What’s the Best Way to Serve Multiple AI Models with Node.js?

Really solid insights! The containerized approach with worker pools sounds like a smart way to manage resources effectively. I’m curious about how BullMQ performs under heavy loads when managing thousands of concurrent jobs. We’re exploring a different setup with a shared orchestrator layer to reduce cold-start times while maintaining fault tolerance for each model.

I’ve had great success with the containerized method, where each AI model runs in its own isolated container. This setup has helped in managing resources effectively and avoiding memory leaks, especially when mixing GPU and CPU workloads. I coupled it with a worker pool setup, with each worker handling one model. For job queues, I prefer BullMQ; it’s been really reliable and makes it so much easier to manage concurrency. Just be cautious about cleaning up GPU memory between runs to avoid crashes. Proper error handling and monitoring from the start is a lifesaver!

I’d recommend going with a containerized approach combined with a worker pool. It would be difficult to run multiple models in a single long-lived Node process efficiently due to resource constraints, as it could quickly get expensive. Containerization allows for dynamically spinning up and down models, minimizing resource usage and optimizing costs. Plus, with this method, you can 'right-size' the resources, ensuring each model has exactly what it needs.