Agent skill · software engineering · jeremylongshore
coreweave-deploy-integration
Deploy inference services on CoreWeave with Helm charts and Kustomize.
Why this skill is useful
Adds executable deployment scripts and specific configurations for GPU-accelerated inference on CoreWeave that are not commonly found in public documentation.
What it needs
Requires docker, helm, kubectl, kustomize installed locally. Requires coreweave account access. About 3k tokens when loaded. Last updated 2026-08-07. 2,604 stars on the source repository.
What this skill does
CoreWeave Deploy Integration Community-contributed. Not affiliated with, endorsed by, or sponsored by CoreWeave, Inc. CoreWeave is a registered trademark of CoreWeave, Inc. Overview Deploy GPU-accelerated inference services on CoreWeave Kubernetes (CKS). This skill covers containerizing inference workloads with NVIDIA CUDA base images, configuring GPU resource limits and node affinity for A100/H100 scheduling, setting up health checks that validate GPU availability and model loading, and executing rolling updates that respect GPU node draining. CoreWeave's scheduler requires explicit GPU resource requests to place pods on the correct hardware tier. Docker Configuration Prerequisites A reviewed image digest in an approved registry and a namespace-scoped image pull secret. A production deployment manifest with resource limits, health checks, SLO, and rollback revision. Approval for the target namespace, GPU capacity, and service exposure. Instructions 1. Build and scan the image, then deploy the immutable digest to staging first. 2. Verify readiness, health, GPU allocation, and baseline request behavior before promotion. 3. Use a controlled rolling update with a timeout and named observer. 4. Roll back immediately if readiness, error rate, latency, or security verification fails. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills jeremylongshore/coreweave-deploy-integration--703c3e