--- name: coreweave-install-auth-226e696f0a96 description: 'Configure CoreWeave Kubernetes Service (CKS) access with kubeconfig and API tokens. Use when setting up kubectl access to CoreWeave, configuring CKS clusters, or authenticating with CoreWeave cloud services. Trigger with phrases like "install coreweave", "setup coreweave", "coreweave kubeconfig", "coreweave auth", "connect to coreweave". ' allowed-tools: Read, Write, Edit, Bash(kubectl:*), Grep version: 1.11.0 license: MIT author: Jeremy Longshore tags: - saas - gpu-cloud - kubernetes - inference - coreweave compatibility: Designed for Claude Code --- # CoreWeave Install & Auth > **Community-contributed.** Not affiliated with, endorsed by, or sponsored by CoreWeave, Inc. CoreWeave is a registered trademark of CoreWeave, Inc. ## Overview Set up access to CoreWeave Kubernetes Service (CKS). CKS runs bare-metal Kubernetes with NVIDIA GPUs -- no hypervisor overhead. Access is via standard kubeconfig with CoreWeave-issued credentials. ## Prerequisites - CoreWeave account at https://cloud.coreweave.com - `kubectl` v1.28+ installed - Kubernetes namespace provisioned by CoreWeave ## Instructions ### Step 1: Download Kubeconfig 1. Log in to https://cloud.coreweave.com 2. Navigate to **API Access** > **Kubeconfig** 3. Download the kubeconfig file ```bash # Save kubeconfig mkdir -p ~/.kube cp ~/Downloads/coreweave-kubeconfig.yaml ~/.kube/coreweave # Set as active context export KUBECONFIG=~/.kube/coreweave # Verify connection kubectl get nodes kubectl get namespaces ``` ### Step 2: Configure API Token ```bash # CoreWeave API token for programmatic access export COREWEAVE_API_TOKEN="your-api-token" # Store securely echo "COREWEAVE_API_TOKEN=${COREWEAVE_API_TOKEN}" >> .env echo "KUBECONFIG=~/.kube/coreweave" >> .env ``` ### Step 3: Verify GPU Access ```bash # List available GPU nodes kubectl get nodes -l gpu.nvidia.com/class -o custom-columns=\ NAME:.metadata.name,GPU:.metadata.labels.gpu\.nvidia\.com/class,\ STATUS:.status.conditions[-1].type # Check GPU allocatable resources kubectl describe nodes | grep -A5 "Allocatable:" | grep nvidia ``` ### Step 4: Test with a Simple GPU Pod ```yaml # test-gpu.yaml apiVersion: v1 kind: Pod metadata: name: gpu-test spec: restartPolicy: Never containers: - name: cuda-test image: nvidia/cuda:12.2.0-base-ubuntu22.04 command: ["nvidia-smi"] resources: limits: nvidia.com/gpu: 1 affinity: nodeAffinity: requiredDuringSchedulingIgnoredDuringExecution: nodeSelectorTerms: - matchExpressions: - key: gpu.nvidia.com/class operator: In values: ["A100_PCIE_80GB"] ``` ```bash kubectl apply -f test-gpu.yaml kubectl logs gpu-test # Should show nvidia-smi output kubectl delete pod gpu-test ``` ## Error Handling | Error | Cause | Solution | |-------|-------|----------| | `Unable to connect to the server` | Wrong kubeconfig | Verify KUBECONFIG path | | `Forbidden` | Missing namespace permissions | Contact CoreWeave support | | No GPU nodes found | Wrong node labels | Check `gpu.nvidia.com/class` labels | | Pod stuck Pending | GPU capacity exhausted | Try different GPU type or region | ## Output - A namespace-scoped Kubernetes context and a verified GPU scheduling result. - A credential setup that references the approved secret manager and never commits or prints live values. - A deleted smoke-test Pod after its redacted result is recorded. ## Examples Configure a temporary shell session from your secret manager, then run the smallest GPU smoke test in a sandbox namespace: ```bash export KUBECONFIG="$HOME/.kube/coreweave-sandbox" kubectl -n sandbox apply -f test-gpu.yaml kubectl -n sandbox wait --for=condition=Ready pod/gpu-test --timeout=10m kubectl -n sandbox logs gpu-test kubectl -n sandbox delete -f test-gpu.yaml ``` If access is denied or capacity is unavailable, retain the redacted status and contact the namespace owner. Do not put a token in `.env`, a manifest, shell history, or support tickets. ## Resources - [CoreWeave Documentation](https://docs.coreweave.com) - [CKS Introduction](https://docs.coreweave.com/docs/products/cks) - [GPU Instance Types](https://docs.coreweave.com/docs/platform/instances/gpu-instances) ## Next Steps Proceed to `coreweave-hello-world` to deploy your first inference service. --- Source attribution: jeremylongshore Original project: https://github.com/jeremylongshore/claude-code-plugins-plus-skills/blob/ab85a061f7bcc039dac13ee193de7a4cd4388571/plugins/saas-packs/coreweave-pack/skills/coreweave-install-auth/SKILL.md License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice MIT License Copyright (c) 2025 Jeremy Longshore Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # Mega AI Hub resource metadata Creator / publisher: jeremylongshore Original project: https://github.com/jeremylongshore/claude-code-plugins-plus-skills/blob/ab85a061f7bcc039dac13ee193de7a4cd4388571/plugins/saas-packs/coreweave-pack/skills/coreweave-install-auth/SKILL.md Attribution basis: Source repository record Fields of work: Development & Engineering Roles: Backend Developer, DevOps / SRE, ML / AI Engineer Specialties: Backend, DevOps Tools: Kubernetes, Coreweave Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: 59f8d695fe097ccef07480fb85710d5aa512e8c46491a127e3e47be6414b9b50