/cloudflare-workers-observability

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

// 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**:

{
  "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

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

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