Logging & Error Tracking Expert (2026 Edition)

English | Bahasa Indonesia

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<a name="english"></a>

English

Orchestration & Integration

Connects and orchestrates with relevant domain skills like brainstorming, zero-to-prod-orchestrator, and session-memory-manager to ensure cohesive execution.

Description

Production-grade guide for implementing structured logging, error tracking, and application monitoring. Covers Pino (high-performance JSON logging), Sentry SDK integration (React, Node.js, Next.js), source map upload for production errors, request ID correlation across microservices, log aggregation (Axiom, Datadog, Logflare), alert rules, GDPR-compliant log redaction (PII masking), and OpenTelemetry integration.

Trigger Conditions

Activate this skill when:

• Setting up structured logging for Node.js/Bun backend services.
• Integrating Sentry for error tracking in React/Next.js apps.
• Implementing request ID correlation across microservices.
• Setting up log aggregation and search (Axiom, Datadog, Grafana Loki).
• Configuring alerting rules for production errors.
• Implementing GDPR-compliant log management (PII redaction).
• Setting up source map uploads for production debugging.

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Logging Library Selection Guide

Library	Best For	Performance	Output Format
Pino	High-throughput Node.js services	⭐⭐⭐⭐⭐ (fastest)	JSON (structured)
Winston	Enterprise, multiple transports	⭐⭐⭐	Configurable
Bunyan	Legacy projects	⭐⭐⭐⭐	JSON
console.log	Never in production	❌	Unstructured

Recommendation: Use Pino for all production services (10x faster than Winston, native JSON).

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1. Structured Logging with Pino

// lib/logger.ts
import pino from 'pino';

export const logger = pino({
  level: process.env.LOG_LEVEL ?? 'info',
  // Redact sensitive fields (GDPR/PII)
  redact: {
    paths: ['req.headers.authorization', 'req.headers.cookie', '*.password', '*.token', '*.ssn', '*.creditCard'],
    censor: '[REDACTED]',
  },
  // Standardized format
  formatters: {
    level: (label) => ({ level: label }),
    bindings: (bindings) => ({
      service: process.env.SERVICE_NAME ?? 'app',
      environment: process.env.NODE_ENV,
      version: process.env.APP_VERSION,
      pid: bindings.pid,
      hostname: bindings.hostname,
    }),
  },
  timestamp: pino.stdTimeFunctions.isoTime,
});

// Child logger for specific domain
export const dbLogger = logger.child({ module: 'database' });
export const authLogger = logger.child({ module: 'auth' });
export const paymentLogger = logger.child({ module: 'payment' });

Log Level Strategy

// When to use each level:
logger.fatal('Application cannot start — exiting');       // Process crash
logger.error({ err }, 'Payment processing failed');        // Failed operations (needs attention)
logger.warn('Rate limit threshold at 80%');                // Degraded state, approaching limits
logger.info({ userId, action: 'login' }, 'User logged in'); // Business events, audit trail
logger.debug({ query, params }, 'Database query executed'); // Development troubleshooting
logger.trace({ request }, 'Incoming request');              // Extreme detail (rarely enabled)

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2. Request ID Correlation

// middleware/request-id.ts
import { randomUUID } from 'crypto';
import { AsyncLocalStorage } from 'async_hooks';

// Async context for request correlation
export const requestContext = new AsyncLocalStorage<{ requestId: string }>();

export function requestIdMiddleware(req: Request): string {
  // Use incoming header or generate new ID
  const requestId = req.headers.get('x-request-id') ?? randomUUID();

  // Propagate to downstream services
  return requestId;
}

// Usage with Pino child logger
export function getRequestLogger() {
  const ctx = requestContext.getStore();
  return ctx ? logger.child({ requestId: ctx.requestId }) : logger;
}

// In API route
export async function GET(request: Request) {
  const requestId = requestIdMiddleware(request);

  return requestContext.run({ requestId }, async () => {
    const log = getRequestLogger();
    log.info('Processing request');

    // All downstream log calls include requestId automatically
    const result = await fetchData(log);
    return Response.json(result);
  });
}

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3. Sentry Integration (Next.js)

// sentry.client.config.ts
import * as Sentry from '@sentry/nextjs';

Sentry.init({
  dsn: process.env.NEXT_PUBLIC_SENTRY_DSN,
  environment: process.env.NODE_ENV,
  release: process.env.SENTRY_RELEASE,

  // Performance monitoring
  tracesSampleRate: process.env.NODE_ENV === 'production' ? 0.1 : 1.0,

  // Session replay for debugging
  replaysSessionSampleRate: 0.01, // 1% of sessions
  replaysOnErrorSampleRate: 1.0,   // 100% of error sessions

  integrations: [
    Sentry.replayIntegration({ maskAllText: false, blockAllMedia: false }),
  ],

  // Filter noise
  ignoreErrors: [
    'ResizeObserver loop',
    'Non-Error promise rejection',
    /Loading chunk \d+ failed/,
  ],

  // Scrub PII before sending
  beforeSend(event) {
    if (event.user) {
      delete event.user.ip_address;
      delete event.user.email; // Or hash it
    }
    return event;
  },
});

// sentry.server.config.ts
import * as Sentry from '@sentry/nextjs';

Sentry.init({
  dsn: process.env.SENTRY_DSN,
  tracesSampleRate: 0.1,

  // Capture unhandled promise rejections
  integrations: [
    Sentry.prismaIntegration(), // Auto-track Prisma queries
  ],
});

Source Map Upload (CI/CD)

# .github/workflows/deploy.yml
- name: Upload Source Maps to Sentry
  env:
    SENTRY_AUTH_TOKEN: ${{ secrets.SENTRY_AUTH_TOKEN }}
    SENTRY_ORG: your-org
    SENTRY_PROJECT: your-project
  run: |
    npx @sentry/cli sourcemaps upload \
      --release=${{ github.sha }} \
      .next/static

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4. Log Aggregation Setup (Axiom)

// lib/axiom-transport.ts
import { pino } from 'pino';

// Pino transport for Axiom (or any HTTP log service)
const transport = pino.transport({
  targets: [
    // Console output (development)
    { target: 'pino-pretty', level: 'debug' },
    // Axiom (production)
    {
      target: '@axiomhq/pino',
      level: 'info',
      options: {
        dataset: process.env.AXIOM_DATASET,
        token: process.env.AXIOM_TOKEN,
      },
    },
  ],
});

export const logger = pino(transport);

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5. Alert Rules Configuration

// Example alert conditions to configure in your monitoring tool
const ALERT_RULES = {
  criticalErrors: {
    condition: 'error count > 50 in 5 minutes',
    severity: 'critical',
    notification: ['pagerduty', 'slack'],
  },
  highErrorRate: {
    condition: 'error rate > 5% of total requests',
    severity: 'high',
    notification: ['slack'],
  },
  slowResponses: {
    condition: 'p99 response time > 3000ms for 10 minutes',
    severity: 'medium',
    notification: ['slack'],
  },
  diskSpace: {
    condition: 'disk usage > 85%',
    severity: 'warning',
    notification: ['email'],
  },
};

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6. GDPR-Compliant Log Management

// lib/pii-redactor.ts

/** Fields that must be redacted in logs */
const PII_PATTERNS = [
  /\b\d{3}-\d{2}-\d{4}\b/g,           // SSN
  /\b\d{4}[\s-]?\d{4}[\s-]?\d{4}[\s-]?\d{4}\b/g, // Credit card
  /\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}\b/g, // Email
];

export function redactPII(text: string): string {
  let result = text;
  for (const pattern of PII_PATTERNS) {
    result = result.replace(pattern, '[REDACTED]');
  }
  return result;
}

// Log retention policy
const LOG_RETENTION = {
  debug: '7 days',
  info: '30 days',
  warn: '90 days',
  error: '365 days',
  audit: '7 years', // Compliance requirement
};

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Common Pitfalls to Avoid

Anti-Pattern	Problem	Correct Approach
console.log in production	Unstructured, no levels, no rotation	Use Pino with JSON output
Logging PII (emails, passwords)	GDPR violation, security risk	Use Pino redact option
No request correlation ID	Can't trace requests across services	Propagate x-request-id header
Logging everything at info level	Log noise, storage waste	Use appropriate levels (debug/info/warn/error)
No source maps in production errors	"Minified React error #xxx"	Upload source maps to Sentry
No log rotation/retention policy	Disk fills up, storage costs grow	Set TTL per level, archive old logs
Alerting on every error	Alert fatigue	Set meaningful thresholds and severity levels

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Integration with Other Skills

• data-telemetry-expert — OpenTelemetry spans + log correlation
• error-resilience-expert — Error tracking and monitoring setup
• js-backend-expert — Server-side logging middleware (Fastify/Hono/Express)
• ci-cd-devops-architect — Source map upload in CI/CD pipeline
• production-ready-hardener — Pre-launch logging and monitoring audit
• zero-trust-secret-vault — Secure logging of secret access patterns

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<a name="bahasa-indonesia"></a>

Bahasa Indonesia

Integrasi Orkestrasi

Terhubung dan mengorkestrasi skill domain yang relevan seperti brainstorming, zero-to-prod-orchestrator, dan session-memory-manager untuk memastikan eksekusi yang kohesif.

Deskripsi

Panduan tingkat produksi untuk mengimplementasikan logging terstruktur, pelacakan error, dan pemantauan aplikasi. Mencakup Pino (logging JSON berkinerja tinggi), integrasi SDK Sentry (React, Node.js, Next.js), upload source map untuk error produksi, korelasi request ID lintas microservice, agregasi log (Axiom, Datadog, Logflare), aturan alerting, redaksi log sesuai GDPR (masking PII), dan integrasi OpenTelemetry.

Kondisi Pemicu

Aktifkan skill ini ketika:

• Menyiapkan logging terstruktur untuk layanan backend Node.js/Bun.
• Mengintegrasikan Sentry untuk pelacakan error di aplikasi React/Next.js.
• Mengimplementasikan korelasi request ID lintas microservice.
• Menyiapkan agregasi dan pencarian log (Axiom, Datadog, Grafana Loki).
• Mengonfigurasi aturan alerting untuk error produksi.
• Mengimplementasikan manajemen log sesuai GDPR (redaksi PII).

Integrasi dengan Skill Lain

• data-telemetry-expert — Span OpenTelemetry + korelasi log
• error-resilience-expert — Setup pelacakan error dan monitoring
• js-backend-expert — Middleware logging sisi server (Fastify/Hono/Express)
• ci-cd-devops-architect — Upload source map dalam pipeline CI/CD
• production-ready-hardener — Audit logging dan monitoring pra-peluncuran