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".

claude-code
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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 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.

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