Docker 和 Elasticsearch 集成

强大的性能和简单的集成,由 Telegraf 提供支持,Telegraf 是 InfluxData 构建的开源数据连接器。

info

这不是大规模实时查询的推荐配置。 为了查询和压缩优化、高速摄取和高可用性,您可能需要考虑 Docker 和 InfluxDB

50 亿+

Telegraf 下载量

#1

时间序列数据库
来源:DB Engines

10 亿+

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,它会更有价值。 借助 InfluxDB,第一的时间序列平台,旨在与 Telegraf 一起扩展。

查看入门方法

输入和输出集成概述

Docker 输入插件允许您使用 Docker Engine API 从 Docker 容器中收集指标,从而增强容器化应用程序的可见性和监控。

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

Docker

Telegraf 的 Docker 输入插件从 Docker Engine API 收集有价值的指标,从而深入了解正在运行的容器。 该插件利用官方 Docker 客户端与 Engine API 接口,使用户能够监控各种容器状态、资源分配和性能指标。 通过按名称和状态过滤容器的选项,以及可自定义的标签,此插件支持在各种环境中灵活监控容器化应用程序,无论是在本地系统上还是在 Kubernetes 等编排平台内。 此外,它通过要求访问 Docker 守护进程的权限来解决安全问题,并强调在容器化环境中部署时的正确配置。

Elasticsearch

此插件将指标写入 Elasticsearch,Elasticsearch 是一种分布式 RESTful 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,例如模板管理、动态索引命名以及与 OpenSearch 的集成。 它还允许对 Elasticsearch 节点进行身份验证和运行状况监控的配置。

配置

Docker

[[inputs.docker]]
  ## Docker Endpoint
  ##   To use TCP, set endpoint = "tcp://[ip]:[port]"
  ##   To use environment variables (ie, docker-machine), set endpoint = "ENV"
  endpoint = "unix:///var/run/docker.sock"

  ## Set to true to collect Swarm metrics(desired_replicas, running_replicas)
  ## Note: configure this in one of the manager nodes in a Swarm cluster.
  ## configuring in multiple Swarm managers results in duplication of metrics.
  gather_services = false

  ## Only collect metrics for these containers. Values will be appended to
  ## container_name_include.
  ## Deprecated (1.4.0), use container_name_include
  container_names = []

  ## Set the source tag for the metrics to the container ID hostname, eg first 12 chars
  source_tag = false

  ## Containers to include and exclude. Collect all if empty. Globs accepted.
  container_name_include = []
  container_name_exclude = []

  ## Container states to include and exclude. Globs accepted.
  ## When empty only containers in the "running" state will be captured.
  # container_state_include = []
  # container_state_exclude = []

  ## Objects to include for disk usage query
  ## Allowed values are "container", "image", "volume" 
  ## When empty disk usage is excluded
  storage_objects = []

  ## Timeout for docker list, info, and stats commands
  timeout = "5s"

  ## Whether to report for each container per-device blkio (8:0, 8:1...),
  ## network (eth0, eth1, ...) and cpu (cpu0, cpu1, ...) stats or not.
  ## Usage of this setting is discouraged since it will be deprecated in favor of 'perdevice_include'.
  ## Default value is 'true' for backwards compatibility, please set it to 'false' so that 'perdevice_include' setting
  ## is honored.
  perdevice = true

  ## Specifies for which classes a per-device metric should be issued
  ## Possible values are 'cpu' (cpu0, cpu1, ...), 'blkio' (8:0, 8:1, ...) and 'network' (eth0, eth1, ...)
  ## Please note that this setting has no effect if 'perdevice' is set to 'true'
  # perdevice_include = ["cpu"]

  ## Whether to report for each container total blkio and network stats or not.
  ## Usage of this setting is discouraged since it will be deprecated in favor of 'total_include'.
  ## Default value is 'false' for backwards compatibility, please set it to 'true' so that 'total_include' setting
  ## is honored.
  total = false

  ## Specifies for which classes a total metric should be issued. Total is an aggregated of the 'perdevice' values.
  ## Possible values are 'cpu', 'blkio' and 'network'
  ## Total 'cpu' is reported directly by Docker daemon, and 'network' and 'blkio' totals are aggregated by this plugin.
  ## Please note that this setting has no effect if 'total' is set to 'false'
  # total_include = ["cpu", "blkio", "network"]

  ## docker labels to include and exclude as tags.  Globs accepted.
  ## Note that an empty array for both will include all labels as tags
  docker_label_include = []
  docker_label_exclude = []

  ## Which environment variables should we use as a tag
  tag_env = ["JAVA_HOME", "HEAP_SIZE"]

  ## 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

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

Docker

  1. 监控容器化应用程序的性能:使用 Docker 输入插件来跟踪在 Docker 容器中运行的应用程序的 CPU、内存、磁盘 I/O 和网络活动。 通过收集这些指标,DevOps 团队可以主动管理资源分配、排除性能瓶颈并确保跨不同环境的最佳应用程序性能。

  2. 与 Kubernetes 集成:利用此插件收集由 Kubernetes 编排的 Docker 容器的指标。 通过过滤掉不必要的 Kubernetes 标签并专注于关键指标,团队可以简化其监控解决方案并创建仪表板,以深入了解在 Kubernetes 集群中运行的微服务的整体运行状况。

  3. 容量规划和资源优化:使用 Docker 输入插件收集的指标来执行 Docker 部署的容量规划。 分析使用模式有助于识别未充分利用的资源和过度配置的容器,从而指导基于实际使用趋势的向上或向下扩展决策。

  4. 容器异常的自动警报:根据通过 Docker 插件收集的指标设置警报规则,以通知团队资源使用量异常激增或服务中断。 这种主动监控方法有助于保持服务可靠性并优化容器化应用程序的性能。

Elasticsearch

  1. 基于时间的索引:使用此插件将指标存储在 Elasticsearch 中,以根据收集的时间为每个指标编制索引。 例如,CPU 指标可以存储在名为 telegraf-2023.01.01 的每日索引中,从而实现轻松的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针对您的指标定制的自定义模板。 这使您可以定义如何索引和分析不同的字段,而无需手动配置 Elasticsearch,从而确保用于查询的最佳数据结构。

  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,它会更有价值。 借助 InfluxDB,第一的时间序列平台,旨在与 Telegraf 一起扩展。

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,并允许根据这些消息创建指标。 它支持各种配置,包括不同的 Kafka 设置和消息处理选项。

查看集成

Kinesis 和 InfluxDB 集成

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

查看集成