cloudflare-workers-observability
Cloudflare Workers observability with logging, Analytics Engine, Tail Workers, metrics, and alerting. Use for monitoring, debugging, tracing, or encountering log parsing, metric aggregation, alert configuration errors.
Works with
---
name: cloudflare-workers-observability
description: Cloudflare Workers observability with logging, Analytics Engine, Tail Workers, metrics, and alerting. Use for monitoring, debugging, tracing, or encountering log parsing, metric aggregation, alert configuration errors.
license: MIT
---
# Cloudflare Workers Observability
Production-grade observability for Cloudflare Workers: logging, metrics, tracing, and alerting.
## Quick Start
```typescript
// Structured logging with context
export default {
async fetch(request: Request, env: Env, ctx: ExecutionContext): Promise<Response> {
const requestId = crypto.randomUUID();
const logger = createLogger(requestId, env);
try {
logger.info('Request received', { method: request.method, url: request.url });
const result = await handleRequest(request, env);
logger.info('Request completed', { status: result.status });
return result;
} catch (error) {
logger.error('Request failed', { error: error.message, stack: error.stack });
throw error;
}
}
};
// Simple logger factory
function createLogger(requestId: string, env: Env) {
return {
info: (msg: string, data?: object) => console.log(JSON.stringify({ level: 'info', requestId, msg, ...data, timestamp: Date.now() })),
error: (msg: string, data?: object) => console.error(JSON.stringify({ level: 'error', requestId, msg, ...data, timestamp: Date.now() })),
warn: (msg: string, data?: object) => console.warn(JSON.stringify({ level: 'warn', requestId, msg, ...data, timestamp: Date.now() })),
};
}
```
## Critical Rules
1. **Always use structured JSON logging** - Plain text logs are hard to parse and aggregate
2. **Include request context** - Request ID, method, path in every log entry
3. **Never log sensitive data** - Redact tokens, passwords, PII from logs
4. **Use appropriate log levels** - ERROR for failures, WARN for recoverable issues, INFO for operations
5. **Sample high-volume logs** - Use 1-10% sampling for request logs in production
## Observability Components
| Component | Purpose | When to Use |
|-----------|---------|-------------|
| `console.log` | Basic logging | Development, debugging |
| **Tail Workers** | Real-time log streaming | Production log aggregation |
| **Analytics Engine** | Custom metrics/analytics | Business metrics, performance tracking |
| **Logpush** | Log export to external services | Long-term storage, compliance |
| **Workers Trace Events** | Distributed tracing | Request flow debugging |
## Top 8 Errors Prevented
| Error | Symptom | Prevention |
|-------|---------|------------|
| Logs not appearing | No output in dashboard | Enable "Standard" logging in wrangler.jsonc |
| Log truncation | Messages cut off at 128KB | Chunk large payloads, use sampling |
| Tail Worker not receiving | No events processed | Check binding name matches wrangler.jsonc |
| Analytics Engine write fails | Data not recorded | Verify AE binding, check blobs format |
| PII in logs | Security/compliance violation | Implement redaction middleware |
| Missing request context | Can't correlate logs | Add requestId to all log entries |
| Log volume explosion | High costs, noise | Implement sampling for high-frequency events |
| Alerting gaps | Incidents not detected | Configure monitors for error rate thresholds |
## Logging Configuration
**wrangler.jsonc**:
```jsonc
{
"name": "my-worker",
"observability": {
"enabled": true,
"head_sampling_rate": 1 // 0-1, 1 = 100% of requests
},
"tail_consumers": [
{
"service": "log-aggregator", // Tail Worker name
"environment": "production"
}
],
"analytics_engine_datasets": [
{
"binding": "ANALYTICS",
"dataset": "my_worker_metrics"
}
]
}
```
## Structured Logging Pattern
```typescript
interface LogEntry {
level: 'debug' | 'info' | 'warn' | 'error';
message: string;
requestId: string;
timestamp: number;
// Contextual data
method?: string;
path?: string;
status?: number;
duration?: number;
// Error details
error?: {
name: string;
message: string;
stack?: string;
};
// Custom fields
[key: string]: unknown;
}
class Logger {
constructor(private requestId: string, private baseContext: object = {}) {}
private log(level: LogEntry['level'], message: string, data?: object) {
const entry: LogEntry = {
level,
message,
requestId: this.requestId,
timestamp: Date.now(),
...this.baseContext,
...data,
};
// Redact sensitive fields
const sanitized = this.redact(entry);
const output = JSON.stringify(sanitized);
level === 'error' ? console.error(output) : console.log(output);
}
private redact(entry: LogEntry): LogEntry {
const sensitiveKeys = ['password', 'token', 'secret', 'authorization', 'cookie'];
const redacted = { ...entry };
for (const key of Object.keys(redacted)) {
if (sensitiveKeys.some(s => key.toLowerCase().includes(s))) {
redacted[key] = '[REDACTED]';
}
}
return redacted;
}
info(message: string, data?: object) { this.log('info', message, data); }
warn(message: string, data?: object) { this.log('warn', message, data); }
error(message: string, data?: object) { this.log('error', message, data); }
debug(message: string, data?: object) { this.log('debug', message, data); }
}
```
## Analytics Engine Usage
```typescript
interface Env {
ANALYTICS: AnalyticsEngineDataset;
}
export default {
async fetch(request: Request, env: Env, ctx: ExecutionContext): Promise<Response> {
const start = Date.now();
const url = new URL(request.url);
try {
const response = await handleRequest(request, env);
// Write success metric
env.ANALYTICS.writeDataPoint({
blobs: [request.method, url.pathname, String(response.status)],
doubles: [Date.now() - start], // Response time in ms
indexes: [url.pathname.split('/')[1] || 'root'], // Index for fast queries
});
return response;
} catch (error) {
// Write error metric
env.ANALYTICS.writeDataPoint({
blobs: [request.method, url.pathname, 'error', error.message],
doubles: [Date.now() - start],
indexes: ['error'],
});
throw error;
}
}
};
```
## Tail Worker Pattern
```typescript
// tail-worker.ts - Receives logs from other workers
interface TailEvent {
scriptName: string;
event: {
request?: { method: string; url: string };
response?: { status: number };
};
logs: Array<{
level: string;
message: unknown[];
timestamp: number;
}>;
exceptions: Array<{
name: string;
message: string;
timestamp: number;
}>;
outcome: 'ok' | 'exception' | 'exceededCpu' | 'exceededMemory' | 'canceled';
eventTimestamp: number;
}
export default {
async tail(events: TailEvent[], env: Env): Promise<void> {
for (const event of events) {
// Filter and forward logs
const errorLogs = event.logs.filter(l => l.level === 'error');
const exceptions = event.exceptions;
if (errorLogs.length > 0 || exceptions.length > 0) {
// Send to external logging service
await fetch(env.LOGGING_ENDPOINT, {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({
scriptName: event.scriptName,
timestamp: event.eventTimestamp,
errors: errorLogs,
exceptions,
outcome: event.outcome,
}),
});
}
}
}
};
```
## When to Load References
Load specific references based on the task:
- **Setting up logging?** → Load `references/logging.md` for structured logging patterns, log levels, redaction
- **Building custom metrics?** → Load `references/analytics-engine.md` for Analytics Engine SQL queries, data modeling
- **Implementing log aggregation?** → Load `references/tail-workers.md` for Tail Worker patterns, external service integration
- **Creating dashboards/tracking?** → Load `references/custom-metrics.md` for business metrics, performance tracking
- **Setting up alerts?** → Load `references/alerting.md` for error rate monitoring, PagerDuty/Slack integration
## Templates
| Template | Purpose | Use When |
|----------|---------|----------|
| `templates/logging-setup.ts` | Production logging class | Setting up new worker with logging |
| `templates/analytics-worker.ts` | Analytics Engine integration | Adding custom metrics |
| `templates/tail-worker.ts` | Complete Tail Worker | Building log aggregation pipeline |
## Scripts
| Script | Purpose | Command |
|--------|---------|---------|
| `scripts/setup-logging.sh` | Configure logging settings | `./setup-logging.sh` |
| `scripts/analyze-logs.sh` | Query and analyze logs | `./analyze-logs.sh --errors --last 1h` |
## Resources
- Workers Observability: https://developers.cloudflare.com/workers/observability/
- Analytics Engine: https://developers.cloudflare.com/analytics/analytics-engine/
- Tail Workers: https://developers.cloudflare.com/workers/observability/tail-workers/
- Logpush: https://developers.cloudflare.com/logs/get-started/More Debugging skills
diagnosing-bugs
mattpocock/skills
Diagnosis loop for hard bugs and performance regressions. Use when the user says "diagnose"/"debug this", or reports something broken/throwing/failing/slow.
explore-code
lllllllama/rigorpilot-skills
Rigor Improve implementation leaf skill for auditable candidate implementation in deep learning research repositories. Use when the researcher explicitly authorizes exploratory work on an isolated branch or worktree to transplant modules, adapt a backbone, add LoRA or adapter layers, replace a head, or stitch together meaningful low-risk migration ideas with rollback-aware records in `explore_outputs/`. Do not use for end-to-end exploration orchestration on top of `current_research`, trusted baseline reproduction, conservative debugging, environment setup, verified contribution claims, or default repository analysis.
safe-debug
lllllllama/rigorpilot-skills
Rigor Debug / Rigor Audit skill for deep learning research work. Use when the user pastes a traceback, terminal error, CUDA OOM, checkpoint load failure, shape mismatch, NaN loss symptom, or training failure and wants conservative diagnosis before any patching, with debug fixes clearly separated from research contributions. Do not use for broad refactoring, speculative adaptation, automatic exploratory patching, or general repository familiarization.

