Prometheus and Grafana integration concept in Spring Boot - Mini Project: Build & Apply

Prometheus and Grafana Integration with Spring Boot

📖 Scenario: You are building a simple Spring Boot application that exposes metrics for monitoring. You want to integrate Prometheus to collect these metrics and Grafana to visualize them. This project will guide you step-by-step to set up the basic integration.

🎯 Goal: Build a Spring Boot application that exposes Prometheus metrics, configure Prometheus to scrape these metrics, and set up Grafana to visualize them.

📋 What You'll Learn

Create a Spring Boot application with actuator dependency

Enable Prometheus metrics endpoint

Configure Prometheus to scrape the Spring Boot metrics endpoint

Set up Grafana dashboard to visualize the metrics

💡 Why This Matters

🌍 Real World

Monitoring applications is essential to detect issues early and understand system performance. Prometheus collects metrics, and Grafana visualizes them in dashboards.

💼 Career

DevOps engineers and backend developers often integrate Prometheus and Grafana with applications to ensure reliability and performance monitoring.

1

Create Spring Boot application with Actuator

Create a Spring Boot application class named DemoApplication with the @SpringBootApplication annotation and a main method that runs the application using SpringApplication.run(DemoApplication.class, args).

Spring Boot

# Create the DemoApplication class with @SpringBootApplication and main method
# Your code here

Hint

Use the @SpringBootApplication annotation on the class and write a main method that calls SpringApplication.run.

2

Add Actuator and Prometheus dependencies

Add the spring-boot-starter-actuator and micrometer-registry-prometheus dependencies to your pom.xml file inside the <dependencies> section.

Spring Boot

import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;

@SpringBootApplication
public class DemoApplication {
    public static void main(String[] args) {
        SpringApplication.run(DemoApplication.class, args);
    }
}


# Your code here

Hint

Add the actuator and micrometer Prometheus registry dependencies inside the <dependencies> section of pom.xml.

3

Enable Prometheus endpoint in application properties

Add the following line to src/main/resources/application.properties to enable the Prometheus metrics endpoint: management.endpoints.web.exposure.include=prometheus.

Spring Boot

import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;

@SpringBootApplication
public class DemoApplication {
    public static void main(String[] args) {
        SpringApplication.run(DemoApplication.class, args);
    }
}

 in pom.xml -->

    org.springframework.boot
    spring-boot-starter-actuator


    io.micrometer
    micrometer-registry-prometheus

-->

# Add the line below to application.properties
# Your code here

Hint

Open application.properties and add the line to expose the Prometheus endpoint.

4

Print Prometheus metrics endpoint URL

Write a System.out.println statement in the main method to print: "Prometheus metrics available at http://localhost:8080/actuator/prometheus".

Spring Boot

import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;

@SpringBootApplication
public class DemoApplication {
    public static void main(String[] args) {
        // Print the Prometheus metrics URL below
        // Your code here
        SpringApplication.run(DemoApplication.class, args);
    }
}

 in pom.xml -->

    org.springframework.boot
    spring-boot-starter-actuator


    io.micrometer
    micrometer-registry-prometheus

-->

# In src/main/resources/application.properties
management.endpoints.web.exposure.include=prometheus

Hint

Use System.out.println to print the exact URL string.

Practice

1. What is the primary role of Prometheus in a Spring Boot application monitoring setup?

easy

A. To collect metrics by scraping the application's exposed endpoint

B. To visualize metrics using dashboards

C. To expose application metrics automatically

D. To send alerts directly to users

Solution

1. Step 1: Understand Prometheus function

   Prometheus collects metrics by scraping HTTP endpoints exposed by applications.

2. Step 2: Differentiate roles of tools

   Grafana is used for visualization, not collection. Spring Boot exposes metrics but does not collect them.

3. Final Answer:

   To collect metrics by scraping the application's exposed endpoint -> Option A

4. Quick Check:

   Prometheus collects metrics = A [OK]

Hint: Remember: Prometheus scrapes, Grafana shows [OK]

Common Mistakes:

• Confusing Grafana as the collector
• Thinking Spring Boot collects metrics
• Assuming Prometheus sends alerts directly

2. Which dependency must be added to a Spring Boot project to expose metrics for Prometheus scraping?

easy

A. spring-boot-starter-web

B. spring-boot-starter-data-jpa

C. micrometer-registry-prometheus

D. spring-boot-starter-security

Solution

1. Step 1: Identify metrics registry dependency

   Micrometer provides metrics support; the Prometheus registry enables exposing metrics in Prometheus format.

2. Step 2: Exclude unrelated dependencies

   Web starter is for REST APIs, JPA for database, Security for auth; none expose Prometheus metrics.

3. Final Answer:

   micrometer-registry-prometheus -> Option C

4. Quick Check:

   Prometheus metrics need micrometer-registry-prometheus [OK]

Hint: Add micrometer-registry-prometheus for Prometheus metrics [OK]

Common Mistakes:

• Adding only spring-boot-starter-web without metrics registry
• Confusing JPA or Security starters as metrics providers
• Forgetting to include Prometheus registry dependency

3. Given this Spring Boot application.properties snippet:
management.endpoints.web.exposure.include=health,prometheus
management.endpoint.prometheus.enabled=true
What will be the URL path to scrape metrics for Prometheus?

medium

A. /metrics

B. /actuator/metrics

C. /prometheus/metrics

D. /actuator/prometheus

Solution

1. Step 1: Understand actuator endpoint exposure

   Spring Boot exposes actuator endpoints under /actuator by default.

2. Step 2: Identify Prometheus endpoint path

   Prometheus metrics endpoint is /actuator/prometheus when enabled and exposed.

3. Final Answer:

   /actuator/prometheus -> Option D

4. Quick Check:

   Prometheus metrics at /actuator/prometheus [OK]

Hint: Actuator endpoints default under /actuator [OK]

Common Mistakes:

• Using /metrics instead of /actuator/prometheus
• Assuming /prometheus/metrics is default
• Forgetting to enable prometheus endpoint

4. You configured Prometheus to scrape your Spring Boot app, but metrics are not appearing in Grafana. Which is the most likely cause?

medium

A. Prometheus server is down but Grafana is running

B. Prometheus is not scraping the correct endpoint URL

C. Spring Boot app does not have a database connection

D. Grafana does not support Prometheus data sources

Solution

1. Step 1: Check Prometheus scraping configuration

   If Prometheus scrapes wrong URL, no metrics collected, so Grafana shows nothing.

2. Step 2: Exclude other causes

   Grafana supports Prometheus; database unrelated; if Prometheus down, Grafana shows errors.

3. Final Answer:

   Prometheus is not scraping the correct endpoint URL -> Option B

4. Quick Check:

   Wrong scrape URL blocks metrics flow [OK]

Hint: Verify Prometheus scrape URL matches app endpoint [OK]

Common Mistakes:

• Blaming Grafana for lack of support
• Assuming database affects metrics exposure
• Ignoring Prometheus scrape configuration

5. You want to create a Grafana dashboard showing the average response time of your Spring Boot app over the last 5 minutes. Which Prometheus query should you use?

hard

A. rate(http_server_requests_seconds_sum[5m]) / rate(http_server_requests_seconds_count[5m])

B. sum(http_server_requests_seconds_sum) / sum(http_server_requests_seconds_count)

C. avg_over_time(http_server_requests_seconds_sum[5m])

D. count_over_time(http_server_requests_seconds_count[5m])

Solution

1. Step 1: Understand metrics for response time

   http_server_requests_seconds_sum is total time; count is number of requests.

2. Step 2: Calculate average over 5 minutes

   Use rate() to get per-second increase, then divide sum by count for average.

3. Final Answer:

   rate(http_server_requests_seconds_sum[5m]) / rate(http_server_requests_seconds_count[5m]) -> Option A

4. Quick Check:

   Average = sum rate / count rate [OK]

Hint: Divide sum rate by count rate for average response time [OK]

Common Mistakes:

• Using sum without rate causes wrong aggregation
• Using avg_over_time on sum metric alone
• Counting requests instead of averaging time