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Kubernetes 计算 CPU 使用率

作者:CTO技术共享
  • 2022 年 8 月 10 日
    广东
  • 本文字数:3744 字

    阅读完需:约 12 分钟

Kubernetes 计算CPU 使用率

使用 Prometheus 配置 kubernetes 环境中 Container 的 CPU 使用率时,会经常遇到 CPU 使用超出 100%,下面就来解释一下:

  1. container_spec_cpu_period

    当对容器进行 CPU 限制时,CFS 调度的时间窗口,又称容器 CPU 的时钟周期通常是 100,000 微秒

  2. container_spec_cpu_quota

    是指容器的使用 CPU 时间周期总量,如果 quota 设置的是 700,000,就代表该容器可用的 CPU 时间是 7*100,000 微秒,通常对应 kubernetes 的 resource.cpu.limits 的值

  3. container_spec_cpu_share

    是指 container 使用分配主机 CPU 相对值,比如 share 设置的是 500m,代表窗口启动时向主机节点申请 0.5 个 CPU,也就是 50,000 微秒,通常对应 kubernetes 的 resource.cpu.requests 的值

  4. container_cpu_usage_seconds_total

    统计容器的 CPU 在一秒内消耗使用率,应注意的是该 container 所有的 CORE

  5. container_cpu_system_seconds_total

    统计容器内核态在一秒时间内消耗的 CPU

  6. container_cpu_user_seconds_total

    统计容器用户态在一秒时间内消耗的 CPU

    参考官方地址 https://docs.signalfx.com/en/latest/integrations/agent/monitors/cadvisor.html https://github.com/google/cadvisor/blob/master/docs/storage/prometheus.md

具体公式

  1. 默认如果直接使用 container_cpu_usage_seconds_total 的话,如下

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

    默认统计的数据是该容器所有的 CORE 的平均使用率


  1. 如果要精确计算每个容器的 CPU 使用率,使用 % 呈现的形式,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,就代表该容器有多少个 CORE


  1. 参考官方 git issue

    https://github.com/google/cadvisor/issues/2026#issuecomment-415819667

docker stats

docker stats 输出的指标列是如何计算的,如下:

首先 docker stats 是通过 Docker API /containers/(id)/stats 接口来获得 live data stream,再通过 docker stats 进行整合。

在 Linux 中使用 docker stats 输出的内存使用率(MEM USAGE),实则该列的计算是不包含 Cache 的内存。

cache usage 在 ≤ docker 19.03 版本的 API 接口输出对应的字段是 memory_stats.total_inactive_file,而 > docker 19.03 的版本对应的字段是 memory_stats.cache。

docker stats 输出的 PIDS 一列代表的是该容器创建的进程或线程的数量,threads 是 Linux kernel 中的一个术语,又称 lightweight process & kernel task

  1. 如何通过 Docker API 查看容器资源使用率,如下


$ 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"
复制代码


  1. 如何计算

    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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