Artificial Intelligence · 26.08.2026, 16:03 UTC
Connect Amazon Bedrock AgentCore to cross-account knowledge bases
| Schweregrad | info |
|---|---|
| Kategorie | Artificial Intelligence |
| Quelle | AWS Machine Learning ↗ |
| Veröffentlicht | 26.08.2026 UTC |
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Organizations often deploy agents using Amazon Bedrock AgentCore, a platform to build, connect, and optimize agents at scale, with any framework or model. These agents may access governed knowledge bases hosted in separate AWS accounts. This cross-account separation helps maintain clear workload boundaries but can introduce integration challenges. This post explains how AgentCore agents in one account can generate answers from a knowledge base (using Amazon Bedrock Knowledge Bases, the fully managed Retrieval Augmented Generation capability) backed by Amazon Redshift Serverless in another account without copying source data. This post covers the architecture, security boundary, request flow, and selection criteria for two generally available Amazon Bedrock AgentCore orchestration models. The linked GitHub sample provides the deployment procedures and implementation details for both variants: A code-based Strands agent on AgentCore runtime, a capability of Amazon Bedrock AgentCore. A declarative AgentCore harness, a capability of Amazon Bedrock AgentCore. The challenge Organizations that build AI agents using Amazon Bedrock can maintain structured data in Amazon Redshift Serverless. These data repositories can reside in separate AWS accounts from their AI agents. Amazon Bedrock Knowledge Bases resource policies support Retrieve and GetDocumentContent for cross-account operations. The supported resource policy actions do not include RetrieveAndGenerate. Because this solution needs the generated answer returned by RetrieveAndGenerate, the tool assumes a narrowly …