Full Stack Observability with Spring Boot, Prometheus, and Grafana

Description

This video, titled "1. Metrics Monitoring: Spring Boot 3 -- Prometheus -- Grafana," is a technical tutorial by Linh Vu that demonstrates how to implement the metrics pillar of observability in a Spring Boot 3 application . The tutorial guides viewers through a full-stack setup involving Spring Boot Actuator, Micrometer, Prometheus, and Grafana . The video covers the following key steps: Spring Boot Configuration: The author creates a Spring Boot 3 application and enables Spring Boot Actuator to expose application metrics . By adding the micrometer-registry-prometheus runtime dependency, the application is configured to expose a specific Prometheus metrics endpoint at /actuator/prometheus . Prometheus Deployment via Docker: The tutorial demonstrates how to deploy Prometheus using Docker Compose . A critical configuration step involves using the special DNS name host.docker.internal to allow the Prometheus container to scrape metrics from the Spring Boot application running on the local host . Grafana Integration: Grafana is also deployed via Docker Compose within the same network as Prometheus . The video shows how to log into Grafana (using the default "admin" credentials), connect it to Prometheus as a data source, and verify the connection . Visualizing Metrics: To complete the observability pipeline, the author demonstrates how to import a pre-made JVM dashboard (specifically ID 4701) from the Grafana dashboard library . This allows for the immediate visualization of performance data, such as CPU usage and memory, once the data source is successfully linked . By the end of the demonstration, the author successfully verifies the entire data flow from the local Spring Boot application to the Grafana dashboard