Skillshub coreweave-webhooks-events
install
source · Clone the upstream repo
git clone https://github.com/ComeOnOliver/skillshub
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/ComeOnOliver/skillshub "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/jeremylongshore/claude-code-plugins-plus-skills/coreweave-webhooks-events" ~/.claude/skills/comeonoliver-skillshub-coreweave-webhooks-events && rm -rf "$T"
manifest:
skills/jeremylongshore/claude-code-plugins-plus-skills/coreweave-webhooks-events/SKILL.mdsource content
CoreWeave Webhooks & Events
Kubernetes Event Monitoring
# Watch GPU pod events kubectl get events --watch --field-selector=reason=Scheduled,reason=Pulled,reason=Failed # Monitor GPU utilization via exec kubectl exec -it deployment/inference -- nvidia-smi --query-gpu=utilization.gpu,memory.used --format=csv -l 5
Prometheus GPU Metrics
# DCGM exporter for GPU metrics (pre-installed on CKS) # Key metrics: # DCGM_FI_DEV_GPU_UTIL - GPU utilization % # DCGM_FI_DEV_FB_USED - GPU memory used # DCGM_FI_DEV_POWER_USAGE - Power draw
Slack Alert Integration
import subprocess, json, requests def check_inference_health(deployment: str, slack_url: str): result = subprocess.run( ["kubectl", "get", "deployment", deployment, "-o", "json"], capture_output=True, text=True, ) deploy = json.loads(result.stdout) ready = deploy["status"].get("readyReplicas", 0) desired = deploy["spec"]["replicas"] if ready < desired: requests.post(slack_url, json={ "text": f"CoreWeave: {deployment} has {ready}/{desired} replicas ready" })
Resources
Next Steps
For performance optimization, see
coreweave-performance-tuning.