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169 lines
3.5 KiB
Markdown
169 lines
3.5 KiB
Markdown
## Configuration Patterns
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### Enable Workers Logs
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```jsonc
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{
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"observability": {
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"enabled": true,
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"head_sampling_rate": 1 // 100% sampling (default)
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}
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}
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```
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**Best Practice**: Use structured JSON logging for better indexing
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```typescript
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// Good - structured logging
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console.log({
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user_id: 123,
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action: "login",
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status: "success",
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duration_ms: 45
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});
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// Avoid - unstructured string
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console.log("user_id: 123 logged in successfully in 45ms");
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```
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### Enable Workers Traces
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```jsonc
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{
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"observability": {
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"traces": {
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"enabled": true,
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"head_sampling_rate": 0.05 // 5% sampling
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}
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}
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}
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```
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**Note**: Default sampling is 100%. For high-traffic Workers, use lower sampling (0.01-0.1).
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### Configure Analytics Engine
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**Bind to Worker**:
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```toml
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# wrangler.toml
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analytics_engine_datasets = [
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{ binding = "ANALYTICS", dataset = "api_metrics" }
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]
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```
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**Write Data Points**:
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```typescript
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export interface Env {
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ANALYTICS: AnalyticsEngineDataset;
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}
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export default {
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async fetch(request: Request, env: Env): Promise<Response> {
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// Track metrics
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env.ANALYTICS.writeDataPoint({
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blobs: ['customer_123', 'POST', '/api/v1/users'],
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doubles: [1, 245.5], // request_count, response_time_ms
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indexes: ['customer_123'] // for efficient filtering
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});
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return new Response('OK');
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}
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}
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```
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### Configure Tail Workers
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Tail Workers receive logs/traces from other Workers for filtering, transformation, or export.
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**Setup**:
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```toml
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# wrangler.toml
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name = "log-processor"
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main = "src/tail.ts"
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[[tail_consumers]]
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service = "my-worker" # Worker to tail
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```
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**Tail Worker Example**:
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```typescript
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export default {
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async tail(events: TraceItem[], env: Env, ctx: ExecutionContext) {
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// Filter errors only
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const errors = events.filter(event =>
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event.outcome === 'exception' || event.outcome === 'exceededCpu'
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);
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if (errors.length > 0) {
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// Send to external monitoring
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ctx.waitUntil(
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fetch('https://monitoring.example.com/errors', {
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method: 'POST',
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body: JSON.stringify(errors)
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})
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);
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}
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}
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}
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```
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### Configure Logpush
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Send logs to external storage (S3, R2, GCS, Azure, Datadog, etc.). Requires Business/Enterprise plan.
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**Via Dashboard**:
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1. Navigate to Analytics → Logs → Logpush
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2. Select destination type
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3. Provide credentials and bucket/endpoint
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4. Choose dataset (e.g., Workers Trace Events)
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5. Configure filters and fields
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**Via API**:
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```bash
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curl -X POST "https://api.cloudflare.com/client/v4/accounts/{account_id}/logpush/jobs" \
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-H "Authorization: Bearer <API_TOKEN>" \
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-H "Content-Type: application/json" \
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-d '{
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"name": "workers-logs-to-s3",
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"destination_conf": "s3://my-bucket/logs?region=us-east-1",
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"dataset": "workers_trace_events",
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"enabled": true,
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"frequency": "high",
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"filter": "{\"where\":{\"and\":[{\"key\":\"ScriptName\",\"operator\":\"eq\",\"value\":\"my-worker\"}]}}"
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}'
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```
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### Environment-Specific Configuration
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**Development** (verbose logs, full sampling):
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```jsonc
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// wrangler.dev.jsonc
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{
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"observability": {
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"enabled": true,
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"head_sampling_rate": 1.0,
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"traces": {
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"enabled": true
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}
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}
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}
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```
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**Production** (reduced sampling, structured logs):
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```jsonc
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// wrangler.prod.jsonc
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{
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"observability": {
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"enabled": true,
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"head_sampling_rate": 0.1, // 10% sampling
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"traces": {
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"enabled": true
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}
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}
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}
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```
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Deploy with env-specific config:
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```bash
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wrangler deploy --config wrangler.prod.jsonc --env production
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``` |