Optimizing Cucumber Test Performance in AWS CodePipeline

Ensuring that tests run efficiently and quickly becomes crucial to maintaining a smooth development workflow. In this article, we will explore strategies for optimizing Cucumber test performance within AWS CodePipeline. We’ll delve into techniques for parallel test execution, using EC2 Auto Scaling, and integrating with AWS CodeBuild. By the end of this article, you’ll have a solid understanding of how to scale your Cucumber tests and ensure they run efficiently in a CI/CD pipeline.

1. Setting Up AWS CodePipeline

To begin with, let’s set up a basic AWS CodePipeline that will run our Cucumber tests. Assuming you already have a repository with your Cucumber tests and step definitions in Java, we will integrate this repository with CodePipeline.

Step 1: Create a CodePipeline

Navigate to the AWS Management Console and go to the CodePipeline service.
Click on “Create pipeline.”
Name your pipeline and choose a new service role.
Select your source provider (e.g., GitHub, CodeCommit) and configure the source repository details.
Add a build stage using AWS CodeBuild.

Step 2: Configure AWS CodeBuild

In the build stage, we will set up AWS CodeBuild to run our Cucumber tests.

Create a new CodeBuild project.
In the “Environment” section, choose a managed image and select the appropriate runtime (e.g., Java).
In the “Buildspec” section, define the buildspec.yml file. This file will instruct CodeBuild on how to build and run your tests.

Here is an example buildspec.yml file:

version: 0.2

phases:
  install:
    commands:
      - echo Installing dependencies...
      - apt-get update
      - apt-get install -y maven
  pre_build:
    commands:
      - echo Setting up environment...
      - mvn clean install -DskipTests
  build:
    commands:
      - echo Running tests...
      - mvn test
artifacts:
  files:
    - target/**

This basic setup will run your Cucumber tests as part of the build phase in CodeBuild.

2. Parallel Test Execution

Running tests in parallel can significantly reduce the time it takes to execute your entire test suite. AWS CodeBuild supports parallel builds, and we can leverage this feature to optimize our test performance.

Step 1: Modify `buildspec.yml` for Parallel Execution

To run tests in parallel, we need to split our test cases and run them across multiple instances. We can achieve this by creating multiple CodeBuild projects and using matrix builds.

version: 0.2

phases:
  install:
    commands:
      - echo Installing dependencies...
      - apt-get update
      - apt-get install -y maven
  pre_build:
    commands:
      - echo Setting up environment...
      - mvn clean install -DskipTests
  build:
    commands:
      - echo Running tests...
      - mvn test -Dtest=TestSuite1
artifacts:
  files:
    - target/**

In the commands section under build, specify different test suites for each CodeBuild project. You can create multiple buildspec.yml files for different test suites and configure them in separate CodeBuild projects.

Step 2: Configure Matrix Builds in CodePipeline

To execute these builds in parallel, configure a matrix build in CodePipeline.

Add multiple build actions in the build stage of your pipeline.
For each build action, select a different CodeBuild project configured with the corresponding buildspec.yml.

This setup will ensure that your test suites run in parallel, significantly reducing the overall test execution time.

3. Using EC2 Auto Scaling

To further optimize performance, we can use EC2 Auto Scaling to dynamically scale the number of instances based on the load.

Step 1: Create an EC2 Auto Scaling Group

Navigate to the EC2 service in the AWS Management Console.
Create a launch configuration or launch template with the required AMI and instance type.
Create an Auto Scaling group using the launch configuration/template.

Step 2: Integrate Auto Scaling with CodePipeline

Use AWS Lambda to trigger scaling events. Create a Lambda function that starts or stops instances based on the build status.
In CodePipeline, add a new stage for scaling events. Use Lambda invoke actions to start/stop instances before and after the build stage.

Example Lambda function to start instances:

import boto3

def lambda_handler(event, context):
    ec2 = boto3.client('ec2')
    response = ec2.start_instances(
        InstanceIds=['i-0123456789abcdef0'],
    )
    return response

Example Lambda function to stop instances:

import boto3

def lambda_handler(event, context):
    ec2 = boto3.client('ec2')
    response = ec2.stop_instances(
        InstanceIds=['i-0123456789abcdef0'],
    )
    return response

Configure these Lambda functions as actions in your CodePipeline to dynamically scale your instances based on the test load.

4. Example: Step Definitions in Java

Let’s look at some example Cucumber step definitions in Java.

import io.cucumber.java.en.Given;
import io.cucumber.java.en.When;
import io.cucumber.java.en.Then;
import static org.junit.Assert.*;

public class StepDefinitions {

    private int count;

    @Given("I have {int} cucumbers")
    public void i_have_cucumbers(int initialCount) {
        count = initialCount;
    }

    @When("I eat {int} cucumbers")
    public void i_eat_cucumbers(int eatenCount) {
        count -= eatenCount;
    }

    @Then("I should have {int} cucumbers left")
    public void i_should_have_cucumbers_left(int remainingCount) {
        assertEquals(remainingCount, count);
    }
}

This is a simple example, but in a real-world scenario, you would have more complex step definitions and test cases.

Conclusion

Optimizing Cucumber test performance in AWS CodePipeline involves parallel test execution, leveraging EC2 Auto Scaling, and properly configuring your build environment. By following the steps outlined in this article, you can significantly reduce your test execution time, leading to faster feedback and more efficient development cycles.

If you found this article helpful and are interested in integrating Cucumber Automation Framework with AWS CodePipeline, I suggest you check out some of the other articles I’ve written for this series:

If you’re looking for a deeper dive into some of the concepts and specifics discussed in my article, feel free to reach out to me directly or as always you can checkout the official AWS CodePipeline Developer Documentation for more information.