Using the Profiling Library in Spring Boot

This article is about using the library to profile methods in Spring Boot applications. It provides a mechanism for monitoring the execution time of methods using the @ActuatorProfiling annotation and Spring Boot Actuator to expose profiling data through custom endpoints.

GitHub https://github.com/litefunction/spring-boot-starter-actuator-profiling

Introduction

The profiling application is designed to help developers monitor and analyze the execution time of methods, with the @ActuatorProfiling annotation. Profiling data is exposed via Spring Boot Actuator.

Peculiarities

• Profiling the execution time of methods.

• Customizable profiling parameters.

• Information about obtaining profiling data in the actuator.

• Thread-safe management of profiling data.

Beginning of work

Maven dependency

To start using the library, add the following dependency to your project:

<dependency>
    <groupId>io.github.litefunction</groupId>
    <artifactId>spring-boot-starter-actuator-profiling</artifactId>
    <version>1.0.0</version>
</dependency>

Configuration

The application can be configured using properties in application.properties or application.yml.

Default Configuration

profiling.actuator.maxCountList=100
profiling.actuator.enabler=true

to configure the actuator display

management.endpoints.web.exposure.include=actuatorProfilingDetail,actuatorProfiling

Usage

Adding Profiling to Methods

To profile a method, simply annotate it with @ActuatorProfiling and optionally give it a name:

import com.lite.function.profiling.ActuatorProfiling;

public class ExampleService {

    @ActuatorProfiling(name = "exampleMethod")
    public void exampleMethod() {
        // логика метода
    }
}

Access to profiling data

Profiling data is available through the provided Actuator endpoints.

Endpoints

List of profiling data

Endpoint: /actuator/actuatorProfiling

{
  "executingProfilingMethod": {
    "exampleMethod": 403
  }
}

• exampleMethod – method name from the @ActuatorProfiling annotation

• 403 – execution time of the last method call in milliseconds

Detailed profiling data

Endpoint: /actuator/actuatorProfilingDetail/{name}

Sample answer:

{
  "name": "exampleMethod",
  "executingProfilingMethodVals": [
    {
      "delta": 506,
      "localDateTime": "2024-06-23T14:28:39.523107"
    },
    {
      "delta": 103,
      "localDateTime": "2024-06-23T14:28:43.101866"
    },
    {
      "delta": 904,
      "localDateTime": "2024-06-23T14:28:44.564218"
    },
    {
      "delta": 403,
      "localDateTime": "2024-06-23T14:28:47.180746"
    }
  ]
}

• name – method name

• executingProfilingMethodVals – list of objects with method execution time (delta in milliseconds) and timestamp (localDateTime)

Conclusion

Using a method profiling library in Spring Boot allows you to effectively monitor and analyze the execution time of methods. This is especially useful for identifying performance bottlenecks and optimizing code. Thanks to the @ActuatorProfiling annotation and integration with Spring Boot Actuator, the profiling process becomes simple and convenient.