Performance Testing

Performance Testing

What is Performance Testing?

Performance Testing is non-functional testing, used for testing the speed, response time, stability, reliability, scalability, and resource usage of a software application under a particular workload. The main purpose of performance testing is to identify and eliminate the performance bottlenecks in the software application.

Why Performance Testing is Importance?

  • The basic benefits of undergoing performance testing include:

  • Increased customer satisfaction.

  • Better overall customer experiences.

  • Higher quality application.

  • Reduced risk of system downtime.

  • Implementing performance patches before taking your product live.

  • Eliminating scalability issues.

  • Benchmarking tools for performance engineering teams.

What is Performance Testing to Measured?

  • To determine whether the application satisfies performance requirements (for instance, the system should handle up to 1,000 concurrent users).

  • To locate computing bottlenecks within an application.

  • To establish whether the performance levels claimed by a software vendor are indeed true.

  • To compare two or more systems and identify the one that performs best.

  • To measure stability under peak traffic events.

Performance Testing Types:

There are many types of testing methods that can be used to determine performance. Some examples are as follows:

Load testing — It is the simplest form of testing conducted to understand the behavior of the system under a specific load. Load testing measures system performance as the workload increases on the database, application server, etc. That workload could mean concurrent users or transactions. The system is monitored to measure response time and system staying power as the workload increases.

Stress testing — Is meant to measure system performance outside of the parameters of normal working conditions (the upper limit capacity of the system). The software is given more users or transactions that can be handled. The goal of stress testing is to measure the software's stability and determine how the system performs if the current load goes well above the expected maximum.

Soak testing — increases the number of concurrent users and monitors the behavior of the system over a more extended period. The objective is to observe if intense and sustained activity over time shows a potential drop in performance levels, making excessive demands on the resources of the system. During soak tests, the parameters such as memory utilization are monitored to detect memory leaks or other performance issues.

Spike testing — Spike testing is performed by increasing the number of users suddenly by a very large amount quickly and repeatedly and measuring the performance of the system. The main aim is to determine whether the system will be able to sustain the workload.

The Performance Testing Process

The goal of performance testing is the same for every software, though the methodology can vary a bit. So, here’s what a typical performance testing process looks like:

1 - Identify your testing environment — Know your physical test environment, production environment, and what testing tools are available. Select appropriate software, hardware, network configuration, etc., to use for the test.

2- Identify performance metrics — In addition to identifying metrics such as response time, throughput, and constraints, identify what are the success criteria for performance testing.

3- Plan and design performance tests — Identify performance test scenarios that take into account user variability, test data, and target metrics. It will help you plan and design a few models for your performance tests.

4- Configuring the test environment — Prepare the elements of the test environment and instruments needed to monitor resources.

5- Implement test design — Create the performance tests according to your test design

6- Execute tests — In addition to running the performance tests, monitor and capture the data generated.

7- Analyze, report, and retest — Analyze the data and share the findings. Run the performance tests again using the same parameters and different parameters.

Performance Testing Fallacies

Performance testing fallacies can lead to mistakes or failure to follow performance testing best practices. These beliefs can cost significant money and resources when developing software:

Performance testing is the last step in development.

We often think that performance tests only take place at the end of a development project, just before rollout, in order to do some fine-tuning to make sure everything goes smoothly. Anticipating and solving performance issues should be an early part of software development. Implementing solutions early will be less costly than major fixes at the end of software development.

More hardware can fix performance issues.

Adding processors, servers or memory simply adds to the cost without solving any problems. More efficient software will run better and avoid potential problems that can occur even when the hardware is increased or upgraded. In short, adding more hardware is not a good substitute for performance testing.

The Testing Environment.

There is another hardware fallacy asserting that we can perform tests in an environment that may or may not resemble the actual production environment. For example, testing for a client on Windows assumes that the application will function perfectly for another client who will install the system in Linux. We must make sure to test in an environment as similar to the production environment as possible. Many elements from the environment affect a system’s performance. Some of these elements include hardware components, settings of the operating system, and the rest of the applications executed at the same time.

Testing each part equals testing the whole system.

Thinking that one performance test will prevent all problems in itself is a problem. While it is important to isolate functions for performance testing, the individual component test results do not add up to a system-wide assessment. But it may not be feasible to test all the functionalities of a system. A complete-as-possible performance test must be designed using the resources available.

Performance Test Tools

There are a wide variety of performance testing tools available in the market. Below is a hand-picked list of the Best Performance Testing Tools:

Apache JMeter — helps you measure and analyze software performance. It’s an open-source tool based on Java that people use mainly for testing web app performance, but it also finds usage on other services. It can test performance for both dynamic and static resources, as well as dynamic web apps. In addition, you can use it to simulate heavy loads over a server, network/object, or group of different servers to test its strength and analyze total performance under varying load types.

BlazeMeter — gets you massive scale load and performance testing directly from your IDE. Plus, see what your user sees under load with combined UX & load testing. You get mock services to visualize your entire system and simulate slow network latency and slow responses to ensure software performance and quality. In addition, you can also control arrival rates, hits/sec, and threads in real-time.

Locust — is an open-source load-testing tool that lets you define user behavior using Python code and flood your system with millions of users simultaneously. It’s a highly distributed and scalable performance testing tool that supports running tests that are spread across multiple machines and let you simulate a massive number of users with ease.

Micro Focus LoadRunner — It tests applications and measures system performance and behavior under load. Simulating thousands of concurrent users, you can record and analyze application performance.

LoadNinja — This cloud-based load testing tool empowers teams to record & instantly playback comprehensive load tests, without complex dynamic correlation & run these load tests in real browsers at scale. It helps you diagnose app performance issues with highly accurate and actionable data. It provides results that are easy to read and doesn’t need extensive programming.

Final Words:

In Software Engineering, Performance testing is necessary before marketing any software product. It ensures customer satisfaction & protects an investor’s investment against product failure. Performance testing will determine whether their software meets speed, scalability, and stability requirements under expected workloads. Applications sent to market with poor performance metrics due to nonexistent or poor performance testing are likely to gain a bad reputation and fail to meet expected sales goals.