StatsD 和 InfluxDB 集成

借助 InfluxData 构建的开源数据连接器 Telegraf,实现强大性能和轻松集成。

50 亿+

Telegraf 下载量

#1

时序数据库
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序数据时,它会更有价值。借助 InfluxDB,排名第一的时序平台,它旨在与 Telegraf 一起扩展。

查看入门方法

输入和输出集成概述

StatsD 输入插件通过在后台运行侦听器服务,从 StatsD 服务器捕获指标,从而实现全面的性能监控和指标聚合。

InfluxDB 插件将指标写入 InfluxDB HTTP 服务,从而可以高效地存储和检索时序数据。

集成详情

StatsD

StatsD 输入插件旨在通过在 Telegraf 处于活动状态时运行后台 StatsD 侦听器服务,从 StatsD 服务器收集指标。此插件利用原始 Etsy 实现建立的 StatsD 消息格式,该格式允许各种类型的指标,包括仪表、计数器、集合、计时、直方图和分布。StatsD 插件的功能扩展到解析标签,并使用包含 InfluxDB 标记系统的功能扩展标准协议。它可以处理通过不同协议(UDP 或 TCP)发送的消息,有效地管理多个指标,并提供高级配置以优化指标处理,例如百分位数计算和数据转换模板。这种灵活性使用户能够全面跟踪应用程序性能,使其成为强大监控设置的重要工具。

InfluxDB

InfluxDB Telegraf 插件用于将指标发送到 InfluxDB HTTP API,从而以结构化方式方便时序数据的存储和查询。此插件与 InfluxDB 无缝集成,提供诸如基于令牌的身份验证和对多个 InfluxDB 集群节点的支持等基本功能,从而确保可靠且可扩展的数据摄取。通过其可配置性,用户可以指定组织、目标存储桶和 HTTP 特定设置等选项,从而灵活地定制数据的发送和存储方式。该插件还支持敏感数据的机密管理,从而增强了生产环境中的安全性。此插件在现代可观测性堆栈中尤其有用,在这些堆栈中,实时分析和时序数据的存储至关重要。

配置

StatsD

[[inputs.statsd]]
  ## Protocol, must be "tcp", "udp4", "udp6" or "udp" (default=udp)
  protocol = "udp"

  ## MaxTCPConnection - applicable when protocol is set to tcp (default=250)
  max_tcp_connections = 250

  ## Enable TCP keep alive probes (default=false)
  tcp_keep_alive = false

  ## Specifies the keep-alive period for an active network connection.
  ## Only applies to TCP sockets and will be ignored if tcp_keep_alive is false.
  ## Defaults to the OS configuration.
  # tcp_keep_alive_period = "2h"

  ## Address and port to host UDP listener on
  service_address = ":8125"

  ## The following configuration options control when telegraf clears it's cache
  ## of previous values. If set to false, then telegraf will only clear it's
  ## cache when the daemon is restarted.
  ## Reset gauges every interval (default=true)
  delete_gauges = true
  ## Reset counters every interval (default=true)
  delete_counters = true
  ## Reset sets every interval (default=true)
  delete_sets = true
  ## Reset timings & histograms every interval (default=true)
  delete_timings = true

  ## Enable aggregation temporality adds temporality=delta or temporality=commulative tag, and
  ## start_time field, which adds the start time of the metric accumulation.
  ## You should use this when using OpenTelemetry output.
  # enable_aggregation_temporality = false

  ## Percentiles to calculate for timing & histogram stats.
  percentiles = [50.0, 90.0, 99.0, 99.9, 99.95, 100.0]

  ## separator to use between elements of a statsd metric
  metric_separator = "_"

  ## Parses tags in the datadog statsd format
  ## http://docs.datadoghq.com/guides/dogstatsd/
  ## deprecated in 1.10; use datadog_extensions option instead
  parse_data_dog_tags = false

  ## Parses extensions to statsd in the datadog statsd format
  ## currently supports metrics and datadog tags.
  ## http://docs.datadoghq.com/guides/dogstatsd/
  datadog_extensions = false

  ## Parses distributions metric as specified in the datadog statsd format
  ## https://docs.datadoghq.com/developers/metrics/types/?tab=distribution#definition
  datadog_distributions = false

  ## Keep or drop the container id as tag. Included as optional field
  ## in DogStatsD protocol v1.2 if source is running in Kubernetes
  ## https://docs.datadoghq.com/developers/dogstatsd/datagram_shell/?tab=metrics#dogstatsd-protocol-v12
  datadog_keep_container_tag = false

  ## Statsd data translation templates, more info can be read here:
  ## https://github.com/influxdata/telegraf/blob/master/docs/TEMPLATE_PATTERN.md
  # templates = [
  #     "cpu.* measurement*"
  # ]

  ## Number of UDP messages allowed to queue up, once filled,
  ## the statsd server will start dropping packets
  allowed_pending_messages = 10000

  ## Number of worker threads used to parse the incoming messages.
  # number_workers_threads = 5

  ## Number of timing/histogram values to track per-measurement in the
  ## calculation of percentiles. Raising this limit increases the accuracy
  ## of percentiles but also increases the memory usage and cpu time.
  percentile_limit = 1000

  ## Maximum socket buffer size in bytes, once the buffer fills up, metrics
  ## will start dropping.  Defaults to the OS default.
  # read_buffer_size = 65535

  ## Max duration (TTL) for each metric to stay cached/reported without being updated.
  # max_ttl = "10h"

  ## Sanitize name method
  ## By default, telegraf will pass names directly as they are received.
  ## However, upstream statsd now does sanitization of names which can be
  ## enabled by using the "upstream" method option. This option will a) replace
  ## white space with '_', replace '/' with '-', and remove characters not
  ## matching 'a-zA-Z_\-0-9\.;='.
  #sanitize_name_method = ""

  ## Replace dots (.) with underscore (_) and dashes (-) with
  ## double underscore (__) in metric names.
  # convert_names = false

  ## Convert all numeric counters to float
  ## Enabling this would ensure that both counters and guages are both emitted
  ## as floats.
  # float_counters = false

InfluxDB

[[outputs.influxdb]]
  ## The full HTTP or UDP URL for your InfluxDB instance.
  ##
  ## Multiple URLs can be specified for a single cluster, only ONE of the
  ## urls will be written to each interval.
  # urls = ["unix:///var/run/influxdb.sock"]
  # urls = ["udp://127.0.0.1:8089"]
  # urls = ["http://127.0.0.1:8086"]

  ## Local address to bind when connecting to the server
  ## If empty or not set, the local address is automatically chosen.
  # local_address = ""

  ## The target database for metrics; will be created as needed.
  ## For UDP url endpoint database needs to be configured on server side.
  # database = "telegraf"

  ## The value of this tag will be used to determine the database.  If this
  ## tag is not set the 'database' option is used as the default.
  # database_tag = ""

  ## If true, the 'database_tag' will not be included in the written metric.
  # exclude_database_tag = false

  ## If true, no CREATE DATABASE queries will be sent.  Set to true when using
  ## Telegraf with a user without permissions to create databases or when the
  ## database already exists.
  # skip_database_creation = false

  ## Name of existing retention policy to write to.  Empty string writes to
  ## the default retention policy.  Only takes effect when using HTTP.
  # retention_policy = ""

  ## The value of this tag will be used to determine the retention policy.  If this
  ## tag is not set the 'retention_policy' option is used as the default.
  # retention_policy_tag = ""

  ## If true, the 'retention_policy_tag' will not be included in the written metric.
  # exclude_retention_policy_tag = false

  ## Write consistency (clusters only), can be: "any", "one", "quorum", "all".
  ## Only takes effect when using HTTP.
  # write_consistency = "any"

  ## Timeout for HTTP messages.
  # timeout = "5s"

  ## HTTP Basic Auth
  # username = "telegraf"
  # password = "metricsmetricsmetricsmetrics"

  ## HTTP User-Agent
  # user_agent = "telegraf"

  ## UDP payload size is the maximum packet size to send.
  # udp_payload = "512B"

  ## Optional TLS Config for use on HTTP connections.
  # 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

  ## HTTP Proxy override, if unset values the standard proxy environment
  ## variables are consulted to determine which proxy, if any, should be used.
  # http_proxy = "http://corporate.proxy:3128"

  ## Additional HTTP headers
  # http_headers = {"X-Special-Header" = "Special-Value"}

  ## HTTP Content-Encoding for write request body, can be set to "gzip" to
  ## compress body or "identity" to apply no encoding.
  # content_encoding = "gzip"

  ## When true, Telegraf will output unsigned integers as unsigned values,
  ## i.e.: "42u".  You will need a version of InfluxDB supporting unsigned
  ## integer values.  Enabling this option will result in field type errors if
  ## existing data has been written.
  # influx_uint_support = false

  ## When true, Telegraf will omit the timestamp on data to allow InfluxDB
  ## to set the timestamp of the data during ingestion. This is generally NOT
  ## what you want as it can lead to data points captured at different times
  ## getting omitted due to similar data.
  # influx_omit_timestamp = false

输入和输出集成示例

StatsD

  1. 实时应用程序性能监控:利用 StatsD 输入插件实时监控应用程序性能指标。通过配置您的应用程序以将各种指标发送到 StatsD 服务器,团队可以利用此插件动态分析性能瓶颈、跟踪用户活动并确保资源优化。历史指标和实时指标的结合可以实现主动故障排除,并提高问题解决过程的响应速度。

  2. 跟踪 Web 应用程序中的用户参与度指标:使用 StatsD 插件收集用户参与度统计信息,例如页面浏览量、点击事件和交互时间。通过将这些指标发送到 StatsD 服务器,企业可以获得有关用户行为的宝贵见解,使他们能够根据定量反馈做出数据驱动的决策,以改善用户体验和界面设计。这可以显着提高营销策略和产品开发工作的有效性。

  3. 基础设施健康监控:部署 StatsD 插件以监控服务器基础设施的健康状况,方法是跟踪资源利用率、服务器响应时间和网络性能等指标。通过此设置,DevOps 团队可以详细了解系统性能,有效预测问题,防止问题升级。这使基础设施管理能够采取主动方法,最大限度地减少停机时间并确保最佳服务交付。

  4. 创建全面的服务仪表板:将 StatsD 与可视化工具集成,以创建全面的仪表板,反映整个架构中服务的状态和健康状况。例如,结合通过 StatsD 记录的来自多个服务的数据可以将原始指标转换为可操作的见解,从而展示系统性能随时间变化的趋势。此功能使利益干系人能够保持监督并根据可视化数据集推动决策,从而提高整体运营透明度。

InfluxDB

  1. 实时系统监控:利用 InfluxDB 插件捕获和存储来自一系列系统组件(例如 CPU 使用率、内存消耗和磁盘 I/O)的指标。通过将这些指标推送到 InfluxDB 中,您可以创建一个实时仪表板,以实时可视化系统性能。此设置不仅有助于识别性能瓶颈,还有助于通过分析随时间变化的趋势来进行主动容量规划。

  2. Web 应用程序的性能跟踪:自动收集与 Web 应用程序性能相关的指标(例如请求持续时间、错误率和用户交互)并将它们推送到 InfluxDB。通过在您的监控堆栈中使用此插件,您可以使用存储的指标来生成报告和分析,这些报告和分析有助于了解用户行为和应用程序效率,从而指导开发和优化工作。

  3. 物联网数据聚合:利用 InfluxDB Telegraf 插件从各种物联网设备收集传感器数据,并将其存储在集中的 InfluxDB 实例中。此用例使您能够分析环境或机器数据随时间变化的趋势和模式,从而促进更明智的决策和预测性维护策略。通过将物联网数据集成到 InfluxDB 中,组织可以利用历史数据分析的力量来推动创新和运营效率。

  4. 分析历史指标以进行预测:设置 InfluxDB 插件以将历史指标数据发送到 InfluxDB,并使用它来驱动预测模型。通过分析过去的性能指标,您可以创建预测未来趋势和需求的预测模型。此应用程序对于商业智能目的特别有用,有助于组织根据历史使用模式为资源需求的波动做好准备。

反馈

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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序数据时,它会更有价值。借助 InfluxDB,排名第一的时序平台,它旨在与 Telegraf 一起扩展。

查看入门方法

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