Tail 和 Azure 数据资源管理器集成

[[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

[[outputs.azure_data_explorer]]
  ## The URI property of the Azure Data Explorer resource on Azure
  ## ex: endpoint_url = https://myadxresource.australiasoutheast.kusto.windows.net
  endpoint_url = ""

  ## The Azure Data Explorer database that the metrics will be ingested into.
  ## The plugin will NOT generate this database automatically, it's expected that this database already exists before ingestion.
  ## ex: "exampledatabase"
  database = ""

  ## Timeout for Azure Data Explorer operations
  # timeout = "20s"

  ## Type of metrics grouping used when pushing to Azure Data Explorer.
  ## Default is "TablePerMetric" for one table per different metric.
  ## For more information, please check the plugin README.
  # metrics_grouping_type = "TablePerMetric"

  ## Name of the single table to store all the metrics (Only needed if metrics_grouping_type is "SingleTable").
  # table_name = ""

  ## Creates tables and relevant mapping if set to true(default).
  ## Skips table and mapping creation if set to false, this is useful for running Telegraf with the lowest possible permissions i.e. table ingestor role.
  # create_tables = true

  ##  Ingestion method to use.
  ##  Available options are
  ##    - managed  --  streaming ingestion with fallback to batched ingestion or the "queued" method below
  ##    - queued   --  queue up metrics data and process sequentially
  # ingestion_type = "queued"