This source did not publish a separate summary. Review SKILL.md before using the skill.
SKILL.md
CoreWeave Upgrade & Migration
Community-contributed. Not affiliated with, endorsed by, or sponsored by CoreWeave, Inc. CoreWeave is a registered trademark of CoreWeave, Inc.
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