How do you implement custom metrics in Spring Boot?

Table of Contents

Introduction

Monitoring application performance is critical for maintaining the health and stability of Spring Boot applications. Spring Boot integrates well with Micrometer, a popular metrics collection library, which allows you to collect custom metrics for tracking application performance. Custom metrics can help monitor specific business logic, measure performance, and integrate with monitoring tools like Prometheus, Grafana, and others. In this guide, we will walk through how to implement custom metrics in a Spring Boot application using Micrometer.

Setting Up Micrometer in Spring Boot

Before implementing custom metrics, make sure Micrometer is set up in your Spring Boot project. Fortunately, Micrometer is included by default in Spring Boot 2.x, so you don't need additional configuration if you're using the Spring Boot starter.

Add Dependencies (If Not Already Present)

If you need to manually add Micrometer and Prometheus support, add the following dependencies to your pom.xml (Maven):

For Gradle:

Creating Custom Metrics in Spring Boot

Micrometer provides several types of metrics that you can use to track specific application statistics. These include counters, gauges, timers, and more. Here's how to implement custom metrics in your Spring Boot application:

1. Using **MeterRegistry** to Create Custom Metrics

You can inject the MeterRegistry into your Spring beans and use it to create custom metrics such as counters, gauges, and timers.

Example:

In this example:

  • The MeterRegistry object is injected into the service.
  • A custom counter metric is created with the name custom_metric_counter.
  • Each time incrementCustomCounter() is called, the counter increments.

2. Creating Custom Gauges

Gauges track a value that can go up or down (like the number of active users in a system). You can use them to track real-time metrics.

Example:

In this example:

  • A custom gauge active_users is registered.
  • The getActiveUsers() method returns the current count of active users.
  • The gauge updates dynamically as the number of active users changes.

3. Creating Custom Timers

Timers are used to track the duration of a specific event, such as how long it takes to process a request.

Example;

Here:

  • The Timer metric tracks the time taken to process a request.
  • The record() method is used to measure the duration of a code block.

Exposing Metrics via Prometheus

Once you've set up your custom metrics, you can expose them to Prometheus by configuring Spring Boot’s Actuator endpoints.

1. Enable Actuator and Prometheus Endpoint

Add the following properties to application.properties or application.yml:

This will expose the /actuator/prometheus endpoint, where Prometheus can scrape your metrics.

2. Scraping Metrics in Prometheus

In your Prometheus configuration, you can set up the following scrape configuration to collect metrics from your Spring Boot app:

Once configured, Prometheus will scrape the /actuator/prometheus endpoint at regular intervals to collect your custom metrics.

Practical Example of Custom Metrics

Let’s assume you have a Spring Boot application that tracks the number of orders placed by users. You could use a counter to track the total number of orders.

Example:

In this example:

  • The total_orders counter tracks the number of orders placed.
  • Each time placeOrder() is called, the counter is incremented.

Conclusion

Implementing custom metrics in a Spring Boot application is straightforward with Micrometer. You can easily track various aspects of your application’s performance, from counters and gauges to timers, and expose these metrics to monitoring tools like Prometheus. This helps you monitor your application's health, performance, and resource usage in real time, leading to better decision-making and proactive issue resolution.

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