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Overview of log-to-metrics conversion

Metrics are often buried in unstructured or semi-structured log data. The Splunk platform can automatically convert log data to metrics data points and then insert that data into a metrics index that you specify. It can perform this conversion when your log data is ingested into your Splunk platform deployment, or when you run a search on the log data with the mcollect or meventcollect commands.

This functionality follows older features for the Splunk platform that enable the extraction of fields from events at ingest time and search time. When you set up a log-to-metrics conversion, you look at the field-value pairs that are pulled out of your unstructured events and identify the numeric fields that are captured as measurement fields. The Splunk platform generates a separate, unique metric data point for each measurement field in an event.

You can optionally identify extracted fields for the Splunk platform to blacklist so they do not appear in the metric data points.

Extracted fields in your events that you have not identified as measurements or blacklisted fields are added by the Splunk platform to metric data points as dimensions. All metric data points generated from the same event share the same dimension field-value pairs.

Log events

Here are two log events that contain metrics data:

_time Event
08-05-2017 20:26:29.073 -0700 INFO Metrics - group=queue, name=aeq, max_size_kb=500, current_size_kb=300, current_size=53, largest_size=65, smallest_size=5
08-05-2017 20:26:29.075 -0700 INFO Metrics - group=queue, name=indexqueue, max_size_kb=500, current_size_kb=200, current_size=55, largest_size=85, smallest_size=0

The Splunk platform runs a process that extracts the field-value pairs from the events and displays the following table.

_time group name max_size_kb current_size_kb current_size largest_size smallest_size
08-05-2017 20:26:29.073 -0700 queue aeq 500 300 53 65 5
08-05-2017 20:26:29.075 -0700 queue indexqueue 500 200 55 85 0

If you identify the measurement fields in these events as max_size_kb, current_size_kb, current_size, largest_size, and smallest_size, the Splunk platform generates a unique metric data point for each extraction of those fields. The following table has 10 metric data points, one for each measurement field-value pair in the two original log events.

_time metric_name _value group name
08-05-2017 20:26:29.073 -0700 max_size_kb 500 queue aeq
08-05-2017 20:26:29.073 -0700 current_size_kb 300 queue aeq
08-05-2017 20:26:29.073 -0700 current_size 53 queue aeq
08-05-2017 20:26:29.073 -0700 largest_size 65 queue aeq
08-05-2017 20:26:29.073 -0700 smallest_size 5 queue aeq
08-05-2017 20:26:29.075 -0700 max_size_kb 500 queue indexqueue
08-05-2017 20:26:29.075 -0700 current_size_kb 200 queue indexqueue
08-05-2017 20:26:29.075 -0700 current_size 55 queue indexqueue
08-05-2017 20:26:29.075 -0700 largest_size 85 queue indexqueue
08-05-2017 20:26:29.075 -0700 smallest_size 0 queue indexqueue

Anatomy of a log-to-metrics metric data point

Each metric data point contains a _time field, a metric_name field, and a _value field. Metric data points can have one or more dimension fields. Learn more about metric data points in Overview of metrics.

The following table explains how the log-to-metrics process derives the values of each metric data point field:

Metric field Example value Origin of value
_time 08-05-2017 20:26:29.075 -0700 Uses the _time value from the original event. If multiple metric data points are generated from a single event, they all share the same _time value.
metric_name largest_size Uses the name of the measurement field that provides the _value for the metric data point. In this case the measurement field was named largest_size.
_value 85 Uses the value of the measurement field that the metric data point is based on. In this case, the metric data point is based on largest_size=85.
dimension field group=queue, name=indexqueue Any fields in a log event besides _time and metric_name that are not otherwise identified as measurement fields or blacklisted fields become dimension fields. All metric data points generated from the same log event share the same timestamps and dimension field-value pairs.

Set up basic ingest-time log-to-metric conversions through Splunk Web

Use Splunk Web to set up ingest-time conversion of logs to metric data points when all of the events in the log being ingested share the same fields.

There are two stages to the Splunk Web process for setting up log-to-metrics conversion:

  1. Create a new source type of the Log to Metrics category on the Source Types listing page in Settings.
  2. Associate that Log to Metrics source type with an appropriate log data input when you create or edit the input.

For more information, see Set up ingest-time log-to-metrics conversion in Splunk Web.

Create sophisticated ingest-time log-to-metric conversions with props.conf and transforms.conf

Manually create configurations in transforms.conf and props.conf for ingest-time conversion of logs to metric data points when the events in the log being ingested have different sets of measurement fields. For example, you can design configurations that sort events by the values of a shared field and then apply specific log-to-metric conversion rules to each of those event groups.

For more information, see Set up ingest-time log-to-metrics conversion with configuration files.

Get metrics in from other sources
Set up ingest-time log-to-metrics conversion in Splunk Web

This documentation applies to the following versions of Splunk® Enterprise: 7.2.0, 7.2.1, 7.2.2, 7.2.3, 7.2.4, 7.2.5, 7.2.6

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