The software development life cycle has evolved a lot over the past few years, with the major changes due to the ever-growing online demands and business from end customers. With this shift in demand on online platforms, application performance and stability is a must-have, and one of the critical components of application growth. Enhanced and better customer experience over the platform can help boost up traffic on the application quickly, which eventually helps in increased business, and hopefully happier customers. Keeping our performance testing methodologies and scripts up to date with the latest software development frameworks is a challenging task and is an ever evolving process. Today, we are going to look at a few of the latest performance testing trends that are getting adopted by major technology companies to help leap over their competition and help gain the consumer base.
Performance Testing Trends of Today
Shift-left testing involves including performance tests as early as possible to the development life cycle and making sure performance testing becomes part of each sprint. It intends to capture and monitor performance metrics after any new feature addition to the application. This will help us find and fix issues if any performance degradation has occurred at an early stage. We usually carry out functional automation test running via CI/CD platforms. Similarly, performance tests should be triggered at each new development and share results comparing the performance trends of applications based on previous runs.
Real Browser-based vs. Protocol-based Load Tests
LoadView provides support to test both real browser and protocol based load tests. You can even create your performance test script for complex applications using the EveryStep Web Recorder, which records the user behavior and reruns its desired virtual users.
Chaos testing involves testing and understanding how will the application behave when we randomly create failures in one of the parts of architecture. We can face many uncertainties in the production environment, therefore chaos engineering tries to identify those scenarios, tests how the system would behave, and allows us to understand if there could be any cascading issues due to the failure in other systems. This helps to make our system and overall infrastructure resilient. For example, in case of sudden downtime of one of our web services or database, our entire infrastructure should never go down. Chaos engineering as part of the software development life cycle tries to find such loopholes and make us ready before it happens in production.
Using AI to Automate Testing
Every now and then, customer behavior changes on our platform, so we tend to change performance testing scripts based on this. But using AI and machine learning we can monitor what the real user is doing on our platform and find patterns around the user journey they are following. Based on this pattern, we can create a performance testing model which will make sure our load testing scripts closely match with real user behavior. Creating AI based performance test models will generate performance test scripts which would eventually help find new issues and loopholes in the system.
Performance Testing to Performance Engineering
Many organizations are taking a cultural shift from usual performance testing to performance engineering, which means measuring and identifying performance metrics is the responsibility of everyone in the team rather than focused on few individuals. It helps to understand how even the smallest parts of overall architecture affects the system and works together as a system. This brings the responsibility to each small team to make sure what they deliver as part should not cause any performance degradation or impact on the overall metrics.
Incorporating Tests into CI/CD Platforms
We have discussed a lot in this article on how we should approach and create performance test scripts, but these scripts should be part of our CI/CD platforms, which eases out all the hassle of running load tests and helps getting results at each code change. Performance tests should be running just like functional testing after each deployment, giving insights and real performance metrics which can help to identify issues at the very early stage of the development life cycle. LoadView provides easy integration of our performance test scripts with Jenkins to help us in such cases. We can create a performance test script over LoadView which can be triggered from Jenkins.
After all the functional tests and performance tests are complete, we can still have issues in production which demands monitoring our production environment and taking action in case of issues. The Dotcom-Monitor platform provides easy monitoring of our web pages, web applications, web services, and infrastructure, and raises alarm at the right moment and helps to save us from a major loss and downtime. Monitoring involves getting details like CPU, memory utilization, response time of application web pages and in case there is threshold breach, an action can be taken before we face any downtime.
Conclusion: Performance Testing Trends
We discussed a few of the major performance testing trends which are helping to scale and adapt with the ever-changing software development frameworks. Staying up-to-date with technology and utilizing these key testing principles can help us provide stable and enriched user experiences for our consumers, helping to provide long lasting customer loyalty. We also looked at how LoadView can help us integrate with few of the key latest trends and help us achieve our goals of a stable application.
Get started with LoadView today. Sign up today and receive up to 5 free load tests to begin your performance testing journey.