Orchestrating multi-agent AI architectures with Amazon S3 Files

This article demonstrates how to build multi-agent AI pipelines using Amazon S3 Files as a shared file system for coordination across different AWS compute services.

• S3 Files provides POSIX semantics over S3 data, enabling agents to use standard file operations like open() and os.listdir() instead of S3 API calls
• Five-stage document processing pipeline with agents on EC2, Lambda, EKS, ECS Fargate, and Bedrock AgentCore Runtime sharing a single mounted file system
• Agents coordinate through directory-based handoffs: intake/ → analyzed/ → validated/ → reports/ → summaries/ with close-to-open consistency
• Access points enable per-agent POSIX identity isolation; deduplication prevents duplicate processing via atomic claims or output file existence checks
• EC2 and EKS mount directly as root; Lambda, ECS, and AgentCore mount through access points with UID 1000/GID 1000
• S3 Files eliminates custom integration code between stages and provides event-driven capabilities through S3 event notifications and EventBridge scheduling

S3 Files simplifies multi-agent coordination by replacing message queues and API calls with a shared file system, enabling agents to read and write through standard POSIX operations while maintaining S3's scalability and event-driven capabilities.