Jenkins 和 Elasticsearch 集成

通过 Telegraf(由 InfluxData 构建的开源数据连接器)实现的强大性能和简易集成。

info

对于大规模实时查询,这不是推荐的配置。为了优化查询和压缩、实现高速摄取和高可用性,您可能需要考虑 Jenkins 和 InfluxDB

5B+

Telegraf 下载量

#1

时间序列数据库
来源:DB Engines

1B+

InfluxDB 下载量

2,800+

贡献者

目录

强大性能,无限扩展

收集、组织和处理海量高速数据。当您将任何数据视为时间序列数据时,它都会更有价值。InfluxDB 是排名第一的时间序列平台,旨在通过 Telegraf 实现扩展。

查看入门方法

输入和输出集成概述

Jenkins 插件通过其 API 从 Jenkins 实例收集有关作业和节点的关键信息,从而促进全面的监控和分析。

Telegraf Elasticsearch 插件无缝地将指标发送到 Elasticsearch 服务器。该插件处理模板创建和动态索引管理,并支持各种 Elasticsearch 特有功能,以确保数据格式正确,以便存储和检索。

集成详情

Jenkins

Jenkins Telegraf 插件允许用户从 Jenkins 实例收集指标,而无需在 Jenkins 本身安装任何额外的插件。通过利用 Jenkins API,该插件检索有关 Jenkins 环境中运行的节点和作业的信息。此集成提供了 Jenkins 基础设施的全面概览,包括可用于监控和分析的实时指标。主要功能包括用于作业和节点选择的可配置过滤器、可选的 TLS 安全设置以及有效管理请求超时和连接限制的能力。这使其成为依赖 Jenkins 进行持续集成和交付的团队的必备工具,确保他们拥有保持最佳性能和可靠性所需的洞察力。

Elasticsearch

此插件将指标写入 Elasticsearch,这是一个分布式、RESTful 的搜索和分析引擎,能够近乎实时地存储大量数据。它旨在处理 Elasticsearch 5.x 到 7.x 版本,并利用其动态模板功能来正确管理数据类型映射。该插件支持高级功能,如模板管理、动态索引命名以及与 OpenSearch 的集成。它还允许配置 Elasticsearch 节点的身份验证和健康监控。

配置

Jenkins

[[inputs.jenkins]]
  ## The Jenkins URL in the format "schema://host:port"
  url = "http://my-jenkins-instance:8080"
  # username = "admin"
  # password = "admin"

  ## Set response_timeout
  response_timeout = "5s"

  ## Optional TLS Config
  # tls_ca = "/etc/telegraf/ca.pem"
  # tls_cert = "/etc/telegraf/cert.pem"
  # tls_key = "/etc/telegraf/key.pem"
  ## Use SSL but skip chain & host verification
  # insecure_skip_verify = false

  ## Optional Max Job Build Age filter
  ## Default 1 hour, ignore builds older than max_build_age
  # max_build_age = "1h"

  ## Optional Sub Job Depth filter
  ## Jenkins can have unlimited layer of sub jobs
  ## This config will limit the layers of pulling, default value 0 means
  ## unlimited pulling until no more sub jobs
  # max_subjob_depth = 0

  ## Optional Sub Job Per Layer
  ## In workflow-multibranch-plugin, each branch will be created as a sub job.
  ## This config will limit to call only the lasted branches in each layer,
  ## empty will use default value 10
  # max_subjob_per_layer = 10

  ## Jobs to include or exclude from gathering
  ## When using both lists, job_exclude has priority.
  ## Wildcards are supported: [ "jobA/*", "jobB/subjob1/*"]
  # job_include = [ "*" ]
  # job_exclude = [ ]

  ## Nodes to include or exclude from gathering
  ## When using both lists, node_exclude has priority.
  # node_include = [ "*" ]
  # node_exclude = [ ]

  ## Worker pool for jenkins plugin only
  ## Empty this field will use default value 5
  # max_connections = 5

  ## When set to true will add node labels as a comma-separated tag. If none,
  ## are found, then a tag with the value of 'none' is used. Finally, if a
  ## label contains a comma it is replaced with an underscore.
  # node_labels_as_tag = false

Elasticsearch


[[outputs.elasticsearch]]
  ## The full HTTP endpoint URL for your Elasticsearch instance
  ## Multiple urls can be specified as part of the same cluster,
  ## this means that only ONE of the urls will be written to each interval
  urls = [ "http://node1.es.example.com:9200" ] # required.
  ## Elasticsearch client timeout, defaults to "5s" if not set.
  timeout = "5s"
  ## Set to true to ask Elasticsearch a list of all cluster nodes,
  ## thus it is not necessary to list all nodes in the urls config option
  enable_sniffer = false
  ## Set to true to enable gzip compression
  enable_gzip = false
  ## Set the interval to check if the Elasticsearch nodes are available
  ## Setting to "0s" will disable the health check (not recommended in production)
  health_check_interval = "10s"
  ## Set the timeout for periodic health checks.
  # health_check_timeout = "1s"
  ## HTTP basic authentication details.
  ## HTTP basic authentication details
  # username = "telegraf"
  # password = "mypassword"
  ## HTTP bearer token authentication details
  # auth_bearer_token = "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9"

  ## Index Config
  ## The target index for metrics (Elasticsearch will create if it not exists).
  ## You can use the date specifiers below to create indexes per time frame.
  ## The metric timestamp will be used to decide the destination index name
  # %Y - year (2016)
  # %y - last two digits of year (00..99)
  # %m - month (01..12)
  # %d - day of month (e.g., 01)
  # %H - hour (00..23)
  # %V - week of the year (ISO week) (01..53)
  ## Additionally, you can specify a tag name using the notation {{tag_name}}
  ## which will be used as part of the index name. If the tag does not exist,
  ## the default tag value will be used.
  # index_name = "telegraf-{{host}}-%Y.%m.%d"
  # default_tag_value = "none"
  index_name = "telegraf-%Y.%m.%d" # required.

  ## Optional Index Config
  ## Set to true if Telegraf should use the "create" OpType while indexing
  # use_optype_create = false

  ## Optional TLS Config
  # tls_ca = "/etc/telegraf/ca.pem"
  # tls_cert = "/etc/telegraf/cert.pem"
  # tls_key = "/etc/telegraf/key.pem"
  ## Use TLS but skip chain & host verification
  # insecure_skip_verify = false

  ## Template Config
  ## Set to true if you want telegraf to manage its index template.
  ## If enabled it will create a recommended index template for telegraf indexes
  manage_template = true
  ## The template name used for telegraf indexes
  template_name = "telegraf"
  ## Set to true if you want telegraf to overwrite an existing template
  overwrite_template = false
  ## If set to true a unique ID hash will be sent as sha256(concat(timestamp,measurement,series-hash)) string
  ## it will enable data resend and update metric points avoiding duplicated metrics with different id's
  force_document_id = false

  ## Specifies the handling of NaN and Inf values.
  ## This option can have the following values:
  ##    none    -- do not modify field-values (default); will produce an error if NaNs or infs are encountered
  ##    drop    -- drop fields containing NaNs or infs
  ##    replace -- replace with the value in "float_replacement_value" (default: 0.0)
  ##               NaNs and inf will be replaced with the given number, -inf with the negative of that number
  # float_handling = "none"
  # float_replacement_value = 0.0

  ## Pipeline Config
  ## To use a ingest pipeline, set this to the name of the pipeline you want to use.
  # use_pipeline = "my_pipeline"
  ## Additionally, you can specify a tag name using the notation {{tag_name}}
  ## which will be used as part of the pipeline name. If the tag does not exist,
  ## the default pipeline will be used as the pipeline. If no default pipeline is set,
  ## no pipeline is used for the metric.
  # use_pipeline = "{{es_pipeline}}"
  # default_pipeline = "my_pipeline"
  #
  # Custom HTTP headers
  # To pass custom HTTP headers please define it in a given below section
  # [outputs.elasticsearch.headers]
  #    "X-Custom-Header" = "custom-value"

  ## Template Index Settings
  ## Overrides the template settings.index section with any provided options.
  ## Defaults provided here in the config
  # template_index_settings = {
  #   refresh_interval = "10s",
  #   mapping.total_fields.limit = 5000,
  #   auto_expand_replicas = "0-1",
  #   codec = "best_compression"
  # }

输入和输出集成示例

Jenkins

  1. 持续集成监控:使用 Jenkins 插件通过收集作业持续时间和失败率的指标来监控持续集成管道的性能。这可以帮助团队识别管道中的瓶颈并提高整体构建效率。

  2. 资源分配分析:利用 Jenkins 节点指标来评估不同代理之间的资源使用情况。通过了解资源的分配方式,团队可以优化其 Jenkins 架构,从而可能重新分配代理或调整作业配置以获得更好的性能。

  3. 作业执行趋势:分析历史作业性能指标以识别作业执行随时间变化的趋势。通过这些数据,团队可以主动解决潜在问题,并在问题扩大之前根据需要调整作业或其配置。

  4. 作业失败警报:实施利用 Jenkins 作业指标的警报,以便在作业失败时通知团队成员。这种主动方法可以提高运营意识并加快对故障的响应时间,从而确保有效监控关键作业。

Elasticsearch

  1. 基于时间的索引:使用此插件将指标存储在 Elasticsearch 中,以根据收集时间为每个指标建立索引。例如,CPU 指标可以存储在名为 telegraf-2023.01.01 的每日索引中,从而方便基于时间的查询和保留策略。

  2. 动态模板管理:利用模板管理功能自动创建为您的指标量身定制的自定义模板。这允许您定义如何索引和分析不同的字段,而无需手动配置 Elasticsearch,从而确保最佳的查询数据结构。

  3. OpenSearch 兼容性:如果您正在使用 AWS OpenSearch,则可以通过激活兼容模式来配置此插件以无缝工作,从而确保您现有的 Elasticsearch 客户端保持功能并与较新的集群设置兼容。

反馈

感谢您成为我们社区的一份子!如果您有任何一般性反馈或在这些页面上发现任何错误,我们欢迎并鼓励您提出意见。请在 InfluxDB 社区 Slack 中提交您的反馈。

强大性能,无限扩展

收集、组织和处理海量高速数据。当您将任何数据视为时间序列数据时,它都会更有价值。InfluxDB 是排名第一的时间序列平台,旨在通过 Telegraf 实现扩展。

查看入门方法

相关集成

HTTP 和 InfluxDB 集成

HTTP 插件从一个或多个 HTTP(S) 端点收集指标。它支持各种身份验证方法和数据格式的配置选项。

查看集成

Kafka 和 InfluxDB 集成

此插件从 Kafka 读取消息,并允许基于这些消息创建指标。它支持各种配置,包括不同的 Kafka 设置和消息处理选项。

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Kinesis 和 InfluxDB 集成

Kinesis 插件允许从 AWS Kinesis 流读取指标。它支持多种输入数据格式,并提供使用 DynamoDB 的检查点功能,以实现可靠的消息处理。

查看集成