100+ animated React components (Aceternity UI) for Next.js with Tailwind. Use for hero sections, parallax, 3D effects, or encountering animation, shadcn CLI integration errors.
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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.
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설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Production-grade observability for Cloudflare Workers: logging, metrics, tracing, and alerting.
// 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() })),
};
}
| 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 |
| 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 |
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"
}
]
}
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); }
}
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.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,
}),
});
}
}
}
};
Load specific references based on the task:
references/logging.md for structured logging patterns, log levels, redactionreferences/analytics-engine.md for Analytics Engine SQL queries, data modelingreferences/tail-workers.md for Tail Worker patterns, external service integrationreferences/custom-metrics.md for business metrics, performance trackingreferences/alerting.md for error rate monitoring, PagerDuty/Slack integration| 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 |
| 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 |
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100+ animated React components (Aceternity UI) for Next.js with Tailwind. Use for hero sections, parallax, 3D effects, or encountering animation, shadcn CLI integration errors.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Secure API authentication with JWT, OAuth 2.0, API keys. Use for authentication systems, third-party integrations, service-to-service communication, or encountering token management, security headers, auth flow errors.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Creates comprehensive API changelogs documenting breaking changes, deprecations, and migration strategies for API consumers. Use when managing API versions, communicating breaking changes, or creating upgrade guides.
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Verifies API contracts between services using consumer-driven contracts, schema validation, and tools like Pact. Use when testing microservices communication, preventing breaking changes, or validating OpenAPI specifications.
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Master REST and GraphQL API design principles to build intuitive, scalable, and maintainable APIs that delight developers. Use when designing new APIs, reviewing API specifications, or establishing API design standards.
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Implements standardized API error responses with proper status codes, logging, and user-friendly messages. Use when building production APIs, implementing error recovery patterns, or integrating error monitoring services.
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