Apache Zookeeper 和 Azure Data Explorer 集成

[[inputs.zookeeper]]
  ## An array of address to gather stats about. Specify an ip or hostname
  ## with port. ie localhost:2181, 10.0.0.1:2181, etc.

  ## If no servers are specified, then localhost is used as the host.
  ## If no port is specified, 2181 is used
  servers = [":2181"]

  ## Timeout for metric collections from all servers. Minimum timeout is "1s".
  # timeout = "5s"

  ## Float Parsing - the initial implementation forced any value unable to be
  ## parsed as an int to be a string. Setting this to "float" will attempt to
  ## parse float values as floats and not strings. This would break existing
  ## metrics and may cause issues if a value switches between a float and int.
  # parse_floats = "string"

  ## Optional TLS Config
  # enable_tls = false
  # tls_ca = "/etc/telegraf/ca.pem"
  # tls_cert = "/etc/telegraf/cert.pem"
  # tls_key = "/etc/telegraf/key.pem"
  ## If false, skip chain & host verification
  # insecure_skip_verify = true

[[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"