Processors

The Batch Processor batches traces and metrics to reduce the number of outgoing connections needed to transfer the telemetry information.

The Memory Limiter Processor periodically checks the Collector’s memory usage and pauses data processing when the soft memory limit is reached. This processor supports traces, metrics, and logs. The preceding component, which is typically a receiver, is expected to retry sending the same data and may apply a backpressure to the incoming data. When memory usage exceeds the hard limit, the Memory Limiter Processor forces garbage collection to run.

The Resource Detection Processor identifies host resource details in alignment with OpenTelemetry’s resource semantic standards. Using the detected information, this processor can add or replace the resource values in telemetry data. This processor supports traces and metrics. You can use this processor with multiple detectors such as the Docket metadata detector or the OTEL_RESOURCE_ATTRIBUTES environment variable detector.

The Attributes Processor can modify attributes of a span, log, or metric. You can configure this processor to filter and match input data and include or exclude such data for specific actions.

This processor operates on a list of actions, executing them in the order specified in the configuration. The following actions are supported:

The Resource Processor applies changes to the resource attributes. This processor supports traces, metrics, and logs.

Attributes represent the actions that are applied to the resource attributes, such as delete the attribute, insert the attribute, or upsert the attribute.

The Span Processor modifies the span name based on its attributes or extracts the span attributes from the span name. This processor can also change the span status and include or exclude spans. This processor supports traces.

Span renaming requires specifying attributes for the new name by using the from_attributes configuration.

You can use this processor to extract attributes from the span name.

You can have the span status modified.

The Kubernetes Attributes Processor enables automatic configuration of spans, metrics, and log resource attributes by using the Kubernetes metadata. This processor supports traces, metrics, and logs. This processor automatically identifies the Kubernetes resources, extracts the metadata from them, and incorporates this extracted metadata as resource attributes into relevant spans, metrics, and logs. It utilizes the Kubernetes API to discover all pods operating within a cluster, maintaining records of their IP addresses, pod UIDs, and other relevant metadata.

The Filter Processor leverages the OpenTelemetry Transformation Language to establish criteria for discarding telemetry data. If any of these conditions are satisfied, the telemetry data are discarded. You can combine the conditions by using the logical OR operator. This processor supports traces, metrics, and logs.

The Routing Processor routes logs, metrics, or traces to specific exporters. This processor can read a header from an incoming gRPC or plain HTTP request or read a resource attribute, and then direct the trace information to relevant exporters according to the read value.

Optionally, you can create an attribute_source configuration, which defines where to look for the attribute that you specify in the from_attribute field. The supported values are context for searching the context including the HTTP headers, and resource for searching the resource attributes.

The Cumulative-to-Delta Processor processor converts monotonic, cumulative-sum, and histogram metrics to monotonic delta metrics.

You can filter metrics by using the include: or exclude: fields and specifying the strict or regexp metric name matching.

This processor does not convert non-monotonic sums and exponential histograms.

The Group-by-Attributes Processor groups all spans, log records, and metric datapoints that share the same attributes by reassigning them to a Resource that matches those attributes.

At minimum, configuring this processor involves specifying an array of attribute keys to be used to group spans, log records, or metric datapoints together, as in the following example:

The Transform Processor enables modification of telemetry data according to specified rules and in the OpenTelemetry Transformation Language (OTTL). For each signal type, the processor processes a series of conditions and statements associated with a specific OTTL Context type and then executes them in sequence on incoming telemetry data as specified in the configuration. Each condition and statement can access and modify telemetry data by using various functions, allowing conditions to dictate if a function is to be executed.

All statements are written in the OTTL. You can configure multiple context statements for different signals, traces, metrics, and logs. The value of the context type specifies which OTTL Context the processor must use when interpreting the associated statements.