Lilly Tech Systems
Serverless AI Inference
Deploy AI models without managing servers. Learn to run inference on AWS Lambda, Azure Functions, and Google Cloud Run with auto-scaling, pay-per-request pricing, and strategies to minimize cold start latency.
Your Learning Path
Follow these lessons in order, or jump to any topic that interests you.
1. Introduction
Understand when serverless makes sense for AI inference and how it compares to dedicated GPU endpoints.
2. AWS Lambda
Deploy ML models on Lambda with container images, EFS model storage, and optimized inference runtimes.
3. Azure Functions
Run AI inference on Azure Functions with custom containers, Durable Functions orchestration, and model caching.
4. Cloud Run
Serve ML models on Cloud Run with GPU support, concurrent request handling, and Vertex AI integration.
5. Cold Starts
Minimize cold start latency with model optimization, provisioned concurrency, warm-up strategies, and model quantization.
6. Best Practices
Cost optimization, monitoring, error handling, and production deployment patterns for serverless AI inference.