Build agentic retrieval on a Managed Amazon Bedrock Knowledge Base with CDK
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This article details how to build enterprise-grade agentic retrieval using Managed Amazon Bedrock Knowledge Bases and the AWS Cloud Development Kit (CDK). It contrasts this approach with traditional single-shot Retrieval Augmented Generation (RAG), explaining that agentic systems use a reasoning agent to decide which knowledge base to consult and whether multiple retrievals are needed for complex questions. The solution leverages Amazon Bedrock AgentCore, which exposes knowledge bases as tools via the Model Context Protocol (MCP) Gateway, enabling semantic routing across different corpora. A key innovation is the integration of comprehensive observability and evaluation directly into the infrastructure, featuring seven layers of telemetry in Amazon CloudWatch and both on-demand and continuous automated evaluations. By using CDK, the authors demonstrate how to manage complex cross-stack dependencies automatically without manual export/import scripts or custom deployment orderings. The system utilizes Managed Knowledge Bases to eliminate the need for provisioning vector databases like OpenSearch Serverless, simplifying the operational footprint. Finally, the post provides a complete Python-based CDK application that deploys the entire architecture, including dashboards and evaluation configurations, with a single command.
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