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Control data to ingest using the Collector đź”—

Depending on its configuration, the Splunk Distribution of OpenTelemetry Collector can forward a wide range of telemetry, such as metrics, traces, or logs, to the Splunk Observability Cloud ingest endpoints. For certain scenarios, some of this data can be redundant, unnecessary, or sensitive, causing technical complications, increased cost, or legal issues.

To address these situations, the Collector comes with options to process the data you’re receiving to modify or delete unwanted elements before they’re ingested by Splunk Observability Cloud. For example, you can use the attributes processor to edit or remove any unwanted data.

Scenarios: Remove dimensions using the attributes processor đź”—

Moira, a performance engineer, notices high cardinality in ingested metrics, which heavily impacts data charges. Moira is considering dropping certain dimensions to cut costs.

Moira checks which dimensions are being used and realizes that for the metric cpu.utilization, the dimensions hostname and source_host are irrelevant. They decide that those dimension don’t need to be ingested at all.

To prevent both dimensions from being ingested, first Moira adds the attributes processor in the Collectors’s configuration, set up to skip the unnecessary dimensions:

      - key: hostname
        action: delete
      - key: source_host
        action: delete

Next, Moira adds the attributes/delete processor to the processors pipeline under pipelines in the Collector’s configuration:

        receivers: ...
        processors: [..., attributes/delete, ...]

Alternatives to alter or remove data đź”—

See another example of how to tweak your data at Remove sensitive data using the Splunk Distribution of OpenTelemetry Collector.

You can also use the metrics pipeline management tool to control how you ingest and store your metrics. Learn more at Introduction to metrics pipeline management.

This page was last updated on Jan 10, 2024.