Coreweave Multi Env Setup
DevOps & Securitycoreweave-multi-env-setupCoreweave Multi Env Setup is an Agent Skill for devops & security published in the jeremylongshore/claude-code-plugins-plus-skills repository on GitHub: a SKILL.md instruction file an AI agent can load to do this task.
Configure CoreWeave across development, staging, and production environments. Use when setting up multi-environment GPU infrastructure, separating namespaces, or managing per-environment GPU quotas. Trigger with phrases like "coreweave environments", "coreweave staging", "coreweave multi-env", "coreweave namespace setup".
How to use this skill
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- Open your project in Codex.
- Copy and paste the prompt below.
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Inspect the Agent Skill at https://github.com/jeremylongshore/claude-code-plugins-plus-skills/blob/HEAD/plugins/saas-packs/coreweave-pack/skills/coreweave-multi-env-setup/SKILL.md and all supporting files. Report provenance, permissions, scripts, dependencies, and security risks. Propose an exact installation into .agents/skills/coreweave-multi-env-setup, but wait for my approval before writing files or running scripts.
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CoreWeave Multi-Environment Setup
Community-contributed. Not affiliated with, endorsed by, or sponsored by CoreWeave, Inc. CoreWeave is a registered trademark of CoreWeave, Inc.
Overview
CoreWeave GPU cloud requires strict environment separation to control infrastructure costs and prevent resource contention. Each environment maps to an isolated Kubernetes namespace with its own GPU quota, scaling policy, and access controls. Development uses cheaper GPU tiers for iteration speed, staging mirrors production GPU types for accurate benchmarking, and production runs full-scale with no scale-to-zero to guarantee inference latency SLAs.
Environment Configuration
const coreweaveConfig = (env: string) => ({
development: {
namespace: "app-dev", apiEndpoint: process.env.CW_API_ENDPOINT_DEV!,
token: process.env.CW_TOKEN_DEV!, gpuType: "L40", scaleToZero: true, replicas: [0, 1],
},
staging: {
namespace: "app-staging", apiEndpoint: process.env.CW_API_ENDPOINT_STG!,
token: process.env.CW_TOKEN_STG!, gpuType: "A100_PCIE_40GB", scaleToZero: true, replicas: [0, 2],
},
production: {
namespace: "app-prod", apiEndpoint: process.env.CW_API_ENDPOINT_PROD!,
token: process.env.CW_TOKEN_PROD!, gpuType: "A100_PCIE_80GB", scaleToZero: false, replicas: [2, 10],
},
}[env]);
Environment Files
# Per-env files: .env.development, .env.staging, .env.production
CW_API_ENDPOINT_{DEV|STG|PROD}=https://k8s.{ord1|ord1|las1}.coreweave.com
CW_TOKEN_{DEV|STG|PROD}=<service-account-token>
CW_NAMESPACE={app-dev|app-staging|app-prod}
CW_GPU_TYPE={L40|A100_PCIE_40GB|A100_PCIE_80GB}
Environment Validation
function validateCoreWeaveEnv(env: string): void {
const required = ["CW_API_ENDPOINT", "CW_TOKEN", "CW_NAMESPACE", "CW_GPU_TYPE"];
const suffix = { development: "_DEV", staging: "_STG", production: "_PROD" }[env];
const missing = required
.map((k) => (k.includes("NAMESPACE") ? k : `${k}${suffix}`))
.filter((k) => !process.env[k]);
if (missing.length) throw new Error(`Missing env vars for ${env}: ${missing.join(", ")}`);
}
Promotion Workflow
# 1. Validate model in dev namespace
kubectl -n app-dev get inferenceservice my-model -o jsonpath='{.status.conditions}'
# 2. Apply staging overlay with production GPU type
kustomize build k8s/overlays/staging | kubectl apply -f -
# 3. Run inference benchmarks against staging endpoint
curl -X POST https://staging.myapp.coreweave.cloud/v1/predict -d @test-payload.json
# 4. Promote to production (blue-green via namespace switch)
kustomize build k8s/overlays/prod | kubectl apply -f -
kubectl -n app-prod rollout status deployment/my-model
Environment Matrix
| Setting | Dev | Staging | Prod |
|---|---|---|---|
| GPU Type | L40 | A100 40GB | A100 80GB |
| Scale-to-Zero | Yes | Yes | No |
| Replicas | 0-1 | 0-2 | 2-10 |
| Namespace | app-dev | app-staging | app-prod |
| Region | ord1 | ord1 | las1 |
| Spot Instances | Yes | No | No |
Error Handling
| Issue | Cause | Fix |
|---|---|---|
| GPU quota exceeded | Namespace limit reached | Request quota increase via CW support portal |
| Pod stuck Pending | GPU type unavailable in region | Check kubectl describe node for capacity; switch region |
| Scale-to-zero not waking | HPA misconfigured | Verify minReplicas: 0 and KEDA scaler settings |
| Namespace access denied | RBAC not applied to overlay | Apply RoleBinding in kustomize overlay |
Resources
Next Steps
See coreweave-deploy-integration.