Tail 和 SQLite 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。为了获得查询和压缩优化、高速摄取和高可用性,您可能需要考虑 Tail 和 InfluxDB

50 亿+

Telegraf 下载量

#1

时间序列数据库
来源:DB Engines

10 亿+

InfluxDB 下载量

2,800+

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,它都会更有价值。借助 InfluxDB,这个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

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。

Telegraf 的 SQL 输出插件通过为每种指标类型动态创建表,将指标存储在 SQL 数据库中。当配置为 SQLite 时,它使用基于文件的 DSN 和为轻量级嵌入式数据库使用量身定制的最小 SQL 模式。

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,并在添加新行时开始读取。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。此插件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尤其有价值。

SQLite

SQL 输出插件使用动态模式将 Telegraf 指标写入 SQL 数据库,其中每种指标类型对应一个表。对于 SQLite,该插件使用 modernc.org/sqlite 驱动程序,并且需要 DSN 采用文件 URI 格式(例如,“file:/path/to/telegraf.db?cache=shared”)。此配置利用标准 ANSI SQL 进行表创建和数据插入,确保与 SQLite 的功能兼容。

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

SQLite

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

  ## Data source name
  ## For SQLite, the DSN is a filename or URL with the scheme "file:".
  ## Example: "file:/path/to/telegraf.db?cache=shared"
  data_source_name = "file:/path/to/telegraf.db?cache=shared"

  ## 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})"

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

  ## Initialization SQL (optional)
  init_sql = ""

  ## 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

  ## 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 SQL types used when writing to SQLite.
  #[outputs.sql.convert]
  #  integer       = "INT"
  #  real          = "DOUBLE"
  #  text          = "TEXT"
  #  timestamp     = "TIMESTAMP"
  #  defaultvalue  = "TEXT"
  #  unsigned      = "UNSIGNED"
  #  bool          = "BOOL"

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和响应流量或错误峰值,从而提高系统可靠性和用户体验。

  2. 集中式日志管理:利用 Tail 插件聚合分布式系统中多个来源的日志。通过配置每个服务以通过 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。通过设置针对某些日志消息的警报,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实时仪表板,这些仪表板根据日志数据展示应用程序性能指标。此设置不仅可以帮助开发人员诊断瓶颈和效率低下问题,还可以进行主动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。

SQLite

  1. 本地监控存储:配置插件以将指标写入本地 SQLite 数据库文件。这非常适合不需要设置全规模数据库服务器的轻量级部署。
  2. 嵌入式应用程序:将 SQLite 用作边缘设备中嵌入式应用程序的后端,受益于其基于文件的架构和最小的资源需求。
  3. 快速设置以进行测试:利用 SQLite 的易用性,快速设置 Telegraf 指标收集的测试环境,而无需外部数据库服务。
  4. 自定义模式管理:如果您需要特定的列类型或索引,请调整表创建模板以预定义您的模式,从而确保与您的应用程序需求兼容。

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,这个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

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。

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,并提供使用 DynamoDB 的检查点功能,以实现可靠的消息处理。

查看集成