Build agentic retrieval on a Managed Amazon Bedrock Knowledge Base with CDK
- Who
- AWS Machine Learning Blog
- What
- publishes a tutorial building and deploying an observable agentic retrieval system on Managed Amazon Bedrock Knowledge Bases with AWS CDK
What happened
AWS demonstrates how to build agentic retrieval across two Managed Amazon Bedrock Knowledge Bases using a Python AWS CDK application. The solution connects a reasoning agent through AgentCore Gateway to separate financial and weather retrieval tools, with cited answers, two CloudWatch dashboards covering seven telemetry layers, and on-demand and continuous evaluation. The walkthrough covers deployment, testing, observability, evaluation sampling costs, and cleanup.
Why it matters
Separating knowledge bases into distinct retrieval tools makes routing decisions observable and keeps quality metrics specific to each corpus, offering a practical pattern for diagnosing retrieval across unrelated domains.
Read next
See the full storyAWS Publishes CDK Tutorial for Agentic Retrieval Across Bedrock Knowledge BasesThe story so far
AWS published a tutorial showing how to deploy an agentic retrieval system across two Managed Amazon Bedrock Knowledge Bases using a single Python AWS CDK application. The example connects a reasoning agent through Amazon Bedrock AgentCore Gateway to separate financial and weather retrieval tools and returns answers with citations. The walkthrough covers deployment, testing, cleanup, and monitoring through two CloudWatch dashboards spanning seven telemetry layers, alongside on-demand and continuous evaluation. AWS says online evaluation invokes an LLM judge for each sampled session, so evaluation costs scale with the sampling rate and traffic volume. Agentic retrieval is available only on the Managed Knowledge Base. Regional availability also limits deployment: Managed Knowledge Bases, agentic retrieval through AgenticRetrieveStream, and AgentCore Runtime and Gateway are not available in every AWS Region.
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