Add Logging and Monitoring for PDF Generation

[yusuftomilola]

Implement detailed logging and monitoring to track usage, errors, and performance of the PDF generation API.

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Details

• Log each request with metadata:

  • User ID
  • Input type (HTML/Markdown)
  • Input size
  • Timestamp
  • Processing duration
  • Success/failure status

• Log detailed error info on failures:

  • Stack traces
  • Input snippets (if safe)

• Integrate with centralized logging system (e.g., ELK stack, Datadog, or similar).

• Set up monitoring dashboards and alerts for:

  • Error rate spikes
  • Latency issues
  • Throughput drops

• Ensure logs respect user privacy and avoid logging sensitive info.

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Subtasks

• Implement structured logging for API and service layers.
• Configure monitoring and alerting tools.
• Test logging under normal and failure conditions.

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Acceptance Criteria

• Logs capture detailed info per request.
• Monitoring dashboards display key metrics and alerts.
• Logs and metrics help diagnose production issues.

[clintjeff2]

Hello, I'm Jefferson, a backend engineer from Cameroon specializing in scalable, secure backend systems. My tech stack includes NestJS, Express, TypeScript, Node.js, PostgreSQL, and modern logging/monitoring stacks like Winston, ELK, and Datadog. I emphasize observability, privacy, and performance across all services.

I’m available to implement detailed logging and monitoring for the PDF generation API. This will provide actionable insights into system health, performance bottlenecks, and error diagnostics. Below is my approach:

Implementation Plan

1. Structured Logging Setup

• Use Winston with NestJS Logger integration or Pino for high-performance logging.
• Configure logs in JSON format with fields:
  • userId (if authenticated)
  • inputType: "html" or "markdown"
  • inputSize: computed from raw request body
  • timestamp: ISO format
  • durationMs: time from request entry to response send
  • status: success or error
• Add middleware/interceptor to time each request and append the duration.

2. Error Logging Enhancements

• On failure, log:
  • Error message and full stack trace
  • Partial input snippet (safely truncated and sanitized)
  • HTTP method and endpoint path
• Mask or omit sensitive data (e.g., access tokens, PII).
• Classify logs by severity (info, warn, error, fatal) for filtering.

3. Centralized Logging Integration

• Forward logs to centralized system:
  • Option 1: Use Filebeat to ship logs to ELK Stack.
  • Option 2: Use Datadog agent with Winston transport.
  • Include context tags like service:pdf, env:production, region.

4. Testing & Privacy Assurance

• Simulate normal and faulty request flows to verify logging consistency.
• Confirm that large or malformed payloads don’t flood logs.
• Review all logs to ensure no sensitive information is stored.

Deliverables

• Structured, privacy-compliant request and error logs
• Monitoring dashboard setup with real-time metrics and alerts
• Automated tests validating logging under success and failure
• Configurable transports for local dev, staging, and production

Timeline

Estimated completion: 40 hours
Telegram: @JeffersonYouashi

Let me know if you’d like to assign me.

[yusuftomilola]

Hi @clintjeff2 Kindly hold on a little. This issue is blocked and depends on other issues. Will let you know in your telegram when you can proceed.

[yusuftomilola]

@clintjeff2 You can proceed on this