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This tutorial on Spring Boot Actuator Metrics is part of a Spring Actuators playlist. The full set of Actuator tutorials are available here: FULL SPRING ACTUATOR COURSE PLAYLIST https://youtu.be/RQb2mrslq3k?si=0KfxxKwzDevdFnin SHORT INTRO https://youtu.be/RQb2mrslq3k ACTUATOR MAVEN DEPENDENCY https://youtu.be/ba3GKC0NEDE HOW TO EXPOSE AND ENABLE ACTUATOR ENDPOINTS https://youtu.be/7CgPNkpEtyY SPRING BOOT ACTUATOR ENDPOINTS https://youtu.be/z16fBE-k1oQ SPRING ACTUATOR METRICS https://youtu.be/ACrRY0REgA4 HOW TO CREATE YOUR OWN ENDPOINT https://youtu.be/hR-IdJZ9N7I FULL SPRING BOOT ACTUATOR TUTORIAL https://youtu.be/CCMAhpVvpyk Spring Boot Actuator metrics provide insights into the runtime performance and health of an application by exposing key statistics and operational data. These metrics cover a wide range of application-level and system-level properties, allowing you to monitor various aspects such as resource usage, request performance, and custom business metrics. Metrics are essential for understanding how your application behaves under different conditions and for maintaining its stability in production environments. What are Spring Boot Actuator Metrics? Metrics in Spring Boot Actuator are essentially data points that represent the state of different components within your application. They help you measure the performance of your application, such as how much memory it’s using, the response time of HTTP requests, or how many threads are active. These metrics can be gathered and exposed through monitoring tools like Prometheus, Micrometer, or external dashboards such as Grafana. Key Properties You Can Monitor with Spring Boot Actuator Metrics Spring Boot Actuator metrics offer a wide variety of built-in properties that can be monitored, including: JVM Metrics: Memory Usage: Tracks heap and non-heap memory usage. This helps you monitor how your application is using memory and detect potential memory leaks. Garbage Collection: Provides data about garbage collection, including the number of GC operations and time spent in GC. This can help in tuning the garbage collector for performance. Thread Count: Monitors active, daemon, and total thread counts. Useful for identifying if the application is creating too many threads, potentially leading to resource exhaustion. CPU Metrics: System Load: Tracks the CPU load of the system running the application. Process Uptime: Monitors the uptime of the application process itself, which helps in detecting restarts and overall system stability. HTTP Metrics: Request Count: Tracks the number of HTTP requests made to your application. It also captures the breakdown by request type (GET, POST, etc.). Request Latency: Measures the response times of HTTP requests, which helps in understanding how quickly the application responds under load. Database Metrics: Connection Pool: Monitors connection pool statistics like the number of active, idle, and maximum connections. This is essential for ensuring your database interactions are not becoming a bottleneck. Query Performance: Tracks query execution times and can highlight slow database operations. Disk Metrics: Disk Space: Monitors available and total disk space, helping to ensure the application doesn’t run out of storage. Cache Metrics: Hit/Miss Ratio: Tracks how often the cache is being hit versus missed. This is crucial for applications that rely heavily on caching for performance. Cache Size: Monitors the size and eviction rate of cache entries. Custom Metrics: Business Metrics: You can also define custom business-related metrics, such as tracking specific transactions or service health, tailored to your application's needs. Most Important Metrics to Monitor Memory Usage and Garbage Collection: Monitoring JVM memory usage and garbage collection is crucial, as inefficient memory usage can lead to performance degradation and application crashes. CPU Load and Thread Count: These are essential for understanding how your application utilizes system resources and can indicate if it's under too much load. HTTP Request Latency: This is critical for applications that serve external clients, as high latency can lead to a poor user experience. Database Connection Pool: Monitoring the number of active database connections is vital in ensuring your application doesn’t experience database connection shortages or long query execution times. Disk Space: Especially important for applications that generate or store large amounts of data, ensuring there is sufficient disk space available is a common requirement in production systems. Metrics That Might Be Missing Detailed Application-Specific Metrics: While Spring Boot Actuator provides many built-in metrics, you might need to create custom metrics for domain-specific events or performance indicators. For example, tracking the health of specific external services or the status of business processes is often left to custom implementations.