Tail 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 Tail 和 InfluxDB

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时序数据库
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序数据时,它都更有价值。InfluxDB 是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

Tail Telegraf 插件通过跟踪指定的日志文件来收集指标,实时捕获新的日志条目以进行进一步分析。

此插件使用参数化的 SQL INSERT 语句将 Telegraf 中的指标直接写入 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。

集成详情

Tail

tail 插件旨在持续监控和解析日志文件,使其成为实时日志分析和监控的理想选择。它模仿 Unix tail 命令的功能,允许用户指定文件或模式,并开始读取添加的新行。主要功能包括跟踪日志轮换文件、从文件末尾开始读取以及支持日志消息的各种解析格式。用户可以通过各种配置选项自定义插件,例如指定文件编码、监视文件更新的方法以及处理日志数据的过滤器设置。在日志数据对于监控应用程序性能和诊断问题至关重要的环境中,此插件尤其有价值。

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 SQL 兼容数据库(如 MariaDB)。该插件支持 MySQL 驱动程序,与 MariaDB 无缝集成,实现可靠的结构化指标存储。对于喜欢基于 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来说,此设置是理想之选。MariaDB 是 MySQL 的社区开发的、企业级的分支,它强调性能、安全性以及开放性。该插件支持将时序指标插入到自定义架构中,从而实现灵活的分析以及与使用 SQL 连接器的 BI 工具(如 Metabase 或 Grafana)的集成。

配置

Tail

[[inputs.tail]]
  ## File names or a pattern to tail.
  ## These accept standard unix glob matching rules, but with the addition of
  ## ** as a "super asterisk". ie:
  ##   "/var/log/**.log"  -> recursively find all .log files in /var/log
  ##   "/var/log/*/*.log" -> find all .log files with a parent dir in /var/log
  ##   "/var/log/apache.log" -> just tail the apache log file
  ##   "/var/log/log[!1-2]*  -> tail files without 1-2
  ##   "/var/log/log[^1-2]*  -> identical behavior as above
  ## See https://github.com/gobwas/glob for more examples
  ##
  files = ["/var/mymetrics.out"]

  ## Read file from beginning.
  # from_beginning = false

  ## Whether file is a named pipe
  # pipe = false

  ## Method used to watch for file updates.  Can be either "inotify" or "poll".
  ## inotify is supported on linux, *bsd, and macOS, while Windows requires
  ## using poll. Poll checks for changes every 250ms.
  # watch_method = "inotify"

  ## Maximum lines of the file to process that have not yet be written by the
  ## output.  For best throughput set based on the number of metrics on each
  ## line and the size of the output's metric_batch_size.
  # max_undelivered_lines = 1000

  ## Character encoding to use when interpreting the file contents.  Invalid
  ## characters are replaced using the unicode replacement character.  When set
  ## to the empty string the data is not decoded to text.
  ##   ex: character_encoding = "utf-8"
  ##       character_encoding = "utf-16le"
  ##       character_encoding = "utf-16be"
  ##       character_encoding = ""
  # character_encoding = ""

  ## 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"

  ## Set the tag that will contain the path of the tailed file. If you don't want this tag, set it to an empty string.
  # path_tag = "path"

  ## Filters to apply to files before generating metrics
  ## "ansi_color" removes ANSI colors
  # filters = []

  ## multiline parser/codec
  ## https://elastic.ac.cn/guide/en/logstash/2.4/plugins-filters-multiline.html
  #[inputs.tail.multiline]
    ## The pattern should be a regexp which matches what you believe to be an indicator that the field is part of an event consisting of multiple lines of log data.
    #pattern = "^\s"

    ## The field's value must be previous or next and indicates the relation to the
    ## multi-line event.
    #match_which_line = "previous"

    ## The invert_match can be true or false (defaults to false).
    ## If true, a message not matching the pattern will constitute a match of the multiline filter and the what will be applied. (vice-versa is also true)
    #invert_match = false

    ## The handling method for quoted text (defaults to 'ignore').
    ## The following methods are available:
    ##   ignore  -- do not consider quotation (default)
    ##   single-quotes -- consider text quoted by single quotes (')
    ##   double-quotes -- consider text quoted by double quotes (")
    ##   backticks     -- consider text quoted by backticks (`)
    ## When handling quotes, escaped quotes (e.g. \") are handled correctly.
    #quotation = "ignore"

    ## The preserve_newline option can be true or false (defaults to false).
    ## If true, the newline character is preserved for multiline elements,
    ## this is useful to preserve message-structure e.g. for logging outputs.
    #preserve_newline = false

    #After the specified timeout, this plugin sends the multiline event even if no new pattern is found to start a new event. The default is 5s.
    #timeout = 5s

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

Tail

  1. 实时服务器健康状况监控:实施 Tail 插件以实时解析 Web 服务器访问日志,从而立即了解用户活动、错误率和性能指标。通过可视化此日志数据,运营团队可以快速识别并响应流量或错误高峰,从而增强系统可靠性和用户体验。

  2. 集中式日志管理:利用 Tail 插件来聚合分布式系统中多个来源的日志。通过将每个服务配置为通过 Tail 插件将其日志发送到集中位置,团队可以简化日志分析,并确保从单个界面访问所有相关数据,从而简化故障排除流程。

  3. 安全事件检测:使用此插件来监控身份验证日志,以查找未经授权的访问尝试或可疑活动。通过设置针对特定日志消息的警报,团队可以利用此插件来增强安全态势并及时响应潜在的安全威胁,从而降低违规风险并提高整体系统完整性。

  4. 动态应用程序性能洞察:与分析工具集成,以创建基于日志数据展示应用程序性能指标的实时仪表板。此设置不仅可以帮助开发人员诊断瓶颈和效率低下问题,还可以实现主动的性能调整和资源分配,从而优化应用程序在不同负载下的行为。

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)。此设置允许将运营数据与业务 KPI 混合,以实现统一的仪表板,从而增强跨部门的可见性。

  2. 具有历史指标的合规性报告:使用此插件将指标记录到 MariaDB 中,以用于审计和合规性用例。关系模型支持使用带时间戳的条目精确查询过去的性能指标,从而支持法规文档编制。

  3. 基于 SQL 逻辑的自定义警报:将指标插入 MariaDB,并使用自定义 SQL 查询来定义警报阈值或条件。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警报工作流程。

  4. 物联网传感器指标存储:通过 Telegraf 从物联网设备收集传感器数据,并使用规范化架构将其存储在 MariaDB 中。此方法经济高效,并且可以与现有基于 SQL 的系统很好地集成,以进行实时或历史分析。

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。InfluxDB 是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

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,并允许基于这些消息创建指标。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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