Trace Analytics for Amazon OpenSearch Service - Amazon OpenSearch Service
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Trace Analytics for Amazon OpenSearch Service

You can use Trace Analytics, which is part of the OpenSearch Observability plugin, to analyze trace data from distributed applications. Trace Analytics requires OpenSearch or Elasticsearch 7.9 or later.

In a distributed application, a single operation, such as a user clicking a button, can trigger an extended series of events. For example, the application front end might call a backend service, which calls another service, which queries a database, which processes the query and returns a result. Then the first backend service sends a confirmation to the front end, which updates the UI.

You can use Trace Analytics to help you visualize this flow of events and identify performance problems.


This documentation provides a brief overview of Trace Analytics. For comprehensive documentation, see Trace Analytics in the open source OpenSearch documentation.


Trace Analytics requires you to add instrumentation to your application and generate trace data using an OpenTelemetry-supported library such as Jaeger or Zipkin. This step occurs entirely outside of OpenSearch Service. The Amazon Distro for OpenTelemetry documentation contains example applications for many programming languages that can help you get started, including Java, Python, Go, and JavaScript.

After you add instrumentation to your application, the OpenTelemetry Collector receives data from the application and formats it into OpenTelemetry data. See the list of receivers on GitHub. Amazon Distro for OpenTelemetry includes a receiver for Amazon X-Ray.

Finally, you can use Amazon OpenSearch Ingestion to format that OpenTelemetry data for use with OpenSearch. For more information, see Trace Analytics with Amazon OpenSearch Ingestion.

OpenTelemetry Collector sample configuration

To use the OpenTelemetry Collector with Amazon OpenSearch Ingestion, try the following sample configuration:

extensions: sigv4auth: region: "us-east-1" service: "osis" receivers: jaeger: protocols: grpc: exporters: otlphttp: traces_endpoint: "" auth: authenticator: sigv4auth compression: none service: extensions: [sigv4auth] pipelines: traces: receivers: [jaeger] exporters: [otlphttp]

OpenSearch Ingestion sample configuration

To send trace data to an OpenSearch Service domain, try the following sample OpenSearch Ingestion pipeline configuration. For instructions to create a pipeline, see Creating Amazon OpenSearch Ingestion pipelines.

version: "2" otel-trace-pipeline: source: otel_trace_source: "/${pipelineName}/ingest" processor: - trace_peer_forwarder: sink: - pipeline: name: "trace_pipeline" - pipeline: name: "service_map_pipeline" trace-pipeline: source: pipeline: name: "otel-trace-pipeline" processor: - otel_traces: sink: - opensearch: hosts: ["https://domain-endpoint"] index_type: trace-analytics-raw aws: # IAM role that OpenSearch Ingestion assumes to access the domain sink sts_role_arn: "arn:aws:iam::{account-id}:role/pipeline-role" region: "us-east-1" service-map-pipeline: source: pipeline: name: "otel-trace-pipeline" processor: - service_map: sink: - opensearch: hosts: ["https://domain-endpoint"] index_type: trace-analytics-service-map aws: # IAM role that the pipeline assumes to access the domain sink sts_role_arn: "arn:aws:iam::{account-id}:role/pipeline-role" region: "us-east-1"

The pipeline role that you specify in the sts_role_arn option must have write permissions to the sink. For instructions to configure permissions for the pipeline role, see Setting up roles and users in Amazon OpenSearch Ingestion.

Exploring trace data

The Dashboard view groups traces together by HTTP method and path so that you can see the average latency, error rate, and trends associated with a particular operation. For a more focused view, try filtering by trace group name.

To drill down on the traces that make up a trace group, choose the number of traces in the right-hand column. Then choose an individual trace for a detailed summary.

The Services view lists all services in the application, plus an interactive map that shows how the various services connect to each other. In contrast to the dashboard (which helps identify problems by operation), the service map helps you identify problems by service. Try sorting by error rate or latency to get a sense of potential problem areas of your application.