Advanced Monitoring & Observability in Spring Boot

1️⃣ Introduction

Advanced monitoring and observability are crucial for maintaining and optimizing Spring Boot applications. This article explores various monitoring tools and techniques for comprehensive application insights.

Key features include:

  • Micrometer metrics collection
  • Prometheus integration
  • Custom metrics implementation
  • Log aggregation
  • Distributed tracing

2️⃣ Key Concepts & Terminology

  • Micrometer: Metrics collection library
  • Prometheus: Monitoring and alerting toolkit
  • Custom Metrics: Application-specific measurements
  • Log Aggregation: Centralized log collection
  • Distributed Tracing: Request flow tracking

3️⃣ Hands-on Implementation 🛠

🔹 Step 1: Micrometer Configuration

@Configuration
public class MetricsConfig {
    @Bean
    MeterRegistry meterRegistry() {
        return new SimpleMeterRegistry();
    }

    @Bean
    TimedAspect timedAspect(MeterRegistry registry) {
        return new TimedAspect(registry);
    }

    @Bean
    CountedAspect countedAspect(MeterRegistry registry) {
        return new CountedAspect(registry);
    }
}

@Service
public class UserService {
    private final MeterRegistry registry;

    public UserService(MeterRegistry registry) {
        this.registry = registry;
    }

    @Timed(value = "user.creation", description = "Time taken to create user")
    public User createUser(User user) {
        Counter counter = registry.counter("user.created");
        User saved = userRepository.save(user);
        counter.increment();
        return saved;
    }
}

🔹 Step 2: Prometheus Integration

@Configuration
public class PrometheusConfig {
    @Bean
    PrometheusProperties prometheusProperties() {
        return new PrometheusProperties();
    }

    @Bean
    PrometheusMeterRegistry prometheusMeterRegistry() {
        return new PrometheusMeterRegistry(PrometheusConfig.DEFAULT);
    }
}

// application.properties
management.endpoints.web.exposure.include=prometheus,health,info
management.endpoint.prometheus.enabled=true
management.metrics.tags.application=my-application

🔹 Step 3: Custom Metrics

@Component
public class CustomMetrics {
    private final MeterRegistry registry;
    private final Gauge activeUsers;
    private final Counter failedLogins;

    public CustomMetrics(MeterRegistry registry) {
        this.registry = registry;
        
        this.activeUsers = Gauge.builder("users.active", 
            userService, this::getActiveUserCount)
            .description("Number of active users")
            .register(registry);

        this.failedLogins = Counter.builder("auth.failed")
            .description("Number of failed login attempts")
            .register(registry);
    }

    private double getActiveUserCount(UserService userService) {
        return userService.getActiveUserCount();
    }

    public void recordFailedLogin() {
        failedLogins.increment();
    }
}

4️⃣ Common Issues & Debugging 🐞

Common Issues and Solutions

Issue Solution
Metrics not showing Check endpoint exposure and security configuration
High memory usage Configure proper metric retention and sampling
Missing custom metrics Verify metric registration and naming

5️⃣ Q&A / Frequently Asked Questions

Metrics are numerical measurements collected over time, while logs are detailed event records. Metrics are better for monitoring and alerting, while logs are better for debugging and auditing.

Use counters for monotonically increasing values, gauges for current values, and timers for duration measurements. Consider the nature of the data and how it will be used for monitoring.

6️⃣ Best Practices & Pro Tips 🚀

  • Use meaningful metric names
  • Implement proper tagging
  • Configure appropriate retention
  • Monitor metric cardinality
  • Set up proper alerts
  • Regular metric review

7️⃣ Read Next 📖

8️⃣ Conclusion

Advanced monitoring and observability are essential for maintaining healthy Spring Boot applications. Understanding metrics collection, custom metrics, and proper configuration is crucial for effective monitoring.

Remember to implement comprehensive monitoring strategies, use appropriate metrics, and follow best practices for monitoring and alerting.