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Cross-account access to Amazon Bedrock Knowledge Base for RAG applications

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hi team, Is it possible to build RAG-based applications using Amazon Bedrock in multiple AWS accounts, while accessing a centralized/shared Knowledge Base hosted in a separate AWS account?

I'm working on a multi-account architecture where each account would run its own chatbot or LLM-based application, but ideally all of them should query a single shared vector store/knowledge base for consistency and efficiency. Is this setup supported by Bedrock, and are there recommended best practices for cross-account access to the Knowledge Base?

tks

AWS

asked a year ago2.1K views

2 Answers
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Yes, it is possible to build RAG-based applications using Amazon Bedrock across multiple AWS accounts while accessing a centralized Knowledge Base hosted in a separate AWS account. Amazon Bedrock Knowledge Bases now supports cross-account data access, which enables this type of multi-account architecture.

Here are some key points about this setup:

  1. Multiple S3 buckets: Amazon Bedrock Knowledge Bases can incorporate data from multiple S3 buckets, including those in different AWS accounts. This allows you to combine information from various sources across accounts.

  2. Cross-account data access: You can configure S3 buckets as data sources across different accounts. This feature expands the range of information that can be incorporated into your knowledge bases.

  3. Centralized Knowledge Base: You can create a single, shared Knowledge Base in one account and allow other accounts to access it. This promotes consistency and efficiency across your multi-account architecture.

  4. Data source management: When setting up data sources, you can specify whether data should be retained or deleted if a data source is removed. This helps maintain the integrity and accuracy of your shared Knowledge Base.

  5. Security and access control: To implement cross-account access, you'll need to set up appropriate IAM roles and policies. This ensures that only authorized accounts and applications can access the shared Knowledge Base.

Best practices for implementing this setup include:

  1. Use AWS Identity and Access Management (IAM) to carefully manage permissions and access controls between accounts.

  2. Implement metadata filtering to ensure that queries only return results appropriate for each specific application or tenant.

  3. Monitor and audit access using AWS CloudTrail to track API calls and detect any unauthorized access attempts.

  4. Consider using AWS Organizations to manage policies across your multi-account structure.

  5. Regularly review and update your cross-account access policies to maintain security and compliance.

By following these practices, you can create a secure and efficient multi-account RAG architecture using Amazon Bedrock Knowledge Bases, allowing each account to run its own chatbot or LLM-based application while querying a single shared Knowledge Base for consistency and efficiency.
Sources
Building scalable, secure, and reliable RAG applications using Amazon Bedrock Knowledge Bases | AWS Machine Learning Blog
Building scalable, secure, and reliable RAG applications using Amazon Bedrock Knowledge Bases | AWS Machine Learning Blog
Multi-tenancy in RAG applications in a single Amazon Bedrock knowledge base with metadata filtering | AWS Machine Learning Blog
Give Amazon Bedrock API cross-account access | AWS re:Post

answered a year ago

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