Valuating a software or application for its scalability, performance, speed, and stability under varying conditions is important before launching it in the market. An effective performance testing methodology identifies functional discrepancies in an application and ensures it meets the client’s requirements for robustness and responsiveness.
Nevertheless, the vagueness in software application performance testing makes it difficult for some people to define this subjective phrase. More specifically, the criteria to determine the efficiency and flexibility of application performance is necessary to identify the best testing practices.
In this context, given below are some of the best practices for application performance testing.
Understand your application
The first step in software application performance testing is to understand the capabilities offered by an application, its intended use, and technical information. Besides, you should also have enough information about the limitations of the application and some of the factors that might affect its performance.
Getting performance testing services from a reliable service provider can give you key details about your application. Once you have understood your application’s performance from a user perspective, you should correlate your testing strategy with bugs that are creating problems.
Comprehend performance test definitions
Before you start testing the performance of your software application, you must comprehend different types of tests and why they are performed. Given below are some of the common types of performance tests and their purposes.
Performance Test | Usage |
Load Tests | To understand the application behavior under average load. |
Single User Tests | Used for baseline measurements and to achieve the best performance. |
Peal Load Tests | To understand the application behavior under the heaviest usage. |
Endurance Tests | To determine the longevity of components and detect potential leaks. |
Stress Tests | To determine the application’s robustness and identify potential breaking points. |
Configuration/Tuning Tests | To maintain the maximum optimal performance (80-85%) during the server upgrade. |
High Availability Tests | To understand the system behavior under extreme load during a failure condition. |
Isolation Tests | To measure the performance of silo components |
Set performance benchmarks
You cannot measure the actual performance of an application in a real-world scenario by throwing millions of clients at a server cluster. Instead, you do not get the real picture and may stress-test your environment. Hence, you should set realistic performance benchmarks while evaluating the performance of the application.
For this purpose, you should pick practical and realistic scenarios and incorporate diverse environments and devices in the testbed. Some of the performance goals you must consider include user satisfaction levels, maximum response times, system capacity & scalability, and acceptable performance metrics.
Take a DevOps approach
While achieving shorter development cycles with test automation is relatively easy, performance testing is a time-consuming process and cannot be completed without teamwork. The DevOps is an agile approach that combines application development with IT operations, and helps you identify errors in a timely manner through continuous testing.
Hence, to achieve the best possible results with your application performance tests, implement a DevOps culture in your organization where SQA testers, IT professionals, and developers work as a team to execute performance tests and configure applicable systems.
Build a realistic performance model
Defining your system’s capacity is a critical step to measure the performance of your software application. For this purpose, you need to monitor the behavior of the steady-state during peak periods in terms of user sessions, simultaneous requests, and server utilization.
Capacity planning and measurement improve the application’s performance by creating a complete feedback loop. Hence, you need to define business process completion rate, KPIs, and hardware metrics while building an effective performance model.
Define baselines for important system functions
Defining baseline performance measurements is necessary when QA systems do not match production systems. The baselines not only provide you with a starting point for response time goals, but offers realistic goals for multiple testing environments.
Therefore, you must define baseline performance tests and measurements for your key system functions and ensure that they occur with no system load.
Consistently monitor the results
Although designing and implementing application performance tests are important, test reports are critical to discuss the results of the application’s behavior. Communicating key insights regarding the application’s performance under various environments within your organization help define attack plans for fixes.
Therefore, you should consistently report and monitor the results and share these details with project owners and developers.
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