Application Real-Time Monitoring Service:Connect Spring Boot applications to Managed Service for Prometheus

Add Maven dependencies

Add Spring Boot Actuator and the Micrometer Prometheus registry to your pom.xml:

<!-- Spring Boot Actuator: exposes operational endpoints -->
<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-actuator</artifactId>
</dependency>
<!-- Micrometer Prometheus registry: formats metrics for Prometheus -->
<dependency>
    <groupId>io.micrometer</groupId>
    <artifactId>micrometer-registry-prometheus</artifactId>
</dependency>

Having micrometer-registry-prometheus on the classpath is enough for Spring Boot to auto-configure the Prometheus registry. No additional code is required for basic JVM and HTTP metrics.

Configure the metrics endpoint

Add the following properties to your application.properties file to expose metrics on a dedicated port:

spring.application.name=frontend

# Serve actuator endpoints on a separate port
management.server.port=8091
# Expose all actuator endpoints, including /actuator/prometheus
management.endpoints.web.exposure.include=*
# Tag all metrics with the application name for filtering in dashboards
management.metrics.tags.application=${spring.application.name}

After configuration, Managed Service for Prometheus scrapes metrics in OpenMetrics format from http://<pod-ip>:8091/actuator/prometheus.

Track API latency with @Timed

Add a @Timed annotation to any controller method to capture rate, error, and duration (RED) metrics:

@Timed(value = "main_page_request_duration",
       description = "Time taken to return main page",
       histogram = true)
@ApiOperation(value = "Main page", tags = {"Main page"})
@GetMapping("/")
public String index(Model model) {
    model.addAttribute("products", productDAO.getProductList());

    model.addAttribute("FRONTEND_APP_NAME", Application.APP_NAME);
    model.addAttribute("FRONTEND_SERVICE_TAG", Application.SERVICE_TAG);
    model.addAttribute("FRONTEND_IP", registration.getHost());

    model.addAttribute("PRODUCT_APP_NAME", PRODUCT_APP_NAME);
    model.addAttribute("PRODUCT_SERVICE_TAG", PRODUCT_SERVICE_TAG);
    model.addAttribute("PRODUCT_IP", PRODUCT_IP);

    model.addAttribute("new_version", StringUtils.isBlank(env));
    return "index.html";
}

Monitor Guava Cache health

If your application uses Guava Cache, wrap it with Micrometer to track hit ratios and eviction counts:

1. Inject MeterRegistry. Spring Boot auto-injects PrometheusMeterRegistry.

2. Call GuavaCacheMetrics.monitor to register cache metrics.

3. Enable statistics collection with .recordStats().

4. Set a descriptive cache name for the generated metrics.

Monitor thread pool utilization

1. Inject MeterRegistry.

2. Wrap the thread pool with a Micrometer utility class.

3. Set a descriptive thread pool name for the generated metrics.

Register custom business metrics

To track metrics specific to your business logic, inject MeterRegistry into any bean and register Counter, Gauge, or Timer metrics:

@Service
public class DemoService {

    Counter visitCounter;

    public DemoService(MeterRegistry registry) {
        visitCounter = Counter.builder("visit_counter")
            .description("Number of visits to the site")
            .register(registry);
    }

    public String visit() {
        visitCounter.increment();
        return "Hello World!";
    }
}

Verify service discovery

After the ServiceMonitor is configured, confirm that the application appears on the Targets tab of the Service Discovery page.

Import community dashboard templates

The Grafana community provides two dashboard templates that cover Spring Boot and JVM metrics:

• Spring Boot 2.1 Statistics: request rate, error rate, and response time.

• JVM (Micrometer): memory usage, garbage collection, and thread activity.

Import these templates into the Grafana instance provided by Managed Service for Prometheus, then customize them for your specific metrics.

Example dashboard

The following dashboard combines community templates with custom business metrics. It shows uptime, memory usage, heap and non-heap memory allocation, and garbage collection data across generations.

Configure alert rules

You can configure alert rules for key metrics to detect issues before they affect users.