OpenTelemetry 和 Elasticsearch 集成

借助 InfluxData 构建的开源数据连接器 Telegraf,实现强大的性能和轻松的集成。

info

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

5B+

Telegraf 下载量

#1

时序数据库
来源:DB Engines

1B+

InfluxDB 下载量

2,800+

贡献者

目录

强大的性能,无限的扩展能力

收集、组织和处理海量高速数据。当您将任何数据视为时序数据时,它都更有价值。借助 InfluxDB,排名第一的时序平台,旨在与 Telegraf 一起扩展。

查看入门方法

输入和输出集成概述

此插件通过 gRPC 从 OpenTelemetry 客户端和代理接收跟踪、指标和日志,从而实现对应用程序的全面可观测性。

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

OpenTelemetry

OpenTelemetry 插件旨在通过 gRPC 从实施 OpenTelemetry 的客户端和代理接收遥测数据,例如跟踪、指标和日志。此插件启动一个 gRPC 服务,监听传入的遥测数据,这使其与按定义的时间间隔收集指标的标准插件不同。OpenTelemetry 生态系统通过提供一种供应商中立的方式来检测、生成、收集和导出遥测数据,帮助开发人员观察和理解其应用程序的性能。此插件的主要功能包括可自定义的连接超时、可调整的传入数据最大消息大小以及用于指定 span、log 和 profile 维度以标记传入指标的选项。凭借这种灵活性,组织可以定制其遥测数据收集以满足精确的可观测性要求,并确保将数据无缝集成到 InfluxDB 等系统中。

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,例如模板管理、动态索引命名以及与 OpenSearch 的集成。它还允许配置 Elasticsearch 节点的身份验证和运行状况监控。

配置

OpenTelemetry

[[inputs.opentelemetry]]
  ## Override the default (0.0.0.0:4317) destination OpenTelemetry gRPC service
  ## address:port
  # service_address = "0.0.0.0:4317"

  ## Override the default (5s) new connection timeout
  # timeout = "5s"

  ## gRPC Maximum Message Size
  # max_msg_size = "4MB"

  ## Override the default span attributes to be used as line protocol tags.
  ## These are always included as tags:
  ## - trace ID
  ## - span ID
  ## Common attributes can be found here:
  ## - https://github.com/open-telemetry/opentelemetry-collector/tree/main/semconv
  # span_dimensions = ["service.name", "span.name"]

  ## Override the default log record attributes to be used as line protocol tags.
  ## These are always included as tags, if available:
  ## - trace ID
  ## - span ID
  ## Common attributes can be found here:
  ## - https://github.com/open-telemetry/opentelemetry-collector/tree/main/semconv
  ## When using InfluxDB for both logs and traces, be certain that log_record_dimensions
  ## matches the span_dimensions value.
  # log_record_dimensions = ["service.name"]

  ## Override the default profile attributes to be used as line protocol tags.
  ## These are always included as tags, if available:
  ## - profile_id
  ## - address
  ## - sample
  ## - sample_name
  ## - sample_unit
  ## - sample_type
  ## - sample_type_unit
  ## Common attributes can be found here:
  ## - https://github.com/open-telemetry/opentelemetry-collector/tree/main/semconv
  # profile_dimensions = []

  ## Override the default (prometheus-v1) metrics schema.
  ## Supports: "prometheus-v1", "prometheus-v2"
  ## For more information about the alternatives, read the Prometheus input
  ## plugin notes.
  # metrics_schema = "prometheus-v1"

  ## Optional TLS Config.
  ## For advanced options: https://github.com/influxdata/telegraf/blob/v1.18.3/docs/TLS.md
  ##
  ## Set one or more allowed client CA certificate file names to
  ## enable mutually authenticated TLS connections.
  # tls_allowed_cacerts = ["/etc/telegraf/clientca.pem"]
  ## Add service certificate and key.
  # tls_cert = "/etc/telegraf/cert.pem"
  # tls_key = "/etc/telegraf/key.pem"

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

OpenTelemetry

  1. 跨服务统一监控:使用 OpenTelemetry 插件收集和整合来自 Kubernetes 环境中各种微服务的遥测数据。通过使用 OpenTelemetry 检测每个服务,您可以利用此插件实时收集应用程序性能和依赖关系的整体视图,从而更快地进行故障排除并提高复杂系统的可靠性。

  2. 通过跟踪增强调试:实施此插件以捕获流经多个服务的请求的端到端跟踪。例如,当用户发起一个触发多个后端服务的事务时,OpenTelemetry 插件可以记录详细的跟踪信息,突出显示性能瓶颈,从而为开发人员提供调试问题和优化代码所需的见解。

  3. 动态负载测试和性能监控:在负载测试阶段,通过在模拟的更高负载下收集实时指标和跟踪信息,来利用此插件的功能。这种方法有助于评估应用程序组件的弹性,并预先识别潜在的性能下降,从而确保在生产环境中获得流畅的用户体验。

  4. 集成日志记录和指标以进行实时监控:将 OpenTelemetry 插件与日志记录框架结合使用,以收集实时日志以及指标数据,从而创建一个强大的可观测性平台。例如,将其集成到 CI/CD 管道中以监控构建和部署,同时收集有助于实时诊断故障或性能问题的日志。

Elasticsearch

  1. 基于时间的索引:使用此插件将指标存储在 Elasticsearch 中,以根据收集时间对每个指标进行索引。例如,CPU 指标可以存储在名为 telegraf-2023.01.01 的每日索引中,从而可以轻松进行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 客户端保持功能正常并与较新的集群设置兼容。

反馈

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强大的性能,无限的扩展能力

收集、组织和处理海量高速数据。当您将任何数据视为时序数据时,它都更有价值。借助 InfluxDB,排名第一的时序平台,旨在与 Telegraf 一起扩展。

查看入门方法

相关集成

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Kafka 和 InfluxDB 集成

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Kinesis 和 InfluxDB 集成

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