Monitoring
Monitoring Stack
Application → Micrometer → Prometheus → Grafana
→ Alertmanager → PagerDuty
SLA Metrics
| Metric | SLA |
|---|---|
| Availability | 99.9% (8.76 hrs downtime/year) |
| Latency p99 | < 200ms |
| Error rate | < 0.1% |
Key Points
- Understanding Monitoring is essential for production systems
- Always consider scalability and maintainability
- Test thoroughly before deploying to production
- Monitor performance and set up alerting
Common Patterns
- Validation: Always validate input at the boundary
- Error Handling: Use structured error responses
- Logging: Log key events for debugging
- Testing: Unit, integration, and load tests
- Documentation: Keep docs updated with code changes
Monitoring Best Practices
Three Pillars
- Metrics: Quantitative data
- Logs: Event records
- Traces: Request flow
Key Metrics
- Request rate
- Error rate
- Latency (p50, p95, p99)
- Saturation
Alerting
- Actionable alerts
- Appropriate severity
- Escalation policies
- Avoid alert fatigue
Key Points
- Understanding Monitoring is essential for production systems
- Always consider scalability and maintainability
- Test thoroughly before deploying to production
- Monitor performance and set up alerting
Common Patterns
- Validation: Always validate input at the boundary
- Error Handling: Use structured error responses
- Logging: Log key events for debugging
- Testing: Unit, integration, and load tests
- Documentation: Keep docs updated with code changes
Practice Problems
Design and implement a solution for Monitoring in a backend system. Consider scalability, error handling, and production readiness.
Solution
// Monitoring implementation
// Key aspects: validation, error handling, logging, testing
public class Monitoring {
// Production-ready implementation
}Identify and handle edge cases for Monitoring. 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, idempotencyWrite a testing strategy for Monitoring. Include unit tests, integration tests, and performance tests.
Solution
// Test plan:
// - Unit: 80% coverage target
// - Integration: API contracts
// - Performance: latency, throughput
// - Chaos: failure injectionQuiz
1. 99.9% availability means?
2. Grafana does what?
3. What is the primary purpose of Monitoring?
4. What is a common mistake when implementing Monitoring?
Flashcards
Question
99.9% availability?
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Answer
8.76 hours downtime per year
Question
Grafana purpose?
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Answer
Visualize metrics in dashboards
Question
What is Monitoring?
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Answer
Monitoring is a key concept in backend development.
Question
When to use Monitoring?
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Answer
Use Monitoring when building production systems that require reliability, scalability, and maintainability.
Question
Monitoring best practices
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Answer
Follow SOLID principles, write clean code, test thoroughly, document decisions, and monitor in production.
Revision Notes
Key Takeaways
- 1.Micrometer → Prometheus → Grafana stack
- 2.Define SLAs: availability, latency, error rate
- 3.Create dashboards for key metrics
- 4.Alert on SLA violations
Interview Tips
- •Set up monitoring
- •Define SLAs
Cheat Sheet
Monitoring
- Stack: Micrometer → Prometheus → Grafana
- SLAs: 99.9% avail, < 200ms p99, < 0.1% errors
- Dashboards: key metrics
- Alerting: on SLA violations