Introduction to Deploying RAG Pipelines for Production at Scale

Why it matters

A retrieval-augmented agent in production is several services, each scaled and balanced on its own terms. This course is NVIDIA’s structured introduction to running such a pipeline at scale.

What to practise

The course is NVIDIA Deep Learning Institute training in deploying retrieval-augmented generation (RAG) pipelines for production at scale; its outline is on the course page. As you work through it, note which components run on GPUs, how requests reach each one, and, wherever the course scales a component, which signal decides when it gets another replica.

How it fits

Hold the deployment against 4.4.1 for how GPU Pods are admitted, 4.4.2 for how inference requests are routed across workers, and 4.4.3 for which metrics should drive autoscaling and what a new replica costs before it can serve.