What problem does it solve?
Deploying a model-serving configuration on dstack without prior validation often fails due to untested images, commands, resources, or backend choices. This Skill guides a task-first prototyping workflow so the serving setup is proven on real hardware before being submitted as a dstack service.
Core Features & Use Cases
- Task-First Prototyping: Start a long-lived dstack task, attach or SSH into it, and test the serving image, model download, cache path, command, port, launch flags, and a real model request before submitting a service.
- Backend and Fleet Selection: Choose VM-based backends, SSH fleets, or Kubernetes fleets that reuse idle instances and instance volumes for caching model weights across runs.
- Serving Source Verification: Consult vLLM recipes, SGLang docs, and release notes to pick the correct image, flags, and expected model behavior.
- Use Case: When serving a new reasoning model with vLLM on dstack, prototype the full serving command inside a task, verify reasoning output via a local request, then submit the identical configuration as a service and confirm it through the dstack service URL.
Quick Start
Use the dstack-prototyping skill to test my vLLM serving configuration for this model in a dstack task before submitting it as a service.
