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：

(资料图)

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

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

2.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

2.参考官方 git issuehttps://github.com/google/cadvisor/issues/2026#issuecomment-415819667

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"

2.如何计算官方地址https://docs.docker.com/engine/api/v1.40/#operation/ContainerStatsThe​​​precpu_stats​​is the CPU statistic of thepreviousread, 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: