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ZK监控方法以及核心指标

探讨zk的监控数据采集方式以及需要关注的核心指标,便于日常生产进行监控和巡检。

1. 监控指标采集

  1. 3.6.0 版本后,原生支持开放指标接口供Prometheus采集。
  2. 如果低于3.6.0 版本,只能使用zookeeper-exporter进行采集

1.1 zk版本高于3.6.0监控指标采集

详细的可以参考 ZooKeeper Monitor Guide

具体操作如下
1, 调整zoo.cfg配置,增加配置

metricsProvider.className=org.apache.zookeeper.metrics.prometheus.PrometheusMetricsProvider
metricsProvider.httpPort=7000
metricsProvider.exportJvmInfo=true

在这里插入图片描述
指标的暴露接口是7000,完成配置并重启zk后可以获取对应的指标。

 curl localhost:7000/metrics

在这里插入图片描述

1.2 zk版本低于3.6.0监控指标采集

可以通过 zookeeper-exporter 下载zookeeper-exporter的安装包,并进行配置。

进程启动配置

./zookeeper-exporter -listen 0.0.0.0:7000  -zk-hosts Master:2181,Slave1:2181,Slave2:2181

更多使用方法可以参考 文档

指标的暴露接口是7000,完成配置并重启zk后可以获取对应的指标。

 curl localhost:7000/metrics

1.3 配置promethues采集和大盘

完成指标采集后,可以通过prometheus配置监控、告警和大盘。

配置prometheus的指标采集任务

  - job_name: zk
    static_configs:
      - targets: ['172.19.0.2:7000','172.19.0.3:7000','172.19.0.4:7000']

完成prometheus监控指标后,就可以配置grafana大盘,grafana的dashboard官网可以下载很多优秀的大盘进行借鉴,本文不再追溯。

2. 核心告警指标

ZooKeeper Monitor Guide中记录了zk的关键指标进行配置告警,可以参考。

groups:
- name: zk-alert-example
  rules:
  - alert: ZooKeeper server is down
    expr:  up == 0
    for: 1m
    labels:
      severity: critical
    annotations:
      summary: "Instance {{ $labels.instance }} ZooKeeper server is down"
      description: "{{ $labels.instance }} of job {{$labels.job}} ZooKeeper server is down: [{{ $value }}]."

  - alert: create too many znodes
    expr: znode_count > 1000000
    for: 1m
    labels:
      severity: warning
    annotations:
      summary: "Instance {{ $labels.instance }} create too many znodes"
      description: "{{ $labels.instance }} of job {{$labels.job}} create too many znodes: [{{ $value }}]."

  - alert: create too many connections
    expr: num_alive_connections > 50 # suppose we use the default maxClientCnxns: 60
    for: 1m
    labels:
      severity: warning
    annotations:
      summary: "Instance {{ $labels.instance }} create too many connections"
      description: "{{ $labels.instance }} of job {{$labels.job}} create too many connections: [{{ $value }}]."

  - alert: znode total occupied memory is too big
    expr: approximate_data_size /1024 /1024 > 1 * 1024 # more than 1024 MB(1 GB)
    for: 1m
    labels:
      severity: warning
    annotations:
      summary: "Instance {{ $labels.instance }} znode total occupied memory is too big"
      description: "{{ $labels.instance }} of job {{$labels.job}} znode total occupied memory is too big: [{{ $value }}] MB."

  - alert: set too many watch
    expr: watch_count > 10000
    for: 1m
    labels:
      severity: warning
    annotations:
      summary: "Instance {{ $labels.instance }} set too many watch"
      description: "{{ $labels.instance }} of job {{$labels.job}} set too many watch: [{{ $value }}]."

  - alert: a leader election happens
    expr: increase(election_time_count[5m]) > 0
    for: 1m
    labels:
      severity: warning
    annotations:
      summary: "Instance {{ $labels.instance }} a leader election happens"
      description: "{{ $labels.instance }} of job {{$labels.job}} a leader election happens: [{{ $value }}]."

  - alert: open too many files
    expr: open_file_descriptor_count > 300
    for: 1m
    labels:
      severity: warning
    annotations:
      summary: "Instance {{ $labels.instance }} open too many files"
      description: "{{ $labels.instance }} of job {{$labels.job}} open too many files: [{{ $value }}]."

  - alert: fsync time is too long
    expr: rate(fsynctime_sum[1m]) > 100
    for: 1m
    labels:
      severity: warning
    annotations:
      summary: "Instance {{ $labels.instance }} fsync time is too long"
      description: "{{ $labels.instance }} of job {{$labels.job}} fsync time is too long: [{{ $value }}]."

  - alert: take snapshot time is too long
    expr: rate(snapshottime_sum[5m]) > 100
    for: 1m
    labels:
      severity: warning
    annotations:
      summary: "Instance {{ $labels.instance }} take snapshot time is too long"
      description: "{{ $labels.instance }} of job {{$labels.job}} take snapshot time is too long: [{{ $value }}]."

  - alert: avg latency is too high
    expr: avg_latency > 100
    for: 1m
    labels:
      severity: warning
    annotations:
      summary: "Instance {{ $labels.instance }} avg latency is too high"
      description: "{{ $labels.instance }} of job {{$labels.job}} avg latency is too high: [{{ $value }}]."

  - alert: JvmMemoryFillingUp
    expr: jvm_memory_bytes_used / jvm_memory_bytes_max{area="heap"} > 0.8
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "JVM memory filling up (instance {{ $labels.instance }})"
      description: "JVM memory is filling up (> 80%)\n labels: {{ $labels }}  value = {{ $value }}\n"

3. 参考文章


原文地址:https://blog.csdn.net/weixin_43845924/article/details/135855210

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