Performance testing determines how a system behaves under different workloads. It evaluates an application's speed, responsiveness, stability, scalability, and resource utilization.

The primary aim of performance test automation is to detect application performance issues causing the applications to slow down or give a bad user experience. In this detailed guide, we will share all the details about how performance testing works and what is the best automation tool to conduct these tests.

performance testing of apps

What Is Performance Testing?

Performance testing involves testing an application under the required load to evaluate its responsiveness and resource usage. During the performance test, the QA tester examines several key factors of an app or website’s performance, including:

Stability: Confirming the application remains stable and functions properly under varying workloads.
Scalability: Measuring how well the application handles increasing user load.
Speed: Verifying that the application's response times are adequate.

Why Is Performance Testing Important?

Performance testing is important in software quality assurance because it ensures the software works well under different conditions. It checks how fast the system responds, how much load it can handle, and if it stays stable when many users access it simultaneously.

Here are some major reasons performance testing is done in QA:

Improves User Experience: Checks if users have a perfect experience by identifying and resolving speed, responsiveness, and stability issues.
Prevents Failures: Helps spot slowdowns early, lowering the chance of crashes or issues in real-time use.
Validates Scalability: Improves the application’s ability to handle multiple user requests without significant performance degradation.
Supports Capacity Planning: Provides insights into the hardware or infrastructure needed to maintain optimal performance.
Strengthens Security: Exposes vulnerabilities that can appear under heavy load, helping to prevent breaches.
Optimizes Resource Utilization: Validates that CPU, memory, and network resources are used efficiently.

QA automation testing

6 Types of Performance Testing

Here’s a brief description of each type of performance testing:

1) Load Testing

This testing checks how a system behaves under expected user loads. Its goal is to identify performance issues, such as slow response times when the system is under normal or in heavy traffic. This testing helps verify that the system can handle the anticipated user demand without affecting performance.

2) Stress Testing

Stress testing involves pushing the system to its limits to see how it behaves under extreme conditions. It helps to identify the breaking points and the system's ability to recover from failure.

3) Soak Test

Soak testing, also known as endurance testing, checks the system's performance under a high load for an extended period. This confirms that the system can handle continuous usage without performance degradation.

3) Spike Testing

Spike testing tests the system's reaction to sudden, large spikes in traffic. It helps identify how well the system can scale up quickly and how it recovers from extreme surges.

4) Volume Testing

Volume tests the system's performance under large volumes of data. It tests the system’s ability to handle massive amounts of input, output, and database operations.

5) Scalability Testing

Scalability testing measures the system's ability to scale up or down depending on user load, transaction volume, and data size. This test automation helps us determine how to grow the user load while maintaining performance.

6) Capacity Testing

Capacity testing helps determine the system's maximum capacity under both normal and peak conditions. This confirms that the system meets the required capacity before it is deployed for real world use.

performance testing types

Difference Between Performance Testing and Performance Engineering

Some people confuse performance engineering with performance testing. So, let’s distinguish between these terms:

Performance Testing

Focus: Primarily tests the system's performance under certain conditions (load, stress, etc.). It identifies performance such as slow response times, crashes, or errors.
Objective: The main goal is to authenticate that the system meets predefined performance requirements.
Scope: Reactive in nature. It’s usually conducted after the software is developed to detect and resolve performance issues.
Techniques Used: Includes testing methods like load, stress, and spike testing to observe how a system behaves under specific conditions.

Performance Engineering

Focus: Designing, building, and optimizing software for performance from the start.
Objective: Aims to improve performance proactively. The architecture, design, and code are optimized for performance.
Scope: Proactive and holistic approach. It encompasses performance testing and works at the design, development, and maintenance phases.
Techniques Used: Involves practices like optimization of code and improving system architecture, along with continuous monitoring to prevent performance issues.

automated performance testing

Step-by-step Guide to Performance Testing

Curious to learn how you can easily conduct performance tests? Just follow this simple approach:

1) Identify Test Environment

Define hardware, software, network configurations, and testing tools.
Authenticating the environment mirrors production as closely as possible.

2) Determine Performance Metrics

Set clear goals for speed, scalability, stability, and responsiveness.
Define key metrics such as response time, throughput, memory usage, and CPU load.

3) Design Test Scenarios

Create test scenarios based on expected user behavior and workload.
Identify various user types and simulate their actions in the system.

4) Prepare Test Data

Gather or create the necessary data to mimic real-world scenarios.
Confirms the data is accurate, complete, and scalable.

5) Set Up Testing Tools/Frameworks

Choose and configure performance testing tools/frameworkss (e.g., vStellar Test, JMeter, LoadRunner, or Gatling).
Prepare monitoring tools to observe server performance during the test.

6) Execute the Tests

Run performance tests like load testing, stress testing, spike testing, etc.
Gradually increase the load on the system and ensure adequate response.

7) Monitor and Analyze Results

Track system performance during testing by capturing metrics (response time, error rates, etc.).
Use logs and monitoring tools to identify issues.

8) Identify and Address Issues

Analyze the data collected during testing to find the root cause of performance issues.
Optimize code, adjust configurations, or scale the infrastructure as needed.

9) Retest

After resolving issues, retest to authenticate performance improvements.
Validate that changes positively impact the system's performance.

10) Report Findings

Create a detailed performance report covering all results, improvements, and recommendations.
Share it with relevant stakeholders for further action.

performance test automation

Success Metrics of Performance Testing

Success metrics are crucial for evaluating the outcomes of performance testing. They assess an application’s efficiency and overall performance under various conditions.

Here are the essential success metrics to consider during performance testing:

Memory usage: The portion of physical memory utilized by the application.
Network bandwidth: The rate of data transfer through the network interface.
Disk I/O busy time: Duration of the disk occupied with operations.
Private memory: Memory allocated to a process that isn’t accessible to other processes.
Virtual memory usage: The amount of virtual memory consumed by the system.
Page faults: Count of memory pages swapped to or from the disk due to hardware issues.
Page fault rate: The speed at which faulty memory pages are processed.
Hardware interrupts: The average number of hardware signals the processor handles per second.
Disk I/O queue length: The average number of read/write requests made to disk during a set period.
Packet queue length: The number of data packets waiting to be sent or received.
Network throughput: Total bytes transmitted or received by the network interface each second.
Response time: Time it takes the system to reply to a request.
Request rate: The number of requests the system or network receives per second.
Pooled connection reuse: Number of user requests fulfilled through reused connections.
Max concurrent sessions: The highest number of active sessions at one time.
Cached SQL statements: Number of SQL queries executed from cached data, reducing I/O operations.
Web server file access: Number of file access requests processed by the web server every second.
Recoverable data: The amount of data that can be retrieved after system failure.
Locking efficiency: Effectiveness of database/table locking mechanisms in managing resources.
Max wait time: Longest delay experienced while waiting for a resource to be available.
Active threads: Number of threads currently running or in use.
Garbage collection: Frequency at which unused memory is released back to the system.

vStellar Test performance testing

Conduct Your Performance Tests With vStellar Test

When it comes to performance testing, vStellar Test stands out as a powerful solution that simplifies the process with its smart features. With it, you can easily create and manage performance test cases customized to your application’s requirements. vStellar Test allows you to conduct all types of performance tests within a secure environment and without writing complex codes.

To get started, simply create your performance test cases by defining the scenarios that mimic real user behavior. vStellar Test also provides detailed documentation to guide you through the process.

Start optimizing your app’s performance today with vStellar Test! Book a demo today.

FAQs

1) What tools are used for performance testing?

vStellar Test, JMeter, LoadRunner, and Gatling can be used for performance testing. vStellar Test stands out because it's easy to use and helps testers create and run performance tests while giving clear feedback on the application's performance.

2) When should performance testing be conducted?

Performance testing should happen at different times during the software development process. It’s important to test early on to catch any issues and before big releases to ensure the app can handle many users. With vStellar Test, you can easily add performance testing to your workflow for regular checks.

3) Can performance testing be automated?

Yes, performance testing can be automated, which makes it easier and more consistent. vStellar Test offers test automation features that let you set up and run tests without doing it all by hand. This saves time and helps find performance problems sooner, keeping your application running well.

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