NEWS · CODING · #3306
Amazon publishes 'Pluggable Agentic AI Framework' — a seven-layer reference architecture for Bedrock AgentCore
Amazon published a blog post presenting the Pluggable Agentic AI Framework, a seven-layer composable reference architecture for running multi-agent AI applications at production scale on Amazon Bedrock AgentCore. The framework defines distinct layers (Data & Knowledge, Model & Inference, Orchestration, agent registry, etc.), protocols like MCP and A2A, and example building blocks such as Vector Engine for OpenSearch Serverless, S3 Vectors, DynamoDB, LiteLLM, and Strands Agents.
KEY POINTS
- Amazon published a blog post presenting the Pluggable Agentic AI Framework, a seven-layer composable reference architecture for running multi-agent AI applications at production scale on Amazon Bedrock AgentCore.
- The framework defines distinct layers (Data & Knowledge, Model & Inference, Orchestration, agent registry, etc.), protocols like MCP and A2A, and example building blocks such as Vector Engine for OpenSearch Serverless, S3 Vectors, DynamoDB, LiteLLM, and Strands Agents.
- A shared, production-ready reference architecture can reduce repeated engineering effort, improve governance and observability, and speed enterprise deployment of agentic AI across organizations.
WHY IT MATTERS
A shared, production-ready reference architecture can reduce repeated engineering effort, improve governance and observability, and speed enterprise deployment of agentic AI across organizations.