coreweave-upgrade-migration

'Upgrade CoreWeave deployments and migrate between GPU types.

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coreweave-pack Plugin
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coreweave-pack

Claude Code skill pack for CoreWeave (24 skills)

saas packs v1.0.0
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Installation

This skill is included in the coreweave-pack plugin:

/plugin install coreweave-pack@claude-code-plugins-plus

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Instructions

CoreWeave Upgrade & Migration

Overview

CoreWeave is a GPU-specialized cloud provider running Kubernetes-native infrastructure. Migrations involve upgrading between GPU instance types (A100 to H100), updating CUDA driver versions, and handling Kubernetes API version changes across namespaces. Tracking API versions is critical because CoreWeave's instance type labels and resource quotas change between platform releases, and deploying to a deprecated instance class will cause scheduling failures.

Version Detection


import { KubeConfig, CoreV1Api } from "@kubernetes/client-node";

async function detectCoreWeaveVersion(): Promise<void> {
  const kc = new KubeConfig();
  kc.loadFromDefault();
  const k8sApi = kc.makeApiClient(CoreV1Api);

  // Check current namespace GPU allocations
  const pods = await k8sApi.listNamespacedPod("my-namespace");
  for (const pod of pods.body.items) {
    const gpuClass = pod.spec?.nodeSelector?.["gpu.nvidia.com/class"];
    const cudaVersion = pod.metadata?.labels?.["cuda-version"];
    console.log(`Pod ${pod.metadata?.name}: GPU=${gpuClass}, CUDA=${cudaVersion}`);
  }

  // Detect deprecated instance types
  const deprecated = ["A100_PCIE_40GB", "V100_PCIE_16GB", "RTX_A5000"];
  const activeGpus = pods.body.items
    .map((p) => p.spec?.nodeSelector?.["gpu.nvidia.com/class"])
    .filter(Boolean);
  const stale = activeGpus.filter((g) => deprecated.includes(g!));
  if (stale.length > 0) console.warn(`Deprecated GPU types in use: ${stale.join(", ")}`);
}

Migration Checklist

  • [ ] Review CoreWeave release notes for deprecated instance types
  • [ ] Audit all deployments for gpu.nvidia.com/class node selectors
  • [ ] Verify CUDA version compatibility with target GPU (see matrix below)
  • [ ] Update container base images to match new CUDA/cuDNN requirements
  • [ ] Test inference latency on new GPU type in staging namespace
  • [ ] Update resource requests (nvidia.com/gpu) for new instance memory
  • [ ] Migrate persistent volumes if switching regions or availability zones
  • [ ] Update Kubernetes API version in manifests (e.g., apps/v1 changes)
  • [ ] Validate HPA scaling behavior on new instance type throughput
  • [ ] Run canary deployment with traffic split before full cutover

Schema Migration


// CoreWeave instance type labels changed in 2025 platform update
// Old: gpu.nvidia.com/class: "A100_PCIE_80GB"
// New: gpu.nvidia.com/class: "H100_SXM5_80GB"

interface DeploymentMigration {
  oldSelector: Record<string, string>;
  newSelector: Record<string, string>;
  cudaMinVersion: string;
}

const GPU_MIGRATIONS: DeploymentMigration[] = [
  {
    oldSelector: { "gpu.nvidia.com/class": "A100_PCIE_80GB" },
    newSelector: { "gpu.nvidia.com/class": "H100_SXM5_80GB" },
    cudaMinVersion: "12.4",
  },
  {
    oldSelector: { "gpu.nvidia.com/class": "A100_SXM4_80GB" },
    newSelector: { "gpu.nvidia.com/class": "H100_SXM5_80GB" },
    cudaMinVersion: "12.4",
  },
];

function migrateNodeSelector(manifest: any, migration: DeploymentMigration): any {
  const selector = manifest.spec?.template?.spec?.nodeSelector;
  if (!selector) return manifest;
  for (const [key, oldVal] of Object.entries(migration.oldSelector)) {
    if (selector[key] === oldVal) {
      selector[key] = migration.newSelector[key];
    }
  }
  return manifest;
}

Rollback Strategy


import { AppsV1Api, KubeConfig } from "@kubernetes/client-node";

async function rollbackDeployment(namespace: string, name: string): Promise<void> {
  const kc = new KubeConfig();
  kc.loadFromDefault();
  const appsApi = kc.makeApiClient(AppsV1Api);

  // Kubernetes rollout undo — reverts to previous revision
  const deployment = await appsApi.readNamespacedDeployment(name, namespace);
  const currentRevision = deployment.body.metadata?.annotations?.["deployment.kubernetes.io/revision"];
  console.log(`Rolling back ${name} from revision ${currentRevision}`);

  // Patch to trigger rollback via revision annotation
  await appsApi.patchNamespacedDeployment(name, namespace, {
    spec: { template: { metadata: { annotations: { "kubectl.kubernetes.io/restartedAt": new Date().toISOString() } } } },
  }, undefined, undefined, undefined, undefined, undefined, { headers: { "Content-Type": "application/strategic-merge-patch+json" } });
  console.log(`Rollback initiated for ${name} in ${namespace}`);
}

Error Handling

Migration Issue Symptom Fix
GPU class not schedulable Pod stuck in Pending with Insufficient nvidia.com/gpu Verify instance type exists in target region; check quota
CUDA version mismatch Container crashes with CUDA driver version is insufficient Rebuild container with CUDA matching target GPU driver
Namespace quota exceeded Forbidden: exceeded quota on deployment Request quota increase for new instance type via CoreWeave dashboard
PVC migration failure VolumeAttachment timeout on new node Detach old PVC, recreate in target availability zone
API version deprecated no matches for kind "Deployment" in version "extensions/v1beta1" Update manifest to apps/v1 and adjust spec fields

Resources

Next Steps

For CI/CD pipeline integration, see coreweave-ci-integration.

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