AMQP 和 MariaDB 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AMQP 和 InfluxDB

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时间序列数据库
来源:DB Engines

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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,它都会更有价值。借助 InfluxDB,排名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

AMQP Consumer 输入插件允许您从兼容 AMQP 0-9-1 的消息代理(如 RabbitMQ)中摄取数据,从而实现无缝的数据收集,以进行监控和分析。

此插件使用参数化的 SQL INSERT 语句将指标从 Telegraf 直接写入 MariaDB,从而提供了一种灵活的方式将指标存储在结构化的关系表中。

集成详细信息

AMQP

此插件为 AMQP 0-9-1 提供了一个消费者,RabbitMQ 是其一个突出的实现。AMQP 或高级消息队列协议最初是为了在网络中各种系统之间实现可靠的、可互操作的消息传递而开发的。该插件使用配置的队列和绑定键从主题交换中读取指标,从而提供了一种灵活高效的方式来从兼容 AMQP 的消息传递系统中收集数据。这使用户能够利用现有的 RabbitMQ 实施来有效地监控他们的应用程序,通过捕获详细的指标以进行分析和告警。

MariaDB

Telegraf 中的 SQL 输出插件通过执行参数化的 SQL 语句,能够将指标直接写入兼容 SQL 的数据库(如 MariaDB)。通过支持 MySQL 驱动程序,该插件与 MariaDB 无缝集成,以实现可靠的、结构化的指标存储。此设置非常适合喜欢基于 SQL 的分析或希望将指标与业务数据一起存储以进行统一查询的用户。MariaDB 是一个社区开发的、企业级的 MySQL 分支,强调性能、安全性和开放性。该插件支持将时间序列指标插入到自定义模式中,从而实现灵活的分析,并与使用 SQL 连接器的 BI 工具(如 Metabase 或 Grafana)集成。

配置

AMQP

[[inputs.amqp_consumer]]
  ## Brokers to consume from.  If multiple brokers are specified a random broker
  ## will be selected anytime a connection is established.  This can be
  ## helpful for load balancing when not using a dedicated load balancer.
  brokers = ["amqp://localhost:5672/influxdb"]

  ## Authentication credentials for the PLAIN auth_method.
  # username = ""
  # password = ""

  ## Name of the exchange to declare.  If unset, no exchange will be declared.
  exchange = "telegraf"

  ## Exchange type; common types are "direct", "fanout", "topic", "header", "x-consistent-hash".
  # exchange_type = "topic"

  ## If true, exchange will be passively declared.
  # exchange_passive = false

  ## Exchange durability can be either "transient" or "durable".
  # exchange_durability = "durable"

  ## Additional exchange arguments.
  # exchange_arguments = { }
  # exchange_arguments = {"hash_property" = "timestamp"}

  ## AMQP queue name.
  queue = "telegraf"

  ## AMQP queue durability can be "transient" or "durable".
  queue_durability = "durable"

  ## If true, queue will be passively declared.
  # queue_passive = false

  ## Additional arguments when consuming from Queue
  # queue_consume_arguments = { }
  # queue_consume_arguments = {"x-stream-offset" = "first"}

  ## A binding between the exchange and queue using this binding key is
  ## created.  If unset, no binding is created.
  binding_key = "#"

  ## Maximum number of messages server should give to the worker.
  # prefetch_count = 50

  ## Max undelivered messages
  ## This plugin uses tracking metrics, which ensure messages are read to
  ## outputs before acknowledging them to the original broker to ensure data
  ## is not lost. This option sets the maximum messages to read from the
  ## broker that have not been written by an output.
  ##
  ## This value needs to be picked with awareness of the agent's
  ## metric_batch_size value as well. Setting max undelivered messages too high
  ## can result in a constant stream of data batches to the output. While
  ## setting it too low may never flush the broker's messages.
  # max_undelivered_messages = 1000

  ## Timeout for establishing the connection to a broker
  # timeout = "30s"

  ## Auth method. PLAIN and EXTERNAL are supported
  ## Using EXTERNAL requires enabling the rabbitmq_auth_mechanism_ssl plugin as
  ## described here: https://rabbitmq.cn/plugins.html
  # auth_method = "PLAIN"

  ## 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

  ## Content encoding for message payloads, can be set to
  ## "gzip", "identity" or "auto"
  ## - Use "gzip" to decode gzip
  ## - Use "identity" to apply no encoding
  ## - Use "auto" determine the encoding using the ContentEncoding header
  # content_encoding = "identity"

  ## Maximum size of decoded message.
  ## Acceptable units are B, KiB, KB, MiB, MB...
  ## Without quotes and units, interpreted as size in bytes.
  # max_decompression_size = "500MB"

  ## 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"

MariaDB

[[outputs.sql]]
  ## Database driver
  ## Valid options: mssql (Microsoft SQL Server), mysql (MySQL), pgx (Postgres),
  ##  sqlite (SQLite3), snowflake (snowflake.com) clickhouse (ClickHouse)
  driver = "mysql"

  ## Data source name
  ## The format of the data source name is different for each database driver.
  ## See the plugin readme for details.
  data_source_name = "username:password@tcp(host:port)/dbname"

  ## Timestamp column name
  timestamp_column = "timestamp"

  ## Table creation template
  ## Available template variables:
  ##  {TABLE} - table name as a quoted identifier
  ##  {TABLELITERAL} - table name as a quoted string literal
  ##  {COLUMNS} - column definitions (list of quoted identifiers and types)
  table_template = "CREATE TABLE {TABLE}({COLUMNS})"

  ## SQL INSERT statement with placeholders. Telegraf will substitute values at runtime.
  ## table_template = "INSERT INTO metrics (timestamp, name, value, tags) VALUES (?, ?, ?, ?)"

  ## Table existence check template
  ## Available template variables:
  ##  {TABLE} - tablename as a quoted identifier
  table_exists_template = "SELECT 1 FROM {TABLE} LIMIT 1"

  ## Initialization SQL
  init_sql = "SET sql_mode='ANSI_QUOTES';"

  ## Maximum amount of time a connection may be idle. "0s" means connections are
  ## never closed due to idle time.
  connection_max_idle_time = "0s"

  ## Maximum amount of time a connection may be reused. "0s" means connections
  ## are never closed due to age.
  connection_max_lifetime = "0s"

  ## Maximum number of connections in the idle connection pool. 0 means unlimited.
  connection_max_idle = 2

  ## Maximum number of open connections to the database. 0 means unlimited.
  connection_max_open = 0

  ## NOTE: Due to the way TOML is parsed, tables must be at the END of the
  ## plugin definition, otherwise additional config options are read as part of the
  ## table

  ## Metric type to SQL type conversion
  ## The values on the left are the data types Telegraf has and the values on
  ## the right are the data types Telegraf will use when sending to a database.
  ##
  ## The database values used must be data types the destination database
  ## understands. It is up to the user to ensure that the selected data type is
  ## available in the database they are using. Refer to your database
  ## documentation for what data types are available and supported.
  #[outputs.sql.convert]
  #  integer              = "INT"
  #  real                 = "DOUBLE"
  #  text                 = "TEXT"
  #  timestamp            = "TIMESTAMP"
  #  defaultvalue         = "TEXT"
  #  unsigned             = "UNSIGNED"
  #  bool                 = "BOOL"
  #  ## This setting controls the behavior of the unsigned value. By default the
  #  ## setting will take the integer value and append the unsigned value to it. The other
  #  ## option is "literal", which will use the actual value the user provides to
  #  ## the unsigned option. This is useful for a database like ClickHouse where
  #  ## the unsigned value should use a value like "uint64".
  #  # conversion_style = "unsigned_suffix"

输入和输出集成示例

AMQP

  1. 集成应用程序指标与 AMQP:使用 AMQP Consumer 插件收集发布到 RabbitMQ 交换机的应用程序指标。通过配置插件以监听特定的队列,团队可以深入了解应用程序性能、跟踪请求率、错误计数和延迟指标,所有这些都是实时的。这种设置不仅有助于异常检测,还为容量规划和系统优化提供了有价值的数据。

  2. 事件驱动的监控:配置 AMQP Consumer 以在应用程序中满足某些条件时触发特定的监控事件。例如,如果收到指示高错误率的消息,插件可以将此数据馈送到监控工具中,生成警报或扩展事件。这种集成可以提高对问题的响应速度,并自动化部分操作工作流程。

  3. 跨平台数据聚合:利用 AMQP Consumer 插件来整合来自分布在不同平台上的各种应用程序的指标。通过使用 RabbitMQ 作为集中式消息代理,组织可以统一他们的监控数据,从而允许通过 Telegraf 进行全面的分析和仪表板展示,从而在异构环境中保持可见性。

  4. 实时日志处理:扩展 AMQP Consumer 的使用以捕获发送到 RabbitMQ 交换机的日志数据,实时处理日志以进行监控和告警。此应用程序确保通过分析日志模式、趋势和异常(在它们发生时)来快速检测和解决操作问题。

MariaDB

  1. 商业智能集成:将应用程序性能指标直接存储到 MariaDB 中,并将其连接到 BI 工具(如 Metabase 或 Apache Superset)。这种设置允许将操作数据与业务 KPI 混合,以实现统一的仪表板,从而提高跨部门的可见性。

  2. 用于合规性报告的历史指标:使用此插件将指标记录到 MariaDB 中,用于审计和合规性用例。关系模型支持使用时间戳条目精确查询过去的绩效指标,从而支持监管文档。

  3. 基于 SQL 逻辑的自定义告警:将指标插入到 MariaDB 中,并使用自定义 SQL 查询来定义告警阈值或条件。与 cron 作业或计划脚本结合使用,这可以实现传统指标平台无法实现的高级告警工作流程。

  4. 物联网传感器指标存储:通过 Telegraf 收集来自物联网设备的传感器数据,并使用规范化的模式将其存储在 MariaDB 中。这种方法具有成本效益,并且与现有的基于 SQL 的系统集成良好,以进行实时或历史分析。

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了任何错误,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,它都会更有价值。借助 InfluxDB,排名第一的时间序列平台,旨在与 Telegraf 一起扩展。

查看入门方法

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