Why use performance testing?
It is important for businesses, especially enterprises using large-scaled apps to ensure that the software remains stable even during the most critical times and sudden peaks in traffic. Eliminating network issues, memory utilization, speed, and scalability problems is the task of Performance Testing. Various subtypes of performance tests and tools ensure the effectiveness and robustness of the application. Discover how performance testing relates to automation testing.
Performance testing can warn about speed, scalability, and stability issues. Websites, desktop, or mobile applications have to sustain an increasing number of users, offer secure gateway, and be scalable to allow the application to grow further and reach higher revenue. There are several reasons why to conduct performance testing:
- Fixes after performance testing improve application speed
- Fast application performance, more users attracted
- Find out application hidden risks
- Enhance the application scalability
- Test tech stack, databases, and API
Types of performance testing
Performance testing measures the response time of the application at a certain number of users (50, 100, 1500, or more). It helps measure how many users the application can sustain simultaneously, and where is the edge when the application breaks down. Performance testing also helps define the performance time.
How does Performance testing differ from Load testing?
Load testing measures the performance under stressful conditions we specifically create. If Performance testing defines the level of the app’s response at normal conditions, Load Testing is designed to find out the app’s behavior under increased numbers. Load tests gradually increase the number of users, until the system reaches the breaking point.
Stress testing checks how the application works under constant “stress”. Tests subject it to a high load for a long period analyzing how long the system can keep responding even if responding at slow speed. Increasing the load on the server usually results in an HTTP error 500 response code which means a point was reached when the server did not manage with so many requests.
Endurance testing is a non-functional type of testing and a subtype of Load testing. Also known as Soak Testing it verifies a system’s performance under a high load maintained for a significant amount of time. We extend a period on purpose to check how the app will behave.
Spike testing is a type of testing that determines the application performance when a sudden increase or decrease in load happens. It helps determine a system’s behavior in case of considerable deviations from a normal number of users.
Volume testing determines under what volume of data an application will fail, how it will fail, and what indicators can help to warn of an impending data issue. It is also a type of non-functional testing measuring a system’s performance at an increased volume of data in the database.
The application needs to scale up to an increasing number of users, which may lead to an increasing number of transactions, databases, or servers used. Scalability testing aims to discover what load the application can support and whether it is enough for expanding the application architecture.
In software, testing engineers can’t do without metrics which are defined as common measurements indicating the quantitative characteristics of the application if to speak about performance testing – processor or memory utilization, memory capacity, etc.
CPU-bound tasks can become bottlenecks for application performance. In performance testing, the measurement of CPU interrupts per second helps define the rate at which processes run under a limited speed of CPU.
- Response time
Response time measures how quickly or slowly the system processes the requests and sends back the response to a user.
Throughput is a measurement of the number of units passing through a system to be processed. Usually, this number is shown in the number of requests, clicks, transactions, reports per second, day, month, etc.
Network bandwidth provides the characteristics of the capacity of the communication channel. In performance testing, this measurement is used to denote the amount of data transmitted at a time.
- Memory utilization
Memory utilization analysis is necessary to know if the hardware size is enough to sustain a load of a certain number of users in the system. Memory is often a tough issue and can be optimized due to code improvements, proper allocation, garbage collecting, caching, and software frameworks that help manage it effectively.
Stages in performance testing
To test the application performance, engineers can use these steps:
1. Set clear objectives that ensure the need for performance testing
It is preferable to define reasonable objectives for testing. Then, choosing the right software testing tool or framework helps detect bugs most efficiently. Frameworks and tools for Performance testing can be JMeter, Splunk, WebLOAD, Load View, SmartMeter.io.
2. Agree on entry and exit criteria for testing performance
Entry criteria could be a document specifying the usage of non-functional tests by a team and types of performance testing used and agreed with a client in advance. Exit criteria define the point at which performance testing is considered finished and specifies which goals were met, what results were achieved.
3. Identify the environmental requirements
The team has to be aware of hardware, software, network configuration specifics, and tools needed for effective performance testing in the production-like environment.
4. Identify performance metrics and set an approach
The team has to define in advance the number of users that should be created in the datastore. Testing scripts have to check with metrics and ensure that correct responses are received. Besides, the task is to find the baseline metrics.
5. Plan performance testing activities
Designing performance testing scenarios should be done carefully to meet the goals of testing and not miss a thing. The team has to know the type of tests to perform (Stress testing, Load testing). The load models have to be defined for each test type.
6. Set up the performance test environment
Preparation of the testing environment includes checking load injectors’ capacity, alerting mechanisms, and access to the application logs.
7. Tests execution and analysis
Running the performance test, it’s important to pay attention to data generated, bugs found to improve performance in the course of the testing-development process.
The team back-ups all the data and concludes a report on successfully run and failed tests.
Investing in performance testing repays a lot in the form of end-users’ satisfaction, strong application potential on the market, and high-quality of the product in general. If you are looking for the QA engineering team for the project, talk with our digital expert, and find details on where to start.