Real-time endpoints are powerful but always-on—they cost money. What if you have hundreds of models? Spinning separate endpoints per model explodes instance costs. Plus, what if you need preprocessing before inference and postprocessing after? How do you bundle that into one endpoint? Today we cover advanced patterns that cut costs and handle complex inference flows in a single endpoint. MLA-C01 tests this topic via keywords like "hundreds of models," "preprocessing + inference in one endpoint," and "slash deep-learning inference cost."
Distinguish 4 core concepts. Multi-model Endpoint (MME) swaps many models via same container dynamically