Performance testing proves to be an integral part of software engineering. It is the behaviour of a system under specific working conditions. It is the speed, stability and scalability testing of a software application under explicit expected conditions so that it performs well.
REQUEST A CALLPerformance testing proves to be an integral part of software engineering. It is the behaviour of a system under specific working conditions. It is the speed, stability and scalability testing of a software application under explicit expected conditions so that it performs well. Here we will cover all the basic concepts of performance testing; its importance, types, methodologies, tools and best practices.
Performance testing is critical for the following reasons
1. To ensure customer satisfaction: Poor performance can result in the user discontinuing the software. And bad words about a software means a terrible reputation to the organisation.
2. To know the bottlenecks: It helps to find out the performance bottlenecks in the system like response getting too slow to the customer, memory leaks and low throughput.
3. To verify scalability: Performance testing is done in recent times, majorly to verify if the application is scalable enough to withstand anticipated growing loads.
4. To verify Reliability: that the application will perform adequately across all the parameters such as peak times.
5. Optimization: Helps to optimize an application's performance since performance issues have been found through testing.
Performance testing can take several forms; each form represents a specific purpose or goal.
Load Testing
Stress Testing
Endurance Testing (Soak Testing)
Spike Testing
Volume Testing
Scalability Testing
This type of testing tests a system performance under an expected load condition. The aim is to be able to determine how the application behaves with multi-users accessing it at the same time. For Example, testing an e-commerce website during a sale period when a high volume of users is expected.
The objectives are:
• Maximum operating capacity
• Identify the bottlenecks
• Ensure that the application will handle peak traffic condition
Stress testing is basically testing the system on extreme conditions, so say, beyond the working capacity. This is done with the goal of determining its breaking point. For example, running a simulation with twice the anticipated number of users to observe how the system copes with the additional load.
Objectives are:
• To make sure the system is robust enough.
• To define the system's breaking point
• To ensure that the system recovers gracefully from failure.
Endurance testing also known as Soak Testing is the type of testing that is done by putting the system under a significant load for an extended duration, for example, running a banking application continuously for a week to check for long-term stability issues. This testing enables the entities to identify the issues that will come up in a time frame like memory leakage.
Objectives are:
• Determine the system's ability to withstand an extended load.
• Detect a performance drop.
• Test system reliability over a specified duration.
Spike testing is the simulation of a sudden increase in load, followed by a sudden decrease to test the system's response to rapid variations in load. On an online store, simulating a sudden increase of users in a flash sale can be an example of Spike testing.
Objectives incudes :
• Find the performance of the system under sudden spikes in load.
• Determine that the system can recover from the rise without time-consuming retries.
• Check the system for susceptibility under sudden spikes.
Volume testing is the type of testing that is carried out using test data that is more than the actual data. For example, Testing a database with millions of records for query and update performance.
Objectives:
• Determining how the system is handling large data volumes.
• Find performance problems related to data storage and access.
• Determine the efficiency of the database in handling huge data.
Scalability testing is performed to check the scalability of the system, whether it is capable of scaling up or down to respond to increased or decreased demand. By steadily increasing the number of users to determine at which point the performance of the system starts to degrade is a case of Scalability Testing.
Objectives are :
• Determine the system's scalability constraints.
• Determine the required changes in the infrastructure for scaling.
• Determine that the application can be scaled horizontally or vertically.
There is quite a range of performance tools for running performance tests. These tools have their unique features and capabilities. Below are the top and most used performance tools:
Apache JMeter is a free open-source tool that is used for conducting load testing and performance measuring in web applications. It is used to mimic a heavy load on a server, group of servers, network, or even object, to determine its strength and evaluate the overall performance under different types of loads.
Supports multiple protocols like HTTP, HTTPS, FTP, JDBC etc
User-friendly GUI for creating test plans
Reporting and visualization of skilled scope
Simulate multiple users
Use Case: Web application performance testing, ideal for open source looking for developers and testers.
LoadRunner is a popular performance testing tool designed by Micro Focus. It assists in determining and guaranteeing the scalability and alignment of businesses. It operates on a trial version and possesses sophisticated analysis and reporting tools.
Support multiple protocols: Web, MQTT, Citrix and SAP etc
Real-time performance monitoring
Detailed analysis and reporting tools
Scalable: Supports large-scale test environments
Use Case: Permits the full version to be used commercially across organizations, assuring that the performance test data is established and assured to meet the scalability and business alignment.
Neoload by Neotys is another performance testing tool for web and mobile applications. It has a user-friendly interface and is meant for creating and executing load tests.
Drag and drop interface for advanced scripting
Integration to CI/CD tools, Jenkins and Bamboo
Load testing of cloud-based
Real-time monitoring and reporting
Use Case: Ideal for agile teams looking to integrate performance testing into their continuous integration/continuous delivery (CI/CD) pipelines.
Gatling is an open-source performance testing tool designed for simplicity, scalability and to be used easily. It is written in Scala and its powerful DSL is used for defining performance tests.
High performant and scalable
User-friendly and expressive DSL scripting interface
Provides efficient reporting along with comprehensive metrics
In-built support for web protocols
Use Case: Ideal for web application developers as a simple, scalable and easy-to-use tool with the most capable scripting language for test creation.
WebLOAD by RadView is an enterprise-based performance testing tool. It is ideally suited for enterprise applications and supports a wide variety of technologies. It offers robust analysis and reporting capabilities.
Test web, mobile and cloud applications
Integration with APM tools such as Dynatrace and AppDynamics.
Strong load test scenarios with real-time monitoring
Strong analytics and reporting
Use Case: Ideal for large-scale enterprise applications that need full-scale performance testing and elaborate analysis.
A regular approach to performance testing will ensure the application is tested properly as expected. There may be different methodologies in the market to do the same thing to come up with accuracy. Follow the steps below for a general performance testing methodology:
1. Requirement Gathering
2. Test Planning
3. Test Environment Setup
4. Test Design
5. Test Execution
6. Monitoring and Analysis
7. Reporting and Retesting
Objective: Gaining an understanding of the performance requirements and acceptance criteria for the system under test.
Activities:
• Some key performance indicators to be identified are response time, throughput and resource utilization.
• Information regarding expected user load and peak usage hours
• Understanding the architecture and components of the system
Output: A comprehensive understanding based on the performance requirements and objectives.
Objective: Develop a detailed performance test plan outlining the scope, objectives, resources, schedule and deliverables.
Activities:
• Clearly defining the scope of testing (components, load scenario, etc.)
• Resources required to be identified (hardware, software, persons)
• Make a detailed schedule with milestones
Output: A well-defined performance test plan that will be a roadmap of a testing process
Objective: To set up a test environment that is a replica of the production environment
Activities:
• Set up hardware and software as per the production specifications
• Configure network settings and other such environmental variables
• The environment should be separated from other activities
Output: A stable and reliable test environment ready for performance test
Objective: To design test cases and scenarios based on the requirements and test plan
Activities:
• Develop detailed script of the test simulating user interaction
• Define datasets and input parameters
• Define performance benchmarks and expecting results
Output: Well defined test cases and scenarios ready for execution.
Objective: Perform the performance tests and measure the metrics.
Activities:
Execute test scripts using identified performance testing tools.
Transaction monitoring for performance and resource use.
Record such metrics as response time, transactions per second, error rates.
Outcome: Raw data and metrics depicting the state of the system under different loads.
Objective: Analyse records obtained during performance tests to pinpoint performance problems.
Activities:
Perform system behaviour and resources use analysis by monitoring tools.
Discover bottlenecks, memory leaks and other performance problems.
Measure real performance to compare it with the benchmark.
Outcome: The analysis with a detailed description of performance problems and suggestions for solution.
Objective: Report the findings and repetition testing after performance tuning.
Activities:
Prepare a detailed set of reports that include the test results, issues and recommendations.
Sharing reports with stakeholders and developers.
Performance tuning and further test to re-execute if the change was positive.
Outcome: A detailed performance report and an optimized system for a better performance.
Performance testing is a very key element of the software development lifecycle, encompassing the assurance of meeting expectations by users and flawless functioning under any condition. As a result of systematic evaluation and validation of system performance upon load testing, stress testing and other methodologies, executed at an early stage, numerous potential bottlenecks and vulnerabilities can be identified and countered. This proactive approach not only enhances the reliability and scalability of applications but also contributes to a superior user experience, minimizes downtime and supports business growth. performance testing is indispensable for delivering quality software that can scale, adapt and perform optimally in today's dynamic digital landscape.
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