Performance Testing is a software testing process that is used for testing the response time, speed, stability, reliability, scalability, and usage of a software application under a particular workload. The primary purpose of performance testing is to identify and eliminate the performance bottlenecks in the software application.
It is done to provide stakeholders with information about the performance of an application regarding speed, scalability, and stability. Without Performance Testing, the software will suffer from issues such as: running slow, inconsistencies across different operating systems.
Performance testing determines whether the software meets speed, stability, and scalability requirements under expected workloads. Applications sent to the market with low-performance metrics due to nonexistent or no performance testing do not gain a good reputation and fail to meet expected sales goals.
Performance Testing Process
- Identify the Test Environment: Identify the performance test environment and the production environment, which includes the software, hardware, and network configurations. Having an understanding of the performance testing environment enables more efficient planning, design, and helps you identify testing challenges. In some situations, this process should be revisited periodically throughout the project’s life cycle.
- Identify the Performance Acceptance Criteria: Identify the response time and resource utilization goals and constraints for performance testing. Those constraints and ideals may not capture the project success criteria; e.g., using performance testing to evaluate the combination of settings will result in the most desirable performance characteristics.
- Plan and Design Tests: We are identifying critical scenarios to determine variability among representative users, such as unique login credentials and search terms for performance testing. The team must also choose how to simulate, define the test data, design performance tests and establish metrics to be gathered.
- Configure the Test Environment: Prepare the tools, environment, and resources that are necessary to execute each strategy for performance testing. Ensure that it is instrumented for resource checking as required.
- Implement the Test Design: Develop the performance tests with the test design best practice that will result in a good performance testing scenario.
- Execute the Test: Run and check your tests. Validate the test data and results collection. Execute the performance tests using the identified performance testing tool.
- Analyze Results, Report, and Retest: Consolidate performance testing results data. Prioritize the remaining tests and re-execute them. When the values are within accepted limits, none of the set has been violated, and all of the information is collected, you have finished testing that particular scenario in that specific configuration.
This is the performance testing process that needs to be followed for any non functional testing in a project. We need to conduct performance testing and design performance of the scenarios so that there are no performance problems. The resource usage should also be monitored while testing.
- Load Testing environments do not have the same configuration as production, and it may produce misleading results.
- If you don’t want a load testing environment, you can avoid all of the costs associated with testing tools, licensing, hardware, personnel, etc.
- Testing performance against the production allows you to avail of load injection tools and services.
- Testing performance against the production ensures you validate the entire technology stack that includes firewalls, network access points, load balancers etc.
- It provides an environment at full capacity to a scaled-down environment.
- The code is live so the issues may cause problems to the users.
- Testing should be conducted during non-peak periods.
- There will be a limited opportunity in services that serves a global user base, e.g. bank trade processing systems.
- The execution window is typically very narrow.
- Real users might experience degradation while the execution runs.
- Less instrumentation available which makes it more difficult to diagnose issues.
Performance Testing Metrics
Performance metrics are generally used to calculate the performance bottlenecks and determine the application areas that are weak and create common performance bottlenecks in the applications.
- They are used to track the project’s progress.
- They are used to make a baseline for all the performance testing.
- By using metrics, you can measure the leading cause of the problem.
- Using metrics, you can compare the result of the different performance test and determine the impact of any changes made to the application.
- It helps in the improvement of the quality of the product.
- It provides an exact output of the activity and finds out the areas which require attention.
Basic parameters that are monitored during performance testing
- Bandwidth — It shows the bits per second used by an interface.
- Private bytes — Several bytes a process that can’t be shared amongst other functions.
- CPU interrupts per second — The average number of hardware interrupts a processor is receiving and processing each second.
- Disk queue length — is the avg. No. of reading and write requests queued for the disk during a sample interval.
- Processor Usage — The amount of time a processor spends on executing the non-idle threads.
- Maximum active sessions — The max number of sessions that are active at once.
- Page faults/second — The rate at which the processor processes fault pages.
- Amount of connection pooling — The number of requests which are met by pooled connections. The more demands met by links in the pool, the better the software will be.
- Thread counts — An application’s health can be measured by the no. of threads running and currently active.
- Garbage collection — It returns unused memory to the system. Garbage collection is monitored for efficiency.
- Database locks — The locking of tables and databases needs to be monitored and carefully tuned.
- Top waits — They are monitored to determine how wait time can be cut down while dealing with how fast data is retrieved from memory.
- Hit ratios — The number of SQL statements handled by cached data instead of expensive I/O operations. It is a place where you can start solving bottlenecking issues.
- Hits per second — The number of hits on the web server during each second of a load test.
- Disk time — The amount of time the disk is busy executing a read or write request.
- Response time — when a user enters a request until the response’s first character is received.
- Bytes total per second — The rate at which the bytes are sent and received on the interface, including framing characters.
- Memory use — The amount of physical memory available to the processes on your system.
- Throughput — The rate a network receives requests per second.
Types of Performance Testing
It measures system performance as the workload increases which helps in the testing load of the application. The workload could mean users or transactions. The system is monitored to measure the response time and system resources as the workload increases. The workload falls within the parameters of normal working conditions.
It is also known as fatigue testing, and it is meant to measure the system’s performance outside the normal working conditions. The application is validated with more than the defined user load that can be handled. The goal of this testing stress is to test performance of the software stability during excess load on the application.
It is a type of stress testing that checks the application’s performance when workloads are increased repeatedly and quickly. The workload is beyond expectations for short amounts of time. Also measures the resource usage like private bytes, speed scalability etc
Endurance testing is also called soak testing, and it is an evaluation of how the application performs with a typical workload and with an extended amount of time. The main aim of endurance testing is to check for system problems such as memory leaks.
Scalability testing is used to determine whether the application is effectively handling the workloads. This is determined by gradually adding to the user load while checking system performance. The workload may be at the same level, while resources may change.
Volume testing tells how efficiently the application performs with a large, projected amount of data. It is also called flood testing because the execution floods the system with a large amount of data.
These are some of the different testing types of performance testing that are covered as part of this performance testing tutorial.
Common Performance Problems
The most common non functional testing problems revolve around response time, speed, load time, and poor scalability. Rate is one of the essential attributes of an application. A slow application will lose potential users. Performance testing ensures that an application runs fast enough to keep the attention and interest of the user intact. Following are the problems faced:
- Bottlenecking – Bottlenecks are a hindrance in a system that degrades system software. It happens when either coding errors or hardware issues cause a decrease under specific loads. It can be generally fixed by either fixing low running processes or adding additional Hardware. Conduct stress testing to confirm the results
- Long Load time – Load time is generally the initial time taken for an application to start. This is usually kept to a minimum. However, some applications are impossible to load in under a minute. Load time should be under a few seconds if possible.
- Poor scalability – A software product suffers due to insufficient scalability when it is not able to handle the expected number of users. Load Testing should be done on applications that can take the anticipated number of users along with stress testing.
Best Performance Testing Companies
A1QA is a quality assurance and software testing company that was founded in 2002. It is situated in Denver, where they have a team of 200+ employees with specialisation in application testing and cybersecurity.
They first serve mid-market clients in the IT and telecommunications industries. A1QA helped an economic research institute in the development of a bespoke economic case management app.
QA Mentor is a software testing company, and it is located in New York. It has 175 employees, and it was founded in 2010. Application testing services is their specialisation.
QA Mentor offers to identify bugs in a planning platform’s software. With the help of a matrix, the team tested the platform and provided daily updates. The client enjoyed working with them.
- Morgan Stanley
QualityLogic is a software testing company, and it is located in Boise, Idaho, with its offices in California and Oklahoma. They have a team of more than 68 people who specialise in application testing. They work with enterprises and mid-market clients in the entertainment, art and music industries.
QualityLogic offers software testing services for a communication application. They conducted manual and exploratory testing for mobile and web apps.
DeviQA is a software testing company, and it is located in Kharkov, Ukraine. It was founded in 2010. They operate with a team of more than 100 engineers, and application testing is their specialization. They work with small businesses and enterprises across various industries. DeviQA enhanced the testing services environment for a big data system firm. They managed to improve the quality and testing environment of a complex social media analytic solution.
- Bizness Apps
- Cipher health
Best Performance Testing Tools
LoadRunner is the industry leader when it comes to performance testing. It has all the protocols that cover almost all the technologies. Also, it integrates very well with multiple other tools like ALM, etc. This is the preferred one among all the testing tools from various load testing tool
- It is commercial software.
- Supports multiple protocols
- Has multiple features like virtualization
- Integrates well with multiple tools
- Best Performance Testing tool.
- Open-source scripts can also be executed
- Good test result is generated from this software
Pricing depends on the protocol bundles and the number of vusers required.
JMeter is an automation testing tool that performs load, functional test, regression test, on different technologies. It supports various types of applications, protocols, and servers like SOAP, TCP, FTP. SOAP, LDAP MOM, shell scripts, Mail Protocols, Java objects, database. Also, this can be used for functional testing.
- It is open-source software.
- Currently the hottest load testing tool in the market
- Interactive and straightforward GUI.
- It is highly protractile.
- The test plans are stored in XML format.
- It is platform-independent.
- Best API automation tool.
It is free to use.
The eggplant testing tool is an automated application testing and debugging tool. It tests a single source of truth for the user experience. Eggplant’s solutions can try cases at any layer from the database. Easy to define performance test scenarios and helps to identify performance problems.
- It is the best GUI automation testing tool.
- The testing is done from the user perspective.
- It is reliable, and the tests are done quickly.
- It uses a single test script for various scenarios.
- Integrate with popular test management tools.
The license costs around $3400—the second stream costs around $1,700, and third stream around $850.
The above mentioned are some of the performance testing tools as examples for this tutorial. There are a lot more testing tools that can be used for various software testing purposes.
Performance Testing FAQs
Why is there a need for performance testing?
Performance testing is a good platform because of the following reasons.
It is used to verify the response time for the user’s numbers.
It also offers the capacity of load testing of the application to the maximum level.
It offers the facility for managing the transaction quantity.
Under both the expected and unexpected load of the user, the application stability is provided.
It makes sure that response time is provided to the users properly during production.
What are the mistakes that are made during performance testing?
The mistakes that are usually committed during Performance Testing are:-
Inappropriate base-lining of configurations.
Too small run duration
Direct jump to multi-user tests
Incorrect extrapolation of pilots
Test results not validated
Unknown workload details
Confusion on definite of Concurrent users
Lacking long-duration sustainability test
Network bandwidth not stimulated
Underestimating performance testing schedules
Mention the entering and exiting criteria in case of performance testing?
The beginning of the performance testing is done at the design level. Once the testing is done, results are collected, and they are analyzed to make improvements regarding their performance. During the whole process performance, tuning is done. The factors on which it depends are scalability and reliability during the presence of the load, application release time, and tolerance criteria of performance and stress.
What are the sub-genres of the performance test?
The sub-genres are mentioned below.
Load Testing: The performance testing is done to examine application performance based on a load termed as Load testing. The load increment is done by increasing the number of users performing a specified work within a specified time limit.
Volume Testing: This test is performed to find the quantity of data that a system can handle effectively and efficiently.
Stress Testing: It is performed to evaluate the system’s performance by increasing users’ numbers than the requirements. It is done to check at which level the application may crash.
Spike Testing: It is used to sterling what will happen if there are a considerable increment and decrement in the number of users of the application system.
Soak Testing: It is a great deal of load for a long time on the application system. Soak testing is performed to determine the application’s behavior in terms of response time and stability.