7 Agile Performance Testing Best Practices

In today's fast-paced development environments, the traditional waterfall approach to testing is not just outdated—it could prove to be a recipe for failure. The longer developers and testers wait to identify performance bottlenecks, security vulnerabilities, and other issues, the more costly and time-consuming they become to fix. That's why the concept of agile testing is gaining traction across organizations of all sizes. By implementing agile performance testing practices, developers can catch issues sooner and ensure better code quality.

What’s the best way to conduct agile performance testing? In this article, we list seven best practices for agile performance testing. They are based on our extensive experience helping enterprises, mid-market business and SMBs transition to an agile performance testing strategy, making them valuable for developers and testers at any stage of their agile journey. Ready? Let’s dive in!

7 Tips for Implementing Agile Performance Testing

1. Shift Left Your Testing

The foundation of agile testing is to “shift left” your performance testing. This means starting performance testing as early as possible in the development cycle, after every release and build. This is in contrast to the waterfall approach, in which performance testing takes place after the development process is complete.

Shifting left testing creates an iterative feedback loop that informs the following stages of the development lifecycle. After identifying performance bottlenecks, security vulnerabilities, and other issues, developers can quickly address them before they escalate into expensive or time-consuming issues to resolve. This proactive approach ensures a smoother and more efficient development process that accurately and rapidly caters to users needs.

2. Integrate Into CI/CD Pipelines

Integrate your performance tests into automated continuous integration/continuous delivery (CI/CD) pipelines. This ensures that they will run frequently, so that any performance issues are caught quickly. Running these tests manually is not only time-consuming but also prone to human error.

When setting up your tests, connect them to the context of your development workflow. For example, trigger a test after every code commit, to catch regressions in real-time. You can also schedule tests to run every X amount of time, say every Sunday in the middle of a sprint or every quarter before deciding on the new product roadmap. This kind of continuous testing can help inform subsequent development plans and business decision-making.

3. Define Clear Objectives

Is a 0.3% error rate good or bad? There’s no universal answer. The answer has to be right for your application and your users. Therefore, before you start running your tests, define clear KPIs (Key Performance Indicators). What are the response times, throughput, and scalability metrics that your application under test (AUT) needs to meet?

Having clear objectives will guide the testing process and the subsequent steps you need to take. Without KPIs, you might be monitoring your test results, but it will be difficult to take actionable steps based on them. Even if you do, they might not be the right steps for your users.

4. Use Realistic Test Data and Scenarios

Simulate real-world conditions by using realistic test data and scenarios rather than simplified ones. This ensures that the test results are more likely to reflect actual user experiences, which helps identify the actual bottlenecks, security issues, or bugs that will impact users. This makes the test results significantly more reliable and actionable.

To build realistic test scenarios, you can analyze the product data and understand how users are using the system. (Alternatively, this approach could also help you identify user journeys that might have performance issues, if users are not taking them but they should be). For new features that don’t have product data yet, conduct regular meetings with product managers. By being in the know you can prepare for what is coming and build scenarios accordingly. 

When building your scenarios, it’s recommended to use a variety of performance testing techniques, such as load testing, stress testing, and endurance testing. This will allow you to test the application under different load conditions, such as peak traffic, which ensures you can also simulate edge cases that are realistic but not always common.

5. Monitor and Analyze

Monitoring is essential during performance tests because it provides real-time insights into system behavior, helping to identify bottlenecks, failures, or inefficiencies that could impact user experience. It’s recommended to monitor data on various system metrics like throughput, error rate and hits/s, as well as CPU usage, memory consumption, and network latency. Performance testing tools can help you collect this data automatically. BlazeMeter, for example, captures metrics and displays in clear dashboards. It also integrates with APM tools for more advanced monitoring capabilities. You can also use tools like Grafana and Prometheus.

Analysis is the second half of the equation. Raw data is useful, but interpretation is key. Remember the objectives you identified before getting started? Analyze those metrics in your dashboards, as well as bottlenecks, spikes, or any irregular patterns that could indicate a performance issue. Once identified, these become targets for optimization in your next development cycle.

6. Collaborate

Collaboration is the backbone of agile performance testing. The goal is to align everyone involved – developers, testers, DevOps, and product managers – on performance requirements and results. Effective collaboration drives expedited time-to-market and results in more satisfied and productive teams. Usually, collaboration includes regular sync-ups, shared documentation, and collective decision-making, but find the methods that work for you.

7. Iterate and Adapt

Each testing cycle provides valuable data that should be used to optimize and refactor the code and the testing procedures. If a test reveals a bottleneck, fix it and then retest to confirm the fix worked. 

The same iterative approach applies to the testing process itself. Maybe you find that certain tests are redundant, or perhaps new features require new types of performance tests. Adapt the test suite accordingly.

Bottom Line

Agile performance testing is not a one-off task. After adapting your testing strategy to shifting left and CI/CD, there’s still the ongoing process that requires collaboration and continuous monitoring and improvement (and of course, running the tests). These will ensure your organization truly benefits from agile performance testing and can consistently and continuously identify issues on time.

Above all, be flexible and adaptable. The agile environment is constantly changing, so it is important for performance testers to be flexible and adaptable as well. This means being willing to change test plans, objectives, and test cases as needed.

By keeping agile performance testing a top priority, organizations can ensure their products are of the highest quality and help them stay competitive in their field. 

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