消耗使用率，應注意的是該container所有的CORE

  5. container_cpu_system_seconds_total

    統計容器內核態在一秒時間內消耗的CPU

  6. container_cpu_user_seconds_total

    統計容器用戶態在一秒時間內消耗的CPU
      參考官方地址
      https://docs.signalfx.com/en/latest/integrations/agent/monitors/cadvisor.html
      https://github.com/google/cadvisor/blob/master/docs/storage/prometheus.md

具體公式

  1. 默認如果直接使用container_cpu_usage_seconds_total的話，如下

    sum(irate(container_cpu_usage_seconds_total{container="$Container",instance="$Node",pod="$Pod"}[5m])*100)by(pod)

    默認統計的數據是該容器所有的CORE的平均使用率

  2. 如果要精確計算每個容器的CPU使用率，使用%呈現的形式，如下

    sum(irate(container_cpu_usage_seconds_total{container="$Container",instance="$Node",pod="$Pod"}[5m])*100)by(pod)/sum(container_spec_cpu_quota{container="$Container",instance="$Node",pod="$Pod"}/container_spec_cpu_period{container="$Container",instance="$Node",pod="$Pod"})by(pod)

    其中container_spec_cpu_quota/container_spec_cpu_period，就代表該容器有多少個CORE

  3. 參考官方git issue
    https://github.com/google/cadvisor/issues/2026#issuecomment-415819667

docker stats

docker stats輸出的指標列是如何計算的，如下

首先docker stats是通過Docker API /containers/(id)/stats接口來獲得live data stream，再通過docker stats進行整合

在Linux中使用docker stats輸出的內存使用率（MEM USAGE），實則該列的計算是不包含Cache的內存

cache usage在 ≤ docker 19.03版本的API接口輸出對應的字段是memory_stats.total_inactive_file，而 > docker 19.03的版本對應的字段是memory_stats.cache

docker stats 輸出的PIDS一列代表的是該容器創建的進程或線程的數量，threads是Linux kernel中的一個術語，又稱 lightweight process & kernel task

  1. 如何通過Docker API查看容器資源使用率，如下

    <root@PROD-BE-K8S-WN17 ~># curl -s --unix-socket /var/run/docker.sock "http://localhost/v1.40/containers/10f2db238edc/stats" | jq -r
{
  "read": "2022-01-05T06:14:47.705943252Z",
  "preread": "0001-01-01T00:00:00Z",
  "pids_stats": {
    "current": 240
  },
  "blkio_stats": {
    "io_service_bytes_recursive": [
      {
        "major": 253,
        "minor": 0,
        "op": "Read",
        "value": 0
      },
      {
        "major": 253,
        "minor": 0,
        "op": "Write",
        "value": 917504
      },
      {
        "major": 253,
        "minor": 0,
        "op": "Sync",
        "value": 0
      },
      {
        "major": 253,
        "minor": 0,
        "op": "Async",
        "value": 917504
      },
      {
        "major": 253,
        "minor": 0,
        "op": "Discard",
        "value": 0
      },
      {
        "major": 253,
        "minor": 0,
        "op": "Total",
        "value": 917504
      }
    ],
    "io_serviced_recursive": [
      {
        "major": 253,
        "minor": 0,
        "op": "Read",
        "value": 0
      },
      {
        "major": 253,
        "minor": 0,
        "op": "Write",
        "value": 32
      },
      {
        "major": 253,
        "minor": 0,
        "op": "Sync",
        "value": 0
      },
      {
        "major": 253,
        "minor": 0,
        "op": "Async",
        "value": 32
      },
      {
        "major": 253,
        "minor": 0,
        "op": "Discard",
        "value": 0
      },
      {
        "major": 253,
        "minor": 0,
        "op": "Total",
        "value": 32
      }
    ],
    "io_queue_recursive": [],
    "io_service_time_recursive": [],
    "io_wait_time_recursive": [],
    "io_merged_recursive": [],
    "io_time_recursive": [],
    "sectors_recursive": []
  },
  "num_procs": 0,
  "storage_stats": {},
  "cpu_stats": {
    "cpu_usage": {
      "total_usage": 251563853433744,
      "percpu_usage": [
        22988555937059,
        6049382848016,
        22411490707722,
        5362525449957,
        25004835766513,
        6165050456944,
        27740046633494,
        6245013152748,
        29404953317631,
        5960151933082,
        29169053441816,
        5894880727311,
        25772990860310,
        5398581194412,
        22856145246881,
        5140195759848
      ],
      "usage_in_kernelmode": 30692640000000,
      "usage_in_usermode": 213996900000000
    },
    "system_cpu_usage": 22058735930000000,
    "online_cpus": 16,
    "throttling_data": {
      "periods": 10673334,
      "throttled_periods": 1437,
      "throttled_time": 109134709435
    }
  },
  "precpu_stats": {
    "cpu_usage": {
      "total_usage": 0,
      "usage_in_kernelmode": 0,
      "usage_in_usermode": 0
    },
    "throttling_data": {
      "periods": 0,
      "throttled_periods": 0,
      "throttled_time": 0
    }
  },
  "memory_stats": {
    "usage": 8589447168,
    "max_usage": 8589926400,
    "stats": {
      "active_anon": 0,
      "active_file": 260198400,
      "cache": 1561460736,
      "dirty": 3514368,
      "hierarchical_memory_limit": 8589934592,
      "hierarchical_memsw_limit": 8589934592,
      "inactive_anon": 6947250176,
      "inactive_file": 1300377600,
      "mapped_file": 0,
      "pgfault": 3519153,
      "pgmajfault": 0,
      "pgpgin": 184508478,
      "pgpgout": 184052901,
      "rss": 6947373056,
      "rss_huge": 6090129408,
      "total_active_anon": 0,
      "total_active_file": 260198400,
      "total_cache": 1561460736,
      "total_dirty": 3514368,
      "total_inactive_anon": 6947250176,
      "total_inactive_file": 1300377600,
      "total_mapped_file": 0,
      "total_pgfault": 3519153,
      "total_pgmajfault": 0,
      "total_pgpgin": 184508478,
      "total_pgpgout": 184052901,
      "total_rss": 6947373056,
      "total_rss_huge": 6090129408,
      "total_unevictable": 0,
      "total_writeback": 0,
      "unevictable": 0,
      "writeback": 0
    },
    "limit": 8589934592
  },
  "name": "/k8s_prod-xc-fund_prod-xc-fund-646dfc657b-g4px4_prod_523dcf9d-6137-4abf-b4ad-bd3999abcf25_0",
  "id": "10f2db238edc13f538716952764d6c9751e5519224bcce83b72ea7c876cc0475"

  2. 如何計算

      官方地址

      https://docs.docker.com/engine/api/v1.40/#operation/ContainerStats

    The precpu_stats is the CPU statistic of the previous read, and is used to calculate the CPU usage percentage. It is not an exact copy of the cpu_stats field.

    If either precpu_stats.online_cpus or cpu_stats.online_cpus is nil then for compatibility with older daemons the length of the corresponding cpu_usage.percpu_usage array should be used.

    To calculate the values shown by the stats command of the docker cli tool the following formulas can be used:

    • used_memory = memory_stats.usage - memory_stats.stats.cache

    • available_memory = memory_stats.limit

    • Memory usage % = (used_memory / available_memory) * 100.0

    • cpu_delta = cpu_stats.cpu_usage.total_usage - precpu_stats.cpu_usage.total_usage

    • system_cpu_delta = cpu_stats.system_cpu_usage - precpu_stats.system_cpu_usage

    • number_cpus = lenght(cpu_stats.cpu_usage.percpu_usage) or cpu_stats.online_cpus

    • CPU usage % = (cpu_delta / system_cpu_delta) * number_cpus * 100.0


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