coreweave-observability
Set up comprehensive observability for CoreWeave integrations with metrics, traces, and alerts. Use when implementing monitoring for CoreWeave operations, setting up dashboards, or configuring alerting for CoreWeave integration health. Trigger with phrases like "coreweave monitoring", "coreweave metrics", "coreweave observability", "monitor coreweave", "coreweave alerts", "coreweave tracing".
Allowed Tools
Provided by Plugin
coreweave-pack
Claude Code skill pack for CoreWeave (24 skills)
Installation
This skill is included in the coreweave-pack plugin:
/plugin install coreweave-pack@claude-code-plugins-plus
Click to copy
Instructions
CoreWeave Observability
Overview
Set up comprehensive observability for CoreWeave integrations.
Prerequisites
- Prometheus or compatible metrics backend
- OpenTelemetry SDK installed
- Grafana or similar dashboarding tool
- AlertManager configured
Metrics Collection
Key Metrics
| Metric | Type | Description |
|---|---|---|
coreweaverequeststotal |
Counter | Total API requests |
coreweaverequestduration_seconds |
Histogram | Request latency |
coreweaveerrorstotal |
Counter | Error count by type |
coreweaveratelimit_remaining |
Gauge | Rate limit headroom |
Prometheus Metrics
import { Registry, Counter, Histogram, Gauge } from 'prom-client';
const registry = new Registry();
const requestCounter = new Counter({
name: 'coreweave_requests_total',
help: 'Total CoreWeave API requests',
labelNames: ['method', 'status'],
registers: [registry],
});
const requestDuration = new Histogram({
name: 'coreweave_request_duration_seconds',
help: 'CoreWeave request duration',
labelNames: ['method'],
buckets: [0.05, 0.1, 0.25, 0.5, 1, 2.5, 5],
registers: [registry],
});
const errorCounter = new Counter({
name: 'coreweave_errors_total',
help: 'CoreWeave errors by type',
labelNames: ['error_type'],
registers: [registry],
});
Instrumented Client
async function instrumentedRequest<T>(
method: string,
operation: () => Promise<T>
): Promise<T> {
const timer = requestDuration.startTimer({ method });
try {
const result = await operation();
requestCounter.inc({ method, status: 'success' });
return result;
} catch (error: any) {
requestCounter.inc({ method, status: 'error' });
errorCounter.inc({ error_type: error.code || 'unknown' });
throw error;
} finally {
timer();
}
}
Distributed Tracing
OpenTelemetry Setup
import { trace, SpanStatusCode } from '@opentelemetry/api';
const tracer = trace.getTracer('coreweave-client');
async function tracedCoreWeaveCall<T>(
operationName: string,
operation: () => Promise<T>
): Promise<T> {
return tracer.startActiveSpan(`coreweave.${operationName}`, async (span) => {
try {
const result = await operation();
span.setStatus({ code: SpanStatusCode.OK });
return result;
} catch (error: any) {
span.setStatus({ code: SpanStatusCode.ERROR, message: error.message });
span.recordException(error);
throw error;
} finally {
span.end();
}
});
}
Logging Strategy
Structured Logging
import pino from 'pino';
const logger = pino({
name: 'coreweave',
level: process.env.LOG_LEVEL || 'info',
});
function logCoreWeaveOperation(
operation: string,
data: Record<string, any>,
duration: number
) {
logger.info({
service: 'coreweave',
operation,
duration_ms: duration,
...data,
});
}
Alert Configuration
Prometheus AlertManager Rules
# coreweave_alerts.yaml
groups:
- name: coreweave_alerts
rules:
- alert: CoreWeaveHighErrorRate
expr: |
rate(coreweave_errors_total[5m]) /
rate(coreweave_requests_total[5m]) > 0.05
for: 5m
labels:
severity: warning
annotations:
summary: "CoreWeave error rate > 5%"
- alert: CoreWeaveHighLatency
expr: |
histogram_quantile(0.95,
rate(coreweave_request_duration_seconds_bucket[5m])
) > 2
for: 5m
labels:
severity: warning
annotations:
summary: "CoreWeave P95 latency > 2s"
- alert: CoreWeaveDown
expr: up{job="coreweave"} == 0
for: 1m
labels:
severity: critical
annotations:
summary: "CoreWeave integration is down"
Dashboard
Grafana Panel Queries
{
"panels": [
{
"title": "CoreWeave Request Rate",
"targets": [{
"expr": "rate(coreweave_requests_total[5m])"
}]
},
{
"title": "CoreWeave Latency P50/P95/P99",
"targets": [{
"expr": "histogram_quantile(0.5, rate(coreweave_request_duration_seconds_bucket[5m]))"
}]
}
]
}
Instructions
Step 1: Set Up Metrics Collection
Implement Prometheus counters, histograms, and gauges for key operations.
Step 2: Add Distributed Tracing
Integrate OpenTelemetry for end-to-end request tracing.
Step 3: Configure Structured Logging
Set up JSON logging with consistent field names.
Step 4: Create Alert Rules
Define Prometheus alerting rules for error rates and latency.
Output
- Metrics collection enabled
- Distributed tracing configured
- Structured logging implemented
- Alert rules deployed
Error Handling
| Issue | Cause | Solution |
|---|---|---|
| Missing metrics | No instrumentation | Wrap client calls |
| Trace gaps | Missing propagation | Check context headers |
| Alert storms | Wrong thresholds | Tune alert rules |
| High cardinality | Too many labels | Reduce label values |
Examples
Quick Metrics Endpoint
app.get('/metrics', async (req, res) => {
res.set('Content-Type', registry.contentType);
res.send(await registry.metrics());
});
Resources
Next Steps
For incident response, see coreweave-incident-runbook.