Guide to Performance Testing
What is performance testing?
Performance testing is a type of software testing that measures how well a system performs in terms of speed, stability, scalability, and resource usage under various workloads. This type of testing helps in identifying performance bottlenecks and bugs that might affect the system's performance when it is deployed in a production environment. Performance testing also helps to identify areas of improvement for future versions of the software.
Why it is important?
Performance testing is important because it helps ensure that web applications, software, and hardware products perform optimally in terms of speed, scalability, and reliability. It helps identify bottlenecks in applications so that developers can make improvements to ensure that the user experience is not hindered by slow or non-functional features. Performance testing also ensures that companies are able to maximize their resources and minimize costs associated with inefficient systems. Finally, it helps to identify any potential security risks which may arise from bugs or other issues which may occur during use.
What are risks associated with not doing performance testing?
Insufficient user capacity: Without performance testing, you may not be able to accurately estimate the number of users that your system can support and may not be able to scale appropriately.
Poor user experience: Performance testing helps identify and address any bottlenecks or other issues that could lead to slower response times, which can impact the user experience.
Security vulnerabilities: Performance testing can help identify security vulnerabilities related to how a system handles unexpected levels of usage or data.
Data Integrity Issues: Performance testing helps ensure that your system is capable of handling large volumes of data without compromising integrity or accuracy.
Unanticipated Costs: Without performance testing, unexpected costs can arise from the need for additional hardware or other changes to accommodate unexpected levels of usage.
How to do performance testing?
Performance testing is the process of determining how well an application or system performs under a given workload. It is designed to identify any potential bottlenecks, measure system performance and identify areas for improvement.
The steps for performing performance testing include:
Identifying the workload: This involves understanding the users of the application and their usage patterns, including peak usage times and typical user activities.
Setting up test environments: Performance tests are typically conducted in a closed environment with specific hardware and software configurations that closely match the production environment.
Selecting test tools: A variety of performance testing tools are available to simulate user activity and provide metrics on system performance.
Establishing performance baselines: Before conducting performance tests, it is important to establish baseline performance metrics in order to compare results.
Executing the tests: This involves running the tests and collecting data on system performance.
Analyzing the results: The data collected during the tests can be analyzed to identify any potential bottlenecks or areas of improvement in system performance.
Reporting the results: The results of the performance tests should be documented in a report that can be used to inform decisions about system improvements or upgrades.
Metrics for Performance Testing
Performance testing generally involves evaluating the speed, stability, scalability, and reliability of a computer, network, software program or device. Performance testing measures the quality attributes of a system such as responsiveness, throughput (or bandwidth), and/or stability under a particular workload. The following are some of the most common metrics used for performance testing:
Response Time: Response time is the amount of time it takes to complete a task. It is calculated by subtracting the starting time from the ending time of a task.
Throughput: Throughput is the amount of data that can be processed over a given period of time. It is calculated by dividing the total amount of data processed over a certain period by the total time it took to process that data.
Error Rate: Error rate is the percentage of incorrect requests or tasks that are completed successfully. It is calculated by dividing the number of errors by the total number of requests or tasks attempted.
Resource Utilization: Resource utilization is the amount of a computer's resources (e.g., memory, CPU, disk space) that are being used at any given time. It is calculated by dividing the total amount of resources used over a certain period by the total amount of resources available during that period.
Scalability: Scalability refers to the ability of a system to handle increased workloads without negatively affecting its performance. It is calculated by measuring how quickly and effectively a system can increase its capacity when presented with increased workloads.
Reliability: Reliability is the ability of a system to remain available and to perform its intended functions without interruption, or with minimal interruption. It is calculated by measuring the number of successful transactions (e.g., requests or tasks) over a certain period of time, divided by the total number of transactions attempted during that same period.
What are list of open source tools available to do performance testing?
- Apache JMeter
- Gatling
- LoadRunner
- The Grinder
- NeoLoad
- Siege
- WebLOAD
- Tsung
- OpenSTA
- Flood IO