coreweave-multi-env-setup

DevOps & Security

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".

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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

CoreWeave CKS

Next Steps

See coreweave-deploy-integration.