Control data pre-ingest

To optimize data ingestion performance, reduce storage costs, allow for customization, and address privacy concerns by controlling the data sent to Splunk Observability Cloud.

Use this when you encounter redundant or unnecessary telemetry data, need to modify data to meet specific requirements, or must sanitize sensitive information before ingestion using the Collector.

Control data to ingest using the Collector

Work with tags or attributes

To add, modify, or remove tags or attributes on data for better organization and control.

Use this when learning how to modify tags and attributes on data before ingestion using the Collector.

Use tags or attributes in OpenTelemetry

Obfuscate sensitive data in logs

To protect privacy by ensuring sensitive log data is not ingested.

Use this when sensitive information needs to be sanitized before ingestion using the Collector.

Remove or obfuscate sensitive information from logs

Obfuscate sensitive data in traces

To protect privacy by ensuring sensitive trace data is not ingested.

Use this when sensitive information needs to be sanitized before ingestion using the Collector.

Use controls for sensitive data in Splunk APM

Filter unwanted logs

To prevent ingestion of unwanted log data by using filtering logic to include or exclude specific logs. This helps to optimize data flow and reduce costs.

Use this when you need to collect log data only from certain sources or of specific types, or when log ingestion load is too high.

Filter logs

Filter unwanted metrics

To prevent ingestion of unwanted metric data by using filtering logic to include or exclude specific metrics. This helps to optimize data flow and reduce costs.

Use this when you need to collect metric data only from certain sources or of specific types, or when metric ingestion load is too high.

Filter metrics

Filter unwanted traces

To prevent ingestion of unwanted trace data by using filtering logic to include or exclude specific traces. This helps to optimize data flow and reduce costs.

Use this when you need to collect trace data only from certain sources or of specific types, or when trace ingestion load is too high.

Filter spans

Collect a fraction of logs using sampling

To reduce log ingestion volume and costs by using probabilistic sampling to collect a percentage of log data.

Use this when you need to collect only a sample set of log data which can help address ingesting too many logs.

Probabilistic sampler processor

Collect a fraction of traces using sampling

To reduce trace ingestion volume and costs by using tail sampling to collect a percentage of trace data.

Use this when you need to collect only a sample set of trace data which can help address ingesting too many traces.

Tail sampling processor

Collect custom metrics

To send custom infrastructure and application metrics to Splunk Observability Cloud for deeper custom visibility.

Use this when instrumenting a service that isn’t natively supported or when specific custom metrics are required.

Send custom metrics to Splunk Observability Cloud

Collect Prometheus metrics

To collect widely used Prometheus metrics and send them to Splunk Observability Cloud.

Use this when instrumenting a Prometheus source for monitoring.

Prometheus receiver

Collect host logs

To collect on-disk logs for analysis and monitoring.

Use this when you need to collect logs from the local system or host.

Filelog receiver

Dynamically collect data from new data sources at runtime

To monitor data sources that may be created, removed, or recreated during runtime.

Use this when the receiver creator feature is needed to dynamically create receivers at runtime, based on configured rules and observer extensions.

Receiver creator receiver

Look for collector support for a specific environment

To ensure that your environment is compatible with the Collector.

Validate support for your target environment before deploying your Collector instance.

Compatibility and requirements for Splunk Observability Cloud

Evaluate Collector deployment options like Ansible, Chef, PCF, or Puppet

Different deployment methods have unique requirements and features, allowing you to tailor the deployment to your specific needs.

Before deploying the Collector choose the most suitable deployment mechanism for your environment and requirements.

Other Collector deployment tools and options: ECS/EC2, Fargate, Nomad, PCF

Review release changes before collector version upgrades

New Collector versions include important features, optimizations, and fixes, which are documented in the release notes.

Always review the release notes before upgrading the collector to understand the changes.

• Main changelog for the Splunk distribution of the Collector

• Collector Contrib repository

• Upstream changelog (Contrib)

• Upstream changelog (Core)