Title: Discussion 2 — Containerize It or Keep It on the Host?
Course: AIINFRA 200: Production Inference Serving & GPU Orchestration > Section: Week 02 — Docker, GPU Runtime, and Dev-Only Tools (Ollama, LM Studio)

💬 Discussion 2 — Containerize It or Keep It on the Host? (20 pts)

This week you configured Docker to reach your GPU and ran Ollama inside a container. LM Studio, by contrast, is typically installed directly on the host as a desktop application. Prompt: What are the tradeoffs between containerizing a development workload like LM Studio versus keeping it on the host machine? Consider factors like GPU driver/toolkit setup complexity, portability across teammates' machines, ease of experimenting with a GUI, resource isolation, and how "dev-only" tooling decisions might differ once you're thinking about eventually moving a workload toward production. Use at least one concrete example from this week's lab or lecture to support your position. Post your initial response, then respond to at least two classmates, engaging with a point they made that differs from your own view.