Ultimate Guide to Continuous Performance Testing in 2024

In today’s fast-paced and evolving software and tech industry, ensuring software applications perform optimally and meet user expectations is critical for QA teams. Continuous performance testing is an essential practice that helps to identify performance issues before they become significant problems. 

In this article, we will explore

• The difference between traditional performance testing and continuous performance testing
• The benefits of continuous performance testing 
• Challenges 

Whether you are a developer, tester, or project manager, this article will provide you with a comprehensive understanding of continuous performance testing and its importance in ensuring the success of your software applications.

The difference between performance testing vs. continuous performance testing

Continuous performance testing is a variation of performance testing. Unlike traditional performance testing, which is usually done after development is complete (see Figure 1), continuous performance testing is integrated into the software development life cycle and is performed continuously throughout the development process.

Source: Software Testing Training¹

Figure 1: ‘Traditional Performance Testing’

The key difference between performance testing and continuous performance testing is that performance testing is typically conducted as a one-time activity at the end of a development cycle or before releasing the product to production, while CPT is an ongoing process that is integrated into the software development process. (See Figure 2)

Source:Radview²

Figure 2: Continuous performance testing

Automated Continuous Performance Testing

Continuous performance testing is essential in a Continuous Integration/Continuous Deployment or Delivery CI/CD company, especially throughout the CD process, which involves stress testing the platform and checking the dashboards’ availability and response times. 

With automated performance testing, you can essentially identify slowdowns before they get out of hand and negatively affect the user experience. To always guarantee optimal user experience and satisfaction, you must regularly evaluate the performance of your dashboards after delivery to your users or clients and foresee any slowdowns.

See our following articles to understand this topic more thoroughly:

“Continuous Delivery vs. Continuous Deployment”

“CI/CD for Machine Learning: What it is & Benefits”

Sponsored

In several industries, continuous delivery and deployment are essential. For instance, integrating test automation technologies requires CI/CD pipelines. Testifi’s CAST is a test automation tool that offers performance testing and static code analysis, making integrating it into CI/CD workflows easy.

What are the benefits of continuous testing?

1. Early detection of performance issues: Regular performance tests can detect performance issues early in the development cycle, which can help avoid more significant problems.
2. Faster feedback: Continuous performance testing provides immediate feedback on the application’s performance, allowing developers to quickly identify and address issues.
3. Improved user experience: Ensuring that an application performs well under heavy load can improve the user experience, resulting in increased user satisfaction and engagement.
4. Reduced costs: Identifying and addressing performance issues early on can help to reduce the overall cost of development by avoiding expensive rework or infrastructure changes later in the development cycle.
5. Increased efficiency: By automating performance testing, development teams can save time and resources, allowing them to focus on other areas of development.
6. Better quality: Continuous performance testing ensures that an application is thoroughly tested for performance, which can improve its overall quality and reliability.

Top 4 challenges of continuous performance testing

1-Test environment complexity

Setting up a realistic test environment can be complex, especially for applications that rely on complex infrastructure like microservices or cloud-based services. The lack of performance-related requirements (such as response time or support for a number of concurrent users) in user stories also adds up to this challenge. 

2-Test data management

Ensuring that the test data represents real-world scenarios can be challenging, especially for large data processing applications. The challenge of test data management becomes a real issue when DevOps teams lack performance engineering expertise. This is especially important for organizations with external teams managing test data.

3-Test script maintenance

Test scripts must be regularly maintained to accurately simulate user behavior and generate realistic loads. An example of a case study for test script maintenance can be the following:

A software development team wants to implement continuous performance testing to ensure their application is always performing optimally. They need a solution for managing test scripts and results to support this effort.

The team decides to use a cloud-based performance testing tool with built-in test script management and reporting capabilities. They create a set of test scripts that cover various performance scenarios, such as high user load and database stress testing. 

The team sets up the test scripts to run automatically regularly, such as every night or after each new code deployment. The tool automatically executes the test scripts and generates reports showing performance metrics, such as response time and error rate.

By using a cloud-based performance testing tool with built-in test script management and reporting capabilities, the software development team can easily implement continuous performance testing. 

4-Tool integration

Integrating performance testing tools into the development process can be challenging, especially for organizations with legacy systems or complex development workflows. Development teams’ lack of accountability for performance testing is a prominent roadblock. APM tools are often absent in the development teams or the delivery pipeline. 

How to integrate continuous performance testing into CI/CD pipeline?

1-Define your performance testing goals

Before you begin, you should define your performance testing goals. This can include determining what metrics you want to measure, what scenarios you want to test, and what performance thresholds you want to set.

2-Build organizational accountability

The second step to integrating continuous performance testing into CI/CD pipeline is to build organizational accountability, which is a direct solution to the abovementioned challenges. A basic equation for accountability can be explained as Accountability = Awareness + Visibility.³ 

• Awareness would mean that teams would discuss performance factors early 
• Visibility would mean that teams would include performance factors and acceptance criteria in the definition of done. 

3-Set up a performance testing environment

You need to set up an environment where you can run your performance tests. This environment should be similar to your production environment. To set up a testing environment, you should determine what aspects of performance you want to test, such as 

• response time
• throughput
• scalability

This will help you determine the requirements for your performance testing environment.

4-Set performance thresholds

You need to set performance thresholds based on your application’s performance requirements. These thresholds can be based on response times, throughput, or other performance metrics.

5-Analyze the test results

After each performance test, you must analyze the results to identify any performance issues or bottlenecks. You can use the performance metrics to optimize your application’s performance.

If you have further questions, reach us:

External Links

• 1. Software Testing Training “Continuous Performance Testing in the DevOps Pipeline”
• 2. Radview “Continuous Performance Testing: A DevOps Imperative”
• 3. Software Testing Training “Continuous Performance Testing in the DevOps Pipeline”