Azure 监控和 Elasticsearch 集成

强大的性能,轻松集成,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 Azure Monitor 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

强大的性能,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,第一名的时间序列平台,旨在与 Telegraf 一起扩展。

查看入门方法

输入和输出集成概述

使用 Azure Monitor API 从 Azure 资源收集指标。

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

Azure 监控

Azure Monitor Telegraf 插件专门用于使用 Azure Monitor API 从各种 Azure 资源收集指标。 用户必须提供特定的凭据,例如 client_idclient_secrettenant_idsubscription_id,才能进行身份验证并访问其 Azure 资源。 此外,该插件还支持从单个资源以及资源组或订阅中收集指标的功能,从而可以根据用户需求灵活且可扩展地收集指标。 此插件非常适合利用 Azure 云基础设施的组织,可深入了解资源在一段时间内的性能和利用率,从而促进云资源的积极管理和优化。

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。 它还允许配置 Elasticsearch 节点的身份验证和运行状况监控。

配置

Azure 监控

# Gather Azure resources metrics from Azure Monitor API
[[inputs.azure_monitor]]
  # can be found under Overview->Essentials in the Azure portal for your application/service
  subscription_id = "<>"
  # can be obtained by registering an application under Azure Active Directory
  client_id = "<>"
  # can be obtained by registering an application under Azure Active Directory.
  # If not specified Default Azure Credentials chain will be attempted:
  # - Environment credentials (AZURE_*)
  # - Workload Identity in Kubernetes cluster
  # - Managed Identity
  # - Azure CLI auth
  # - Developer Azure CLI auth
  client_secret = "<>"
  # can be found under Azure Active Directory->Properties
  tenant_id = "<>"
  # Define the optional Azure cloud option e.g. AzureChina, AzureGovernment or AzurePublic. The default is AzurePublic.
  # cloud_option = "AzurePublic"

  # resource target #1 to collect metrics from
  [[inputs.azure_monitor.resource_target]]
    # can be found under Overview->Essentials->JSON View in the Azure portal for your application/service
    # must start with 'resourceGroups/...' ('/subscriptions/xxxxxxxx-xxxx-xxxx-xxx-xxxxxxxxxxxx'
    # must be removed from the beginning of Resource ID property value)
    resource_id = "<>"
    # the metric names to collect
    # leave the array empty to use all metrics available to this resource
    metrics = [ "<>", "<>" ]
    # metrics aggregation type value to collect
    # can be 'Total', 'Count', 'Average', 'Minimum', 'Maximum'
    # leave the array empty to collect all aggregation types values for each metric
    aggregations = [ "<>", "<>" ]

  # resource target #2 to collect metrics from
  [[inputs.azure_monitor.resource_target]]
    resource_id = "<>"
    metrics = [ "<>", "<>" ]
    aggregations = [ "<>", "<>" ]

  # resource group target #1 to collect metrics from resources under it with resource type
  [[inputs.azure_monitor.resource_group_target]]
    # the resource group name
    resource_group = "<>"

    # defines the resources to collect metrics from
    [[inputs.azure_monitor.resource_group_target.resource]]
      # the resource type
      resource_type = "<>"
      metrics = [ "<>", "<>" ]
      aggregations = [ "<>", "<>" ]

    # defines the resources to collect metrics from
    [[inputs.azure_monitor.resource_group_target.resource]]
      resource_type = "<>"
      metrics = [ "<>", "<>" ]
      aggregations = [ "<>", "<>" ]

  # resource group target #2 to collect metrics from resources under it with resource type
  [[inputs.azure_monitor.resource_group_target]]
    resource_group = "<>"

    [[inputs.azure_monitor.resource_group_target.resource]]
      resource_type = "<>"
      metrics = [ "<>", "<>" ]
      aggregations = [ "<>", "<>" ]

  # subscription target #1 to collect metrics from resources under it with resource type
  [[inputs.azure_monitor.subscription_target]]
    resource_type = "<>"
    metrics = [ "<>", "<>" ]
    aggregations = [ "<>", "<>" ]

  # subscription target #2 to collect metrics from resources under it with resource type
  [[inputs.azure_monitor.subscription_target]]
    resource_type = "<>"
    metrics = [ "<>", "<>" ]
    aggregations = [ "<>", "<>" ]
</code></pre>

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

Azure 监控

  1. 动态资源监控:使用 Azure Monitor 插件根据特定条件(如标签或资源类型)动态收集 Azure 资源的指标。 组织可以自动化加载和卸载资源指标的过程,从而根据资源利用率模式更好地跟踪和优化性能。

  2. 多云监控集成:将从 Azure Monitor 收集的指标与其他云提供商集成,使用集中式监控解决方案。 这使组织可以查看和分析跨多个云部署的性能数据,从而全面了解资源性能和成本,并简化运营。

  3. 异常检测和警报:结合机器学习算法,利用通过 Azure Monitor 插件收集的指标来检测资源利用率中的异常。 通过建立基线性能指标并自动发出偏差警报,组织可以在风险升级和性能问题升级之前缓解风险并解决性能问题。

  4. 历史性能分析:通过将收集到的 Azure 指标馈送到数据仓库解决方案中,使用这些指标进行历史分析。 这使组织能够跟踪一段时间内的趋势,从而可以根据历史性能数据进行详细的报告和决策。

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量身定制的自定义模板。 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:如果您使用的是 AWS OpenSearch,则可以通过激活兼容模式来配置此插件以实现无缝协作,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

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。

强大的性能,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,第一名的时间序列平台,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,并提供带有 DynamoDB 的检查点功能,以实现可靠的消息处理。

查看集成