filebeat+logstash+influxdb+grafana監(jiān)控kube-scheduler調(diào)度耗時(shí)

overview

kubernetes集群中scheduler對(duì)pod各個(gè)階段的調(diào)度耗時(shí)也展示了scheduler的性能，目前在社區(qū)中沒(méi)有找到相關(guān)的監(jiān)控項(xiàng)，于是本文將使用filebeat+logstash+influxdb+grafana技術(shù)棧將Metres展示監(jiān)控起來(lái)。

kube-scheduler.INFO相關(guān)Trace日志
I0117 18:08:43.224106   87811 trace.go:76] Trace[1863564834]: "Scheduling fat-app/xxxxxxxx-xxxxxxxx-3404-0" (started: 2019-01-17 18:08:43.106820332 +0800 CST m=+116911.416416886) (total time: 117.213043ms):
Trace[1863564834]: [117.187μs] [117.187μs] Computing predicates
Trace[1863564834]: [2.093583ms] [1.976396ms] Prioritizing
Trace[1863564834]: [117.172797ms] [115.079214ms] Selecting host
Trace[1863564834]: [117.213043ms] [40.246μs] END

filebeat配置

filebeat.prospectors:
- type: log
  paths:
    - /var/log/kubernetes/kube-scheduler.*.INFO.*
  include_lines: ['trace','Trace']
# pattern: 正則表達(dá)式
# negate: true 或 false(默認(rèn)是false)，false表示匹配pattern的行合并到上一行；true表示不匹配pattern的行合并到上一行
#  match:  after 或 before，合并到上一行的末尾或開(kāi)頭
  multiline:
    pattern: '^Trace\[[0-9]+\]'
    negate: false
    match: after
  fields:
    tag: scheduler  #添加tag
  fields_under_root: true
  scan_frequency: 10s
  ignore_older: 6h
  close_inactive: 5m
  close_removed: true
  clean_removed: true
  tail_files: false

fields:
  zone: $zone_name  #添加自己的環(huán)境信息
fields_under_root: true

output.logstash:
  enabled: true
  hosts:
    - $logstash_host:5044  #logstash的地址

logging.level: info
logging.metrics.enabled: false
http.enabled: true
http.host: localhost
http.port: 5066

setup.dashboards.enabled: false
setup.template.enabled: false

path.home: /usr/share/filebeat
path.data: /var/lib/filebeat
path.logs: /var/log/filebeat
filebeat.registry_file: ${path.data}/registry
max_procs: 2

note:

  • debug時(shí)可通過(guò) filebeat -e -c filebeat.yml -d "publish"來(lái)確認(rèn)采集的信息是否正確
  • 若有如下報(bào)錯(cuò)，則需要將filebeat stop掉，將/var/lib/filebeat/registry 刪除，重啟filebeat重新注冊(cè)即可

ERROR registrar/registrar.go:346 Writing of registry returned error: rename /var/lib/filebeat/registry.new /var/lib/filebeat/registry: no such file or directory. Continuing...

Logstash的安裝及配置

install logstash

  • 下載logstash安裝
$ wget https://artifacts.elastic.co/downloads/logstash/logstash-6.5.4.rpm
$ rpm -ivh
  • 到logstash的path目錄下，鏈接/etc/logstash
$ cd /usr/share/logstash/config
$ ln -s /etc/logstash/* .
  • 更改logstash相關(guān)目錄權(quán)限
$ chown -R /etc/logstash
$ chown -R /usr/share/logstash
$ chown -R /var/lib/logstash
  • 安裝所需插件，詳細(xì)見(jiàn)下文
$ cd /usr/share/logstash/
$ bin/logstash-plugin install logstash-output-influxdb
  • 檢查配置文件是否正常
$ bin/logstash -f /etc/logstash/logstash.conf --config.test_and_exit
  • 啟動(dòng)
$ bin/logstash -f /etc/logstash/logstash.conf --config.reload.automatic

install-plugin

  • logstash-filter-grok
  • logstash-output-influxdb
    插件需要單獨(dú)安裝，安裝方式如果能不能連接外網(wǎng)則可采用以下方式
    https://gems.ruby-china.com/

（1）盡可能用比較新的 RubyGems 版本，建議 2.6.x 以上

$ yum install -y gem
$ gem update --system # 這里請(qǐng)翻墻一下
$ gem -v
  2.6.3

（2） 更換到國(guó)內(nèi)的源，確保只有 gems.ruby-china.com

$ gem sources --add https://gems.ruby-china.com/ --remove https://rubygems.org/
$ gem sources -l
  https://gems.ruby-china.com

（3）安裝單個(gè)插件

$ gem install logstash-output-influxdb

（4）安裝所有Gemfile中的插件

# 在Gemfile中添加想要安裝的plugin
  gem 'logstash-output-influxdb', '~> 5.0', '>= 5.0.5'
$ bin/logstash-plug ininstall --no-verify

self-defined grok-pattern

KUBESCHEDULER .*Scheduling %{NOTSPACE:namespace:tag}/%{NOTSPACE:podname:tag}\".*total time: %{NUMBER:total_time}%{NOTSPACE:total_mesurement}\).*Trace\[\S+\].*\[\S+\].*\[%{NUMBER:computing_time}%{NOTSPACE:computing_mesurement}\]\s+Computing %{WORD:ComputingPredicates:tag}.*Trace\[\S+\].*\[\S+\].*\[%{NUMBER:prioritizing_time}%{NOTSPACE:prioritizing_mesurement}\]\s+%{WORD:Prioritizing:tag}.*Trace\[\S+\].*\[\S+\].*\[%{NUMBER:SelectingHost_time}%{NOTSPACE:SelectingHost_mesurement}\]\s+%{WORD:SelectingHost:tag}.**Trace\[\S+\].*\[\S+\].*\[%{NUMBER:end_time}%{NOTSPACE:end_mesurement}\]\s+%{WORD:END:tag}

KUBESCHEDULERSHORT .*Scheduling %{NOTSPACE:namespace:tag}/%{NOTSPACE:podname:tag}\".*total time: %{NUMBER:total_time}%{NOTSPACE:total_mesurement}\).*Trace\[\S+\].*\[\S+\].*\[%{NUMBER:computing_time}%{NOTSPACE:computing_mesurement}\]\s+Computing %{WORD:ComputingPredicates:tag}.**Trace\[\S+\].*\[\S+\].*\[%{NUMBER:end_time}%{NOTSPACE:end_mesurement}\]\s+%{WORD:END:tag}

logstash.conf配置文件

input {
    beats {
        port => "5044"
        client_inactivity_timeout => "60" #默認(rèn)60s
    }   
}
filter {
    grok {
        # 需要安裝grok插件，并且pattern能正確匹配才能有輸出
        patterns_dir => ["/usr/share/logstash/config/pattern"] #自定義的grok pattern
        match => {
                   "message" => ["%{KUBESCHEDULER}", "%{KUBESCHEDULERSHORT}"]
                 }
        remove_field => ["message"]

    } 
    ruby {
    # logstash的算術(shù)運(yùn)算操作，統(tǒng)一運(yùn)算單位
        code => "
            total_unit = event.get('total_mesurement')
            computing_unit = event.get('computing_mesurement')
            prioritizing_unit = event.get('prioritizing_mesurement')
            selecting_unit = event.get('SelectingHost_mesurement')
            ending_unit = event.get('end_mesurement')
            if total_unit == 'ms'
                event.set('total_time',(event.get('total_time').to_f*1000))
            elsif total_unit == 's'
                event.set('total_time',(event.get('total_time').to_f*1000000))
            else
                event.set('total_time',(event.get('total_time').to_f))
            end
            if computing_unit == 'ms'
                event.set('computing_time',(event.get('computing_time').to_f*1000))
            elsif computing_unit == 's'
                event.set('computing_time',(event.get('computing_time').to_f*1000000))
            else
                event.set('computing_time',(event.get('computing_time').to_f))
            end
            if prioritizing_unit == 'ms'
                event.set('prioritizing_time',(event.get('prioritizing_time').to_f*1000))
            elsif prioritizing_unit == 's'
                event.set('prioritizing_time',(event.get('prioritizing_time').to_f*1000000))
            else
                event.set('prioritizing_time',(event.get('prioritizing_time').to_f))
            end
            if selecting_unit == 'ms'
                event.set('SelectingHost_time',(event.get('SelectingHost_time').to_f*1000))
            elsif selecting_unit == 's'
                event.set('SelectingHost_time',(event.get('SelectingHost_time').to_f*1000000))
            else
                event.set('SelectingHost_time',(event.get('SelectingHost_time').to_f))
            end
            if ending_unit == 'ms'
                event.set('end_time',(event.get('end_time').to_f*1000))
            elsif ending_unit == 's'
                event.set('end_time',(event.get('end_time').to_f*1000000))
            else
                event.set('end_time',(event.get('end_time').to_f))
            end
           "   
        remove_field => ["total_mesurement","computing_mesurement","prioritizing_mesurement","SelectingHost_mesurement","end_mesurement","prospector","offset","tags","beat","source"]
    }   
}

output {
  influxdb {
    db => "$dbname"
    host => "$influxdb-host"
    port => "8086"
    user => "$username"
    password => "$yourpasswd"
    measurement => "kubeSchedulerTimeCost"
    coerce_values => {
      "total_time" => "float"
      "computing_time" => "float"
      "prioritizing_time" => "float"
      "SelectingHost_time" => "float"
      "end_time" => "float"
    }
    data_points => {
      "namespace" => "%{namespace}"
      "podname" => "%{podname}"
      "ComputingPredicates" => "%{ComputingPredicates}"
      "Prioritizing" => "%{Prioritizing}"
      "SelectingHost" => "%{SelectingHost}"
      "End" => "%{END}"
      "zone" => "%{zone}"
      "total_time" => "%{total_time}"
      "computing_time" => "%{computing_time}"
      "prioritizing_time" => "%{prioritizing_time}"
      "SelectingHost_time" => "%{SelectingHost_time}"
      "end_time" => "%{end_time}"
      "host" => "%{host}"
     }   
    send_as_tags => ["host","zone","namespace","podname","ComputingPredicates","Prioritizing","SelectingHost","End"]
  }
#  elasticsearch {
#    hosts => "$es-host:9200"
#    manage_template => false
#    index => "%{[@metadata][beat]}-%{[@metadata][version]}-%{+YYYY.MM.dd}"
#    document_type => "%{[@metadata][type]}"
#  }
  stdout { codec => rubydebug }
}

note:

  • 可通過(guò)執(zhí)行bin/logstash -f ./config/conf.d/scheduler.conf -- config.reload.automatic
  • 若啟動(dòng)logstash服務(wù)，但是input beats 5044 port沒(méi)有打開(kāi)，則可能時(shí)權(quán)限問(wèn)題，更改一下queue的權(quán)限chown -R logstash:logstash /var/lib/logstash

influxdb

influxdb需要將相應(yīng)的端口打開(kāi)

grafana看板

可看到各個(gè)集群的pod在各個(gè)階段的調(diào)度耗時(shí)及調(diào)度時(shí)間


scheduler.png
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