Skip to content
advanced Phase · Observability

Distributed Tracing

Trace requests across multiple services with trace IDs.

45m
0 problems
Topic Progress 0%

Distributed Tracing

How It Works

Request → Service A → Service B → Service C
Trace ID: abc-123 (same across all services)

Service A span: [-------]
Service B span:   [-------]
Service C span:     [-------]

Implementation

// Trace ID in logs
log.info("Processing order", kv("traceId", MDC.get("traceId")));

// Propagate trace across services
RestTemplate template = new RestTemplate();
template.setInterceptors((req, body, exec) -> {
    req.getHeaders().add("X-Trace-Id", MDC.get("traceId"));
    return exec.execute(req, body);
});

Best Practices

Key Principles

  1. Follow SOLID principles
  2. Write clean, readable code
  3. Test thoroughly
  4. Document decisions
  5. Monitor in production

Implementation

  • Start simple, refactor as needed
  • Use established patterns
  • Consider trade-offs
  • Review with peers

Continuous Improvement

  • Learn from incidents
  • Update documentation
  • Share knowledge
  • Mentor others

Key Points

  • Understanding Distributed Tracing is essential for production systems
  • Always consider scalability and maintainability
  • Test thoroughly before deploying to production
  • Monitor performance and set up alerting

Common Patterns

  1. Validation: Always validate input at the boundary
  2. Error Handling: Use structured error responses
  3. Logging: Log key events for debugging
  4. Testing: Unit, integration, and load tests
  5. Documentation: Keep docs updated with code changes

Practice Problems

0 / 3 solved
Implement Distributed Tracing

Design and implement a solution for Distributed Tracing in a backend system. Consider scalability, error handling, and production readiness.

Solution 
// Distributed Tracing implementation
// Key aspects: validation, error handling, logging, testing

public class DistributedTracing {
    // Production-ready implementation
}
Distributed Tracing Edge Cases

Identify and handle edge cases for Distributed Tracing. What happens under high load, with invalid input, or during failures?

Solution 
// Edge case handling:
// 1. Null/empty input -> validation
// 2. High load -> rate limiting, queuing
// 3. Failures -> retries, circuit breaker
// 4. Concurrent access -> locks, idempotency
Distributed Tracing Testing Strategy

Write a testing strategy for Distributed Tracing. Include unit tests, integration tests, and performance tests.

Solution 
// Test plan:
// - Unit: 80% coverage target
// - Integration: API contracts
// - Performance: latency, throughput
// - Chaos: failure injection

Quiz

1. Distributed tracing uses?

Question 1 options

2. Trace ID propagates via?

Question 2 options

3. What is a common mistake when implementing Distributed Tracing?

Question 3 options

Flashcards

Question

Distributed tracing uses?

Click to reveal answer

Answer

Trace IDs across services

Question

Trace ID propagation?

Click to reveal answer

Answer

HTTP headers (X-Trace-Id)

Question

Distributed Tracing best practices

Click to reveal answer

Answer

Follow SOLID principles, write clean code, test thoroughly, document decisions, and monitor in production.

Revision Notes

Key Takeaways

  • 1. Trace ID correlates requests across services
  • 2. Propagate via HTTP headers
  • 3. Each service creates a span
  • 4. Tools: Jaeger, Zipkin, AWS X-Ray

Interview Tips

  • • Implement distributed tracing
  • • Use correlation IDs

Cheat Sheet

Distributed Tracing

  • Trace ID across services
  • Propagate: HTTP headers
  • Each service: span
  • Tools: Jaeger, Zipkin, X-Ray