coreweave-observability
Set up GPU monitoring and observability for CoreWeave workloads. Use when implementing GPU metrics dashboards, configuring alerts, or tracking inference latency and throughput. Trigger with phrases like "coreweave monitoring", "coreweave observability", "coreweave gpu metrics", "coreweave grafana". '
Profile →npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill coreweave-observability --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# CoreWeave Observability > **Community-contributed.** Not affiliated with, endorsed by, or sponsored by CoreWeave, Inc. CoreWeave is a registered trademark of CoreWeave, Inc. ## Overview CoreWeave runs GPU-intensive workloads on Kubernetes where hardware failures, memory exhaustion, and underutilization directly impact cost and reliability. Observability must cover DCGM GPU metrics, Kubernetes pod health, inference latency, and job completion rates. Proactive monitoring prevents wasted spend on idle GPUs and catches OOM conditions before they cascade. ## Key Metrics | Metric | Type | Target | Alert Threshold | |--------|------|--------|-----------------| | GPU utilization | Gauge | > 60% | < 20% for 30m | | GPU memory usage | Gauge | < 85% | > 95% for 5m | | Inference latency p99 | Histogram | < 200ms | > 500ms | | Job completion rate | Counter | > 99% | < 95% per hour | | Pod restart count | Counter | 0 | > 3 in 15m | | Node GPU temperature | Gauge | < 80C | > 85C for 10m | ## Instrumentation ```typescript async function trackInference(model: string, fn: () => Promise<any>) { const start = Date.now(); try { const result = await fn(); metrics.record('coreweave.inference.latency',
- Overview
- Key Metrics
- Instrumentation
- Health Check Dashboard
- Alerting Rules
- Structured Logging
- Error Handling
- Resources
- Next Steps
What does the coreweave-observability skill do?
Set up GPU monitoring and observability for CoreWeave workloads. Use when implementing GPU metrics dashboards, configuring alerts, or tracking inference latency and throughput. Trigger with phrases like "coreweave monitoring", "coreweave observability", "coreweave gpu metrics", "coreweave grafana". '
How do I install it?
Run `npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill coreweave-observability --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From jeremylongshore/claude-code-plugins-plus-skills, a repository with 2,596 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.