Amazon Bedrock AgentCore Memory now enables cross-account access, allowing you to build multi-account architectures where memory resources and consuming agents span multiple AWS accounts. You can grant principals in one account permission to call memory data plane APIs against resources in another account using resource-based policies, and configure memory delivery destinations (Amazon S3, Amazon SNS, Amazon Kinesis Data Streams) that reside in a separate account. Cross-account access is configured by attaching a resource-based policy to your memory resource. Once configured, principals in the
The increasing complexity of AI deployments and enterprise cloud architectures necessitates more flexible and secure ways to manage AI resources across different organizational units or environments.
This development significantly enhances the operational flexibility and security of AI agent deployments for large enterprises and potentially for multi-tenant SaaS providers leveraging AWS Bedrock.
Enterprises can now deploy sophisticated AI agent architectures that span multiple AWS accounts, enabling better resource isolation, cost management, and security partitioning without sacrificing AI functionality.
- · AWS
- · Large enterprises with multi-account AWS structures
- · Developers building AI agent solutions on Bedrock
- · AI-powered SaaS providers
- · Monolithic AI application architectures
Enterprises can more easily integrate AI agents into their existing distributed cloud infrastructure.
Increased adoption of Amazon Bedrock for complex, enterprise-grade AI agent deployments due to enhanced security and scalability.
Accelerated development of robust, distributed AI agent systems capable of operating across diverse data and compute environments.
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