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sample-agentic-frameworks-on-aws
by aws-samples
Reference notebooks for building agentic AI pipelines on AWS with OSS frameworks
Jupyter Notebook
Updated Jun 2, 2026
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Summary
Demonstrates how to build agentic AI solutions on AWS using popular open-source frameworks and integrations. Provides notebooks and reference patterns that wire together agent builders, vector stores, observability hooks, and orchestration components for end-to-end demos. Highlights AWS-managed infrastructure and integration examples so teams can reproduce and extend multi-agent workflows on cloud services.
Key Benefits
As multi-agent systems move toward production, reproducible examples that combine orchestration, observability, and storage are essential for evaluating agent behavior. These [reference notebooks] make it easier to log interactions, exercise failure modes, and stitch together evaluation tooling—helping teams surface agent reliability and track records sooner. Until now many examples were fragmented; centralizing patterns on AWS reduces friction for teams testing multi-agent trust and A2A evaluation scenarios. For better visibility, emphasize observability.
Ideal For
Engineering teams prototyping multi-agent architectures on AWS who want concrete reference patterns for orchestration, storage, and observability.
Use Cases
- Prototyping multi-agent orchestration with cloud-managed infrastructure
- Integrating vector stores and agent builders (llamaindex, langgraph, crewai) into end-to-end demos
- Capturing interaction logs and observability hooks for pre-production agent testing
- Reproducing failure modes and benchmarking agent delegation patterns on AWS
Works With
crewai
Topics
a2a-protocolagentic-aiarize-phoenixcrewailanggraphllamaindexmem0pipecatstrands-agents
Similar Tools
autogencrewai
Keywords
multi-agent trustA2A evaluationagentic-aiaws