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.
git clone --depth 1 https://github.com/secondsky/claude-skills /tmp/cloudflare-workers-observability && cp -r /tmp/cloudflare-workers-observability/plugins/cloudflare-workers/skills/cloudflare-workers-observability ~/.claude/skills/cloudflare-workers-observabilitySKILL.md
# 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'],
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