coreweave-debug-bundle

'Collect CoreWeave cluster diagnostics for support tickets.

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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 Debug Bundle

Overview

Collect GPU node health, Kubernetes pod status, event logs, and API connectivity into a single diagnostic archive for CoreWeave support tickets. This bundle captures cluster-level resource allocation, failed pod logs, GPU device plugin state, and network reachability so support engineers can diagnose infrastructure issues without requesting additional information. Useful when GPU pods are stuck pending, inference workloads OOM, or node autoscaling behaves unexpectedly.

Debug Collection Script


#!/bin/bash
set -euo pipefail
BUNDLE="debug-coreweave-$(date +%Y%m%d-%H%M%S)"
mkdir -p "$BUNDLE"

# Environment check
echo "=== CoreWeave Debug Bundle ===" | tee "$BUNDLE/summary.txt"
echo "Generated: $(date -u +%Y-%m-%dT%H:%M:%SZ)" >> "$BUNDLE/summary.txt"
echo "COREWEAVE_API_KEY: ${COREWEAVE_API_KEY:+[SET]}" >> "$BUNDLE/summary.txt"
echo "KUBECONFIG: ${KUBECONFIG:-default}" >> "$BUNDLE/summary.txt"
echo "kubectl: $(kubectl version --client --short 2>/dev/null || echo 'not found')" >> "$BUNDLE/summary.txt"

# API connectivity
HTTP=$(curl -s -o /dev/null -w "%{http_code}" -H "Authorization: Bearer ${COREWEAVE_API_KEY}" \
  https://api.coreweave.com/v1/namespaces 2>/dev/null || echo "000")
echo "API Status: HTTP $HTTP" >> "$BUNDLE/summary.txt"

# Cluster state
kubectl get nodes -o wide > "$BUNDLE/nodes.txt" 2>&1 || true
kubectl get pods --all-namespaces -o wide > "$BUNDLE/pods.txt" 2>&1 || true
kubectl get events --sort-by=.lastTimestamp > "$BUNDLE/events.txt" 2>&1 || true

# GPU allocation and device plugin status
kubectl describe nodes | grep -A10 "Allocated resources" > "$BUNDLE/gpu-allocation.txt" 2>&1 || true
kubectl get pods -n kube-system -l k8s-app=nvidia-device-plugin -o wide > "$BUNDLE/gpu-plugin.txt" 2>&1 || true

# Failed pod logs
for pod in $(kubectl get pods --field-selector=status.phase=Failed -o name 2>/dev/null); do
  kubectl logs "$pod" --tail=200 > "$BUNDLE/$(basename "$pod")-logs.txt" 2>&1 || true
done

# Rate limit headers
curl -s -D "$BUNDLE/rate-headers.txt" -o /dev/null \
  -H "Authorization: Bearer ${COREWEAVE_API_KEY}" \
  https://api.coreweave.com/v1/namespaces 2>/dev/null || true

tar -czf "$BUNDLE.tar.gz" "$BUNDLE" && rm -rf "$BUNDLE"
echo "Bundle: $BUNDLE.tar.gz"

Analyzing the Bundle


tar -xzf debug-coreweave-*.tar.gz
cat debug-coreweave-*/summary.txt          # API + env status at a glance
grep -i "error\|fail\|oom" debug-coreweave-*/events.txt  # Critical events
cat debug-coreweave-*/gpu-allocation.txt   # GPU resource pressure

Common Issues

Symptom Check in Bundle Fix
GPU pods stuck Pending gpu-allocation.txt shows 0 allocatable GPUs Request quota increase or switch to available GPU type
OOMKilled on inference pod events.txt for OOMKilled entries Increase memory limits in pod spec; check model size vs allocated RAM
Node NotReady nodes.txt status column Check events.txt for kubelet issues; contact CoreWeave if persistent
API returns 401 summary.txt shows HTTP 401 Regenerate API key at CoreWeave dashboard; verify COREWEAVEAPIKEY is set
NVIDIA device plugin missing gpu-plugin.txt empty or error Verify namespace kube-system has device plugin DaemonSet; redeploy if missing

Automated Health Check


async function checkCoreWeave(): Promise<void> {
  const key = process.env.COREWEAVE_API_KEY;
  if (!key) { console.error("[FAIL] COREWEAVE_API_KEY not set"); return; }

  const res = await fetch("https://api.coreweave.com/v1/namespaces", {
    headers: { Authorization: `Bearer ${key}` },
  });
  console.log(`[${res.ok ? "OK" : "FAIL"}] API: HTTP ${res.status}`);

  const limit = res.headers.get("x-ratelimit-remaining");
  if (limit) console.log(`[INFO] Rate limit remaining: ${limit}`);
}
checkCoreWeave();

Resources

Next Steps

See coreweave-common-errors for GPU scheduling and Kubernetes troubleshooting patterns.

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