API Testing | Implementing parallel test execution in your CI/CD pipeline for faster feedback

Introduction:

In today’s fast-paced software development landscape, delivering high-quality applications quickly is paramount. One crucial aspect of ensuring the reliability and performance of modern applications is API testing. APIs (Application Programming Interfaces) serve as the backbone of most applications, enabling communication and data exchange between various components. Proper API testing is essential to identify issues early on and provide faster feedback to development teams. In this blog, we will explore the significance of API testing and how implementing parallel test execution in your CI/CD pipeline can drastically speed up the testing process and improve overall software quality.

Understanding Parallel Execution in CI/CD Pipelines:

• Parallel execution in a CI/CD (Continuous Integration/Continuous Deployment) pipeline refers to the practice of running multiple tasks or stages concurrently, rather than sequentially, to accelerate the software development and delivery process.
• Traditional CI/CD pipelines execute each stage or step one after the other. It will lead to longer build and deployment times, especially for larger and more complex projects.
• Parallel execution aims to overcome this limitation by distributing workloads across multiple resources, such as machines or containers, to speed up the overall process.

Various stages are involved in CI/CD Pipeline, such as:

1. Code Compilation: Compiling the source code into executable artifacts.
2. Unit Testing: Running automated tests to check the functionality of individual units of code.
3. Integration Testing: Testing the interactions between different units or components.
4. Deployment: Deploy the application to a staging environment for further testing.
5. User Acceptance Testing (UAT): Testing the application with real users to ensure it meets the requirements.
6. Production Deployment: Deploy the application to the production environment.

• With parallel execution, these stages can be split into separate jobs and run concurrently on multiple agents or machines. Doing this can significantly reduce the time taken to complete the entire pipeline.
• For example, while the code compilation happens, the testing infrastructure can run unit tests in parallel, and as soon as the compilation finishes, it can start executing integration tests simultaneously.
• By leveraging parallel execution, CI/CD pipelines can become more efficient, providing faster feedback to developers and allowing for quicker identification and resolution of issues. However, it’s essential to manage parallelism effectively to avoid overloading resources and causing performance bottlenecks. The degree of parallelism will depend on the available infrastructure and the complexity of the application. And the overall build and test times. Many CI/CD tools and platforms support parallel execution, and it is a crucial practice for modern software development and delivery processes.

Considerations for Implementing Parallel Execution in API Testing

• It’s important to note that while parallel execution can bring many benefits, it also introduces some challenges. You need to manage test data, and handle potential dependencies between test cases. And ensure that your testing environment can handle the increased load. Moreover, tests should be designed to be thread-safe and not interfere with each other’s execution.
• Overall, when implemented and managed effectively, parallel execution can be a powerful strategy to improve the efficiency and effectiveness of your Rest Assured test suite, providing quicker feedback on API changes and enhancing the overall quality of your RESTful APIs.

For Example:

Let’s consider a simple example of parallel execution with Rest Assured test cases using Java and TestNG as the testing framework. We’ll use TestNG’s parallel execution feature to run multiple Rest Assured test cases concurrently.

Assuming you have TestNG and Rest Assured dependencies configured in your Java project, here’s a basic example:

Step 1: Create a TestNG test class for your Rest Assured test cases.

import org.testng.annotations.Test;
import io.restassured.RestAssured;
import io.restassured.response.Response;

public class APITest {

    @Test
    public void testGetUser1() {
        Response response = RestAssured.get("https://jsonplaceholder.typicode.com/users/1");
        response.then().statusCode(200);
    }

    @Test
    public void testGetUser2() {
        Response response = RestAssured.get("https://jsonplaceholder.typicode.com/users/2");
        response.then().statusCode(200);
    }

    @Test
    public void testPostData() {
        String requestBody = "{\"name\":\"John Doe\",\"job\":\"QA Engineer\"}";
        Response response = RestAssured.given().body(requestBody)
                .post("https://reqres.in/api/users");
        response.then().statusCode(201);
    }
}

Step 2: Set up TestNG XML to configure parallel execution.

<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE suite SYSTEM "http://testng.org/testng-1.0.dtd">
<suite name="RestAssuredTestSuite" parallel="methods">
    <test name="RestAssuredTests">
        <classes>
            <class name="APITest"/>
        </classes>
    </test>
</suite>

In the TestNG XML above, the “parallel” attribute is set to “methods”. It means TestNG will execute test methods in parallel.

Step 3: Run your tests using TestNG.

• When you run your tests with TestNG, it will execute the test methods in parallel, as configured in the XML file. For example, if you have two available threads, TestNG will run testGetUser1 and testGetUser2 concurrently.
• Please note that you should design your test cases to be thread-safe and not have dependencies between them. In the above example, each test method is independent and can run concurrently without affecting each other.
• Keep in mind that you should carefully choose the number of threads used for parallel execution based on your system’s capabilities. And also the resources required for each test case. Too many threads might overload your system and lead to performance issues. TestNG allows you to specify different parallel execution configurations, such as parallel=”tests” or parallel=”classes” depending on your specific requirements.

Execution of parallel execution to CI/CD pipeline in GitLab:

• To execute the parallel execution code in a CI/CD pipeline on GitLab, you can leverage GitLab CI/CD. It will allow you to define and run custom pipelines for your projects. GitLab CI/CD uses a YAML file called .gitlab-ci.yml to define the pipeline configuration. In this file, you can specify the stages, jobs, and various configurations for parallel execution.

Step 1: Add the .gitlab-ci.yml file to the root of your GitLab repository.

• In the above .gitlab-ci.yml file, we define a single stage called “test” that includes a job named “test.” The job uses the latest Maven Docker image, which includes Java and Maven installed.

Step 2: Push the .gitlab-ci.yml file to your GitLab repository.

Step 3: GitLab CI/CD will automatically detect the .gitlab-ci.yml file, and when you push new changes to your repository, it will trigger the CI/CD pipeline.

• During the pipeline execution, the test job will run, and the parallel keyword with the matrix configuration will trigger parallel execution of the specified test methods (testGetUser1, testGetUser2, and testPostData).
• GitLab CI/CD will automatically distribute these test cases across multiple runners or machines (depending on your GitLab configuration). Running them concurrently and significantly reducing the test execution time.
• Please note that for this example to work, you need to have GitLab CI/CD set up properly with appropriate runners and permissions to execute the pipeline. You may also need to adjust the image property and other configurations in the .gitlab-ci.yml file based on your specific environment and requirements.
• Once triggered, the GitLab CI/CD dashboard allows you to monitor the execution of the pipeline. It will show the progress and status of the parallel test execution. If any of the tests fail, GitLab CI/CD will provide detailed logs and reports to help you identify and address any issues.

Benefits of parallel execution in CI/CD pipeline:

Parallel execution in CI/CD pipelines offers several significant benefits that contribute to more efficient and faster software development and delivery. Some of the key advantages include:

1. Reduced build and deployment time: Concurrently running multiple stages reduces the overall pipeline execution time significantly. It allows completing tasks that would have been executed sequentially simultaneously. Resulting in faster feedback loops and quicker delivery of features and bug fixes.
2. Faster feedback loops: Parallel execution enables faster feedback on code changes and test results. When unit tests, integration tests, and other tasks run concurrently, developers can quickly identify and address issues. It will lead to more reliable code and fewer bugs.
3. Higher software quality: The faster feedback provided by parallel execution helps catch defects and issues early in the development process. This, in turn, leads to higher software quality and a more stable application.
4. Scalability: As projects grow larger and more complex, parallel execution becomes crucial for maintaining acceptable build and deployment times. It allows CI/CD pipelines to scale effectively with the growth of the project.
5. Enables frequent deployments: Parallel execution facilitates rapid and reliable deployments. When tasks are executed concurrently, it becomes feasible to deploy updates more frequently, improving the software’s time-to-market and making it easier to roll back changes if necessary.
6. Isolation of failures: Running tasks in parallel can help isolate failures to specific stages or components. This isolation simplifies troubleshooting and debugging, making it easier to identify the root cause of issues.
7. Support for diverse environments: Parallel execution benefits deploying applications to multiple environments like staging, testing, and production, minimizing downtime and deployment-related risks.
8. Enhanced CI/CD pipeline efficiency: Leveraging parallelism improves CI/CD pipeline efficiency, allowing the team to focus on critical tasks and reducing wait times for builds and tests.

Advantages of Parallel Execution in API Testing:

Parallel execution can provide significant benefits when it comes to running Rest Assured test cases, which are used to automate and validate RESTful API endpoints. Here’s how parallel execution helps in this context:

1. Faster test execution: Rest Assured test cases can sometimes involve numerous API requests and validations. Running these test cases in parallel allows you to distribute the workload across multiple threads or machines, leading to faster execution times. This is especially beneficial when you have a large number of test cases or when certain test cases are time-consuming.
2. Optimized resource utilization: With parallel execution, you can make better use of available testing resources, such as CPU, memory, and network bandwidth. Test cases can be executed concurrently, ensuring that your testing infrastructure is utilized efficiently.
3. Quick feedback on API changes: When developing or updating RESTful APIs, it’s crucial to get quick feedback on whether the changes introduced any issues. Parallel execution of Rest Assured test cases allows you to detect regressions faster. It will help you catch and fix issues early in the development process.
4. Scalability for larger projects: As your API and test suite grow, the execution time of your test suite can also increase. Parallel execution helps you handle the growing number of test cases, making it easier to scale your testing infrastructure to accommodate larger projects.
5. Support for continuous integration: In a continuous integration environment, where multiple developers are committing changes simultaneously, parallel execution becomes even more valuable. It allows you to run tests concurrently on different branches or commits, ensuring that integration issues are identified early.
6. Distributed testing: Parallel execution enables distributed testing across multiple servers or cloud-based infrastructure, which can further speed up test execution, particularly for geographically distributed teams.

Conclusion:

API testing is a critical component of the software development process that ensures the reliability and performance of APIs. By implementing parallel test execution in your CI/CD pipeline, you can dramatically speed up the testing process and provide faster feedback to development teams. This results in improved software quality, reduced time to market, and increased customer satisfaction. Embracing parallel testing as part of your testing strategy empowers your team to build. And deliver high-quality applications efficiently in today’s fast-paced digital landscape.