Serverless generative AI architectural patterns – Part 2
Compute Blog
This article explores two serverless architectural patterns for generative AI applications that don't require real-time interactions:
- Buffered Asynchronous Processing: A pattern for handling time-intensive, non-interactive requests like video/music generation or complex analysis
- Multimodal Parallel Fan-out: A method for processing tasks across multiple AI models or agents simultaneously
- Non-Interactive Batch Processing: A technique for processing large data volumes on a scheduled or event-driven basis
Key implementation strategies include:
- Using Amazon SQS for message queuing and buffering
- Leveraging WebSocket and REST APIs for request management
- Utilizing AWS Step Functions and EventBridge for workflow orchestration
The goal is to create scalable, reliable generative AI applications with reduced operational complexity by using serverless AWS services.
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