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Working with Performance and Load Testing In Agile

In waterfall model, performance and load testing were performed at the closing stages of the software development life cycle (SLDC). This meant that developers had to integrate whole system and verify its functionality to generate relevant results.

Problems in performance times for a feature or bugs generated by operational degradation at fewer than the max number of users would start fixing cycling to make sure that operational performance meets the requirements. These processes belonged to User Acceptance Testing (UAT) at one stage. However, the introduction of Agile methodology has transformed the game significantly.

[ Also Read: Best Software Development Methodologies ]

What Are the Agile Processes?

Agile software development refers to a set of practices and methods used for delivering a product that is valued by the end-user. In this methodology, cross-functional and self-organizing teams utilize relevant practices to build solutions that the masses use.

Agile includes an iteration, known as sprint. It is a two-to-four-week period where the development teams create a product increment.

Why Performance and Load Testing Is Different In Agile?

The SLDC has been shortened from months to less than two weeks. This has raised the need for fast performance test verification. To do it, there must be a fast and automated testing process that allows you to hit the deadline.

Due to the never-ending delivery deadline in Agile, load and performance testing are often ignored. In the worst-case scenario, this can lead to a user experience disaster.

Along with developing manual and automated functional tests, you should also produce performance and load tests.

Performance and Load Testing Issues In the Agile Environment

During the initial phases of product’s life cycle, testers create the load test suite to make the user experience operational. You will have to maintain it, and your Agile Sprints must support specific situations where the UI is not usable. This mainly includes using third-party APIs.

[ Also Read: Remote team working in agile environment ]

Performance is usually reliant on the data exchange between programming modules of different descriptions. If you are considering testing it, see to it that interface is working properly. Prepare a body containing the required test data and exercise them. The performance tests are pushed back again as the elements needed will not be provided until the development effort ends. You will find this repeatedly in SaaS-related use cases.

The SaaS concept’s quick spread has incorporated the problem of unavailable system functions into the development too.

Putting Performance and Agile Testing Together

To reach max efficiency in an agile environment, identify and resolve performance issues at the degree of your base code. This will prevent bottlenecks in your pipeline. You have to go through the following stages:

1. Optimization – Implement tests to remove the issues at the base code level.

2. Component Testing – Address bugs at the level of app components.

3. App flow testing – Isolation and testing of key application flows show UX consistency at varying load levels.

Testing Models

There are three main testing models of iterative performance for agile environments.

1. On Demand: This is the usual starting point for businesses that want to combine agile processes with performance testing. In short, it assigns full responsibility to developers to test and tune the application at all stages, where a dedicated tester supervises their efforts and conducts the performance evaluation.

2. On Retainer: In this one, a tester is assigned to each application development project. They are not reserved for each task, but are rather used as standby when developers need in-depth technical assistance for bug resolution

3. Full Immersion: This model is for organizations that are looking for delivering quality applications and have committed to mastering the art of performance testing. Here, the company designates testers for full-time duty to monitor and verify all development stages as well as manage and handle all the performance testing activities from start to end.

Service Virtualization

Service virtualization can help DevOps teams leverage virtual services so that they don’t have to pool resources from the production. This can improve thorough and recurring testing when critical components don’t exist with your system architecture. It aids in emulating the behavior key elements that are going to be present in the actual production.

These days, applications are multifaceted and are required to build robustness for handling real-time defects. By incorporating service virtualization into agile testing, you can build an in-depth testing framework. In addition, it allows you to conduct integration testing for complex applications in the development process by removing bottlenecks that could affect time-to-market and slow down the production for an Application under Test (AUT).

Service virtualization is mostly needed during the development of high-end SOA-based, API-based, and cloud-based systems. It is extremely crucial in a situation where the required software and hardware components are unavailable for testing.

Development teams and organizations have started to prioritize service virtualization and use it in tandem with Agile to deploy quality products, reduce testing expenses, boost productivity, and save time. Moreover, it can speed up time-to-market, aid parallel development practices, improve quality, and motivate collaborative efforts between development and testing teams.

Service virtualization has enabled companies to gain competitive advantage over other businesses that still go by the linear development strategy. It assists with eliminating roadblocks that affect parallel and Agile development.

Final Thoughts

Continuous performance testing in sprint allows you to improve application quality with reduced cycle times in Agile environments. You can achieve this by running performance tests in continuous integration (CI) and build the capability to perform load tests for each and every passing sprint.

By using small teams, businesses can collaborate more effectively and efficiently, offering faster turnaround times and test applications through full testing cycles.