HTTP 和 TimescaleDB 集成

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

info

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

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时间序列数据库
来源:DB Engines

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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间序列数据时,它都更有价值。借助 InfluxDB,排名第一的时间序列平台,专为与 Telegraf 一起扩展而构建。

查看入门方法

输入和输出集成概述

HTTP 插件允许从指定的 HTTP 端点收集指标,处理各种数据格式和身份验证方法。

此输出插件为将 Telegraf 收集的指标直接路由到 TimescaleDB 提供了可靠高效的机制。通过利用 PostgreSQL 强大的生态系统以及 TimescaleDB 的时间序列优化,它支持高性能数据摄取和高级查询功能。

集成详情

HTTP

HTTP 插件从一个或多个 HTTP(S) 端点收集指标,这些端点应具有以支持的输入数据格式之一格式化的指标。它还支持来自密钥存储的密钥,用于各种身份验证选项,并包括全局支持的配置设置。

TimescaleDB

TimescaleDB 是一个开源时间序列数据库,构建为 PostgreSQL 的扩展,旨在高效处理大规模、面向时间的数据。TimescaleDB 于 2017 年推出,是为了响应对强大、可扩展的解决方案日益增长的需求而出现的,该解决方案可以管理海量数据,同时具有高插入率和复杂查询。通过利用 PostgreSQL 熟悉的 SQL 接口并通过专门的时间序列功能对其进行增强,TimescaleDB 在希望将时间序列功能集成到现有关系数据库中的开发人员中迅速普及。它的混合方法使用户可以受益于 PostgreSQL 的灵活性、可靠性和生态系统,同时为时间序列数据提供优化的性能。

该数据库在需要快速摄取数据点并结合对历史时期进行复杂分析查询的环境中尤其有效。TimescaleDB 具有许多创新功能,例如将数据透明地分区为可管理块的超表和内置的连续聚合。这些功能可以显着提高查询速度和资源效率。

配置

HTTP

[[inputs.http]]
  ## One or more URLs from which to read formatted metrics.
  urls = [
    "http://localhost/metrics",
    "http+unix:///run/user/420/podman/podman.sock:/d/v4.0.0/libpod/pods/json"
  ]

  ## HTTP method
  # method = "GET"

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

  ## HTTP entity-body to send with POST/PUT requests.
  # body = ""

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

  ## Optional Bearer token settings to use for the API calls.
  ## Use either the token itself or the token file if you need a token.
  # token = "eyJhbGc...Qssw5c"
  # token_file = "/path/to/file"

  ## Optional HTTP Basic Auth Credentials
  # username = "username"
  # password = "pa$$word"

  ## OAuth2 Client Credentials. The options 'client_id', 'client_secret', and 'token_url' are required to use OAuth2.
  # client_id = "clientid"
  # client_secret = "secret"
  # token_url = "https://indentityprovider/oauth2/v1/token"
  # scopes = ["urn:opc:idm:__myscopes__"]

  ## HTTP Proxy support
  # use_system_proxy = false
  # http_proxy_url = ""

  ## Optional TLS Config
  ## Set to true/false to enforce TLS being enabled/disabled. If not set,
  ## enable TLS only if any of the other options are specified.
  # tls_enable =
  ## Trusted root certificates for server
  # tls_ca = "/path/to/cafile"
  ## Used for TLS client certificate authentication
  # tls_cert = "/path/to/certfile"
  ## Used for TLS client certificate authentication
  # tls_key = "/path/to/keyfile"
  ## Password for the key file if it is encrypted
  # tls_key_pwd = ""
  ## Send the specified TLS server name via SNI
  # tls_server_name = "kubernetes.example.com"
  ## Minimal TLS version to accept by the client
  # tls_min_version = "TLS12"
  ## List of ciphers to accept, by default all secure ciphers will be accepted
  ## See https://pkg.go.dev/crypto/tls#pkg-constants for supported values.
  ## Use "all", "secure" and "insecure" to add all support ciphers, secure
  ## suites or insecure suites respectively.
  # tls_cipher_suites = ["secure"]
  ## Renegotiation method, "never", "once" or "freely"
  # tls_renegotiation_method = "never"
  ## Use TLS but skip chain & host verification
  # insecure_skip_verify = false

  ## Optional Cookie authentication
  # cookie_auth_url = "https://localhost/authMe"
  # cookie_auth_method = "POST"
  # cookie_auth_username = "username"
  # cookie_auth_password = "pa$$word"
  # cookie_auth_headers = { Content-Type = "application/json", X-MY-HEADER = "hello" }
  # cookie_auth_body = '{"username": "user", "password": "pa$$word", "authenticate": "me"}'
  ## cookie_auth_renewal not set or set to "0" will auth once and never renew the cookie
  # cookie_auth_renewal = "5m"

  ## Amount of time allowed to complete the HTTP request
  # timeout = "5s"

  ## List of success status codes
  # success_status_codes = [200]

  ## Data format to consume.
  ## Each data format has its own unique set of configuration options, read
  ## more about them here:
  ## https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md
  # data_format = "influx"

TimescaleDB

# Publishes metrics to a TimescaleDB database
[[outputs.postgresql]]
  ## Specify connection address via the standard libpq connection string:
  ##   host=... user=... password=... sslmode=... dbname=...
  ## Or a URL:
  ##   postgres://[user[:password]]@localhost[/dbname]?sslmode=[disable|verify-ca|verify-full]
  ## See https://postgresql.ac.cn/docs/current/libpq-connect.html#LIBPQ-CONNSTRING
  ##
  ## All connection parameters are optional. Environment vars are also supported.
  ## e.g. PGPASSWORD, PGHOST, PGUSER, PGDATABASE
  ## All supported vars can be found here:
  ##  https://postgresql.ac.cn/docs/current/libpq-envars.html
  ##
  ## Non-standard parameters:
  ##   pool_max_conns (default: 1) - Maximum size of connection pool for parallel (per-batch per-table) inserts.
  ##   pool_min_conns (default: 0) - Minimum size of connection pool.
  ##   pool_max_conn_lifetime (default: 0s) - Maximum connection age before closing.
  ##   pool_max_conn_idle_time (default: 0s) - Maximum idle time of a connection before closing.
  ##   pool_health_check_period (default: 0s) - Duration between health checks on idle connections.
  # connection = ""

  ## Postgres schema to use.
  # schema = "public"

  ## Store tags as foreign keys in the metrics table. Default is false.
  # tags_as_foreign_keys = false

  ## Suffix to append to table name (measurement name) for the foreign tag table.
  # tag_table_suffix = "_tag"

  ## Deny inserting metrics if the foreign tag can't be inserted.
  # foreign_tag_constraint = false

  ## Store all tags as a JSONB object in a single 'tags' column.
  # tags_as_jsonb = false

  ## Store all fields as a JSONB object in a single 'fields' column.
  # fields_as_jsonb = false

  ## Name of the timestamp column
  ## NOTE: Some tools (e.g. Grafana) require the default name so be careful!
  # timestamp_column_name = "time"

  ## Type of the timestamp column
  ## Currently, "timestamp without time zone" and "timestamp with time zone"
  ## are supported
  # timestamp_column_type = "timestamp without time zone"

  ## Templated statements to execute when creating a new table.
  # create_templates = [
  #   '''CREATE TABLE {{ .table }} ({{ .columns }})''',
  # ]

  ## Templated statements to execute when adding columns to a table.
  ## Set to an empty list to disable. Points containing tags for which there is
  ## no column will be skipped. Points containing fields for which there is no
  ## column will have the field omitted.
  # add_column_templates = [
  #   '''ALTER TABLE {{ .table }} ADD COLUMN IF NOT EXISTS {{ .columns|join ", ADD COLUMN IF NOT EXISTS " }}''',
  # ]

  ## Templated statements to execute when creating a new tag table.
  # tag_table_create_templates = [
  #   '''CREATE TABLE {{ .table }} ({{ .columns }}, PRIMARY KEY (tag_id))''',
  # ]

  ## Templated statements to execute when adding columns to a tag table.
  ## Set to an empty list to disable. Points containing tags for which there is
  ## no column will be skipped.
  # tag_table_add_column_templates = [
  #   '''ALTER TABLE {{ .table }} ADD COLUMN IF NOT EXISTS {{ .columns|join ", ADD COLUMN IF NOT EXISTS " }}''',
  # ]

  ## The postgres data type to use for storing unsigned 64-bit integer values
  ## (Postgres does not have a native unsigned 64-bit integer type).
  ## The value can be one of:
  ##   numeric - Uses the PostgreSQL "numeric" data type.
  ##   uint8 - Requires pguint extension (https://github.com/petere/pguint)
  # uint64_type = "numeric"

  ## When using pool_max_conns > 1, and a temporary error occurs, the query is
  ## retried with an incremental backoff. This controls the maximum duration.
  # retry_max_backoff = "15s"

  ## Approximate number of tag IDs to store in in-memory cache (when using
  ## tags_as_foreign_keys). This is an optimization to skip inserting known
  ## tag IDs. Each entry consumes approximately 34 bytes of memory.
  # tag_cache_size = 100000

  ## Cut column names at the given length to not exceed PostgreSQL's
  ## 'identifier length' limit (default: no limit)
  ## (see https://postgresql.ac.cn/docs/current/limits.html)
  ## Be careful to not create duplicate column names!
  # column_name_length_limit = 0

  ## Enable & set the log level for the Postgres driver.
  # log_level = "warn" # trace, debug, info, warn, error, none

输入和输出集成示例

HTTP

  1. 从本地主机收集指标: 该插件可以从 HTTP 端点(如 http://localhost/metrics)获取指标,从而实现简单的本地监控。
  2. 使用 Unix 域套接字: 您可以使用 http+unix 方案指定从 Unix 域套接字上的服务收集指标,例如 http+unix:///path/to/service.sock:/api/endpoint

TimescaleDB

  1. 实时物联网数据摄取:使用该插件实时收集和存储来自数千个物联网设备的传感器数据。此设置有助于即时分析,帮助组织监控运营效率并快速响应不断变化的情况。

  2. 云应用程序性能监控:利用该插件将来自分布式云应用程序的详细性能指标馈送到 TimescaleDB。这种集成支持实时仪表板和警报,使团队能够快速识别和缓解性能瓶颈。

  3. 历史数据分析和报告:实施一个系统,将长期指标存储在 TimescaleDB 中,以进行全面的历史分析。这种方法使企业能够执行趋势分析、生成详细报告,并根据存档的时间序列数据做出数据驱动的决策。

  4. 自适应警报和异常检测:将该插件与自动化异常检测工作流程集成。通过不断将指标流式传输到 TimescaleDB,机器学习模型可以分析数据模式,并在发生异常时触发警报,从而提高系统可靠性和主动维护能力。

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间序列数据时,它都更有价值。借助 InfluxDB,排名第一的时间序列平台,专为与 Telegraf 一起扩展而构建。

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。

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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。

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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。

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