Question

A GenAI developer operates a production RAG chatbot built on API Gateway, Lambda, a Bedrock Knowledge Base, and Amazon Bedrock foundation models. Users report intermittent high end-to-end latency, but the team cannot determine whether the delay originates from vector retrieval, model invocation, or the Lambda orchestration code. They need a solution that provides a per-request breakdown of time spent in each downstream call with minimal custom instrumentation. Which approach best addresses this need?

Accepted Answer

Enable AWS X-Ray active tracing on the Lambda functions and API Gateway, and use the X-Ray SDK to create subsegments around the Knowledge Base retrieval and Bedrock InvokeModel calls to visualize the latency breakdown in service maps and traces.

Answer

Enable Bedrock model invocation logging to Amazon S3 and query the logs with Amazon Athena to calculate average model latency across all requests.

Answer

Create a CloudWatch dashboard aggregating the Lambda Duration metric and the Bedrock InvocationLatency metric to identify overall slowdowns.

Answer

Enable AWS CloudTrail data events for Bedrock and correlate the event timestamps with API Gateway access logs to reconstruct request timing.