StatsD

Metrics data collected by the DDTrace Agent will be sent to port 8125 of DK using the StatsD data type. This includes CPU, memory, thread, and class loading information from the JVM runtime, as well as various JMX metrics that are enabled, such as Kafka, Tomcat, RabbitMQ, etc.

Configuration¶

Prerequisites¶

When running DDTrace as an agent, users do not need to specifically open the JMX port; if the port is not opened, the agent will randomly open a local port.

DDTrace collects JVM information by default. By default, it sends data to localhost:8125.

If you are in a k8s environment, you need to configure the StatsD host and port:

DD_JMXFETCH_STATSD_HOST=datakit_url
DD_JMXFETCH_STATSD_PORT=8125

You can enable specific collectors using dd.jmxfetch.<INTEGRATION_NAME>.enabled=true.

Before filling in INTEGRATION_NAME, you can first check the default supported third-party software

For example, Tomcat or Kafka:

-Ddd.jmxfetch.tomcat.enabled=true
# or
-Ddd.jmxfetch.kafka.enabled=true

Collector Configuration¶

Host InstallationKubernetes

Navigate to the conf.d/statsd directory under the DataKit installation directory, copy statsd.conf.sample and rename it to statsd.conf. An example is shown below:

[[inputs.statsd]]
  ## Collector alias.
  # source = "statsd/-/-"

  ## Collection interval, default is 10 seconds. (optional)
  # interval = '10s'

  protocol = "udp"

  ## Address and port for hosting the UDP listener
  service_address = ":8125"

  ## Tag request metric. Used to distinguish feed metric names.
  ## e.g., DD_TAGS=source_key:tomcat,host_key:cn-shanghai-sq5ei
  ## e.g., -Ddd.tags=source_key:tomcat,host_key:cn-shanghai-sq5ei
  # statsd_source_key = "source_key"
  # statsd_host_key   = "host_key"
  ## Indicate whether to report tags statsd_source_key and statsd_host_key.
  # save_above_key    = false

  delete_gauges = true
  delete_counters = true
  delete_sets = true
  delete_timings = true

  ## Counter metrics are float in the new DataKit version, set true if you want them to be int.
  # set_counter_int = false

  ## Percentiles to calculate for timing & histogram stats
  percentiles = [50.0, 90.0, 99.0, 99.9, 99.95, 100.0]

  ## Separator to use between elements of a StatsD metric
  metric_separator = "_"

  ## Parses tags in the Datadog StatsD format
  ## http://docs.datadoghq.com/guides/dogstatsd/
  parse_data_dog_tags = true

  ## Parses Datadog extensions to the StatsD format
  datadog_extensions = true

  ## Parses distribution metrics as specified in the Datadog StatsD format
  ## https://docs.datadoghq.com/developers/metrics/types/?tab=distribution#definition
  datadog_distributions = true

  ## We do not need following tags (they may create a large number of time series under InfluxDB's logic)
  # Examples:
  # "runtime-id", "metric-type"
  drop_tags = [ ]

  # All metric-names prefixed with 'jvm_' are set to InfluxDB's measurement 'jvm'
  # All metric-names prefixed with 'stats_' are set to InfluxDB's measurement 'stats'
  # Examples:
  # "stats_:stats", "jvm_:jvm", "tomcat_:tomcat",
  metric_mapping = [ ]

  ## Number of UDP messages allowed to queue up, once filled,
  ## the StatsD server will start dropping packets, default is 128.
  # allowed_pending_messages = 128

  ## Number of timing/histogram values to track per-measurement in the
  ## calculation of percentiles. Raising this limit increases the accuracy
  ## of percentiles but also increases the memory usage and CPU time.
  percentile_limit = 1000

  ## Max duration (TTL) for each metric to stay cached/reported without being updated.
  #max_ttl = "1000h"

  [inputs.statsd.tags]
  # some_tag = "some_value"
  # more_tag = "some_other_value"

After configuring, restart DataKit.

Currently, you can enable the collector by injecting the collector configuration via ConfigMap.

Info

If logs show a large amount of Feed: io busy, you can configure interval = '1s', minimum 1s.

Tagging Data Sources¶

To tag hosts collected by DDTrace, you can use the method of injecting tags:

You can use environment variables, i.e., DD_TAGS, for example: DD_TAGS=source_key:tomcat,host_key:cn-shanghai-sq5ei
You can use command-line options, i.e., dd.tags, for example: -Ddd.tags=source_key:tomcat,host_key:cn-shanghai-sq5ei

In the above examples, specify the source key as source_key and the host key as host_key in the DataKit configuration. You can change these to other names, but ensure that the field names in the DataKit configuration match those in DDTrace.

The final effect is that when using datakit monitor, you will see statsd/tomcat/cn-shanghai-sq5ei, which helps distinguish this data source from others. Without this configuration, datakit monitor will display the default: statsd/-/-.

Additionally, there is a configuration switch save_above_key to decide whether to report the tags corresponding to statsd_source_key and statsd_host_key to the center. By default, it does not report (false).

Metrics¶

StatsD does not have predefined metric sets; all metrics are based on those received over the network.

Using the default metric set provided by the Agent, you can view all metric sets on GitHub.