Performance Testing

Understanding Performance Testing: Why It Matters for Your Application’s Success

 

Have you ever been in a situation when too many people are requesting something from you at the same time? When you're so overloaded with queries and requests that you just stop responding to them?

 

Everybody has those moments occasionally, and your website or software program is no exception. We'll talk about the importance of performance testing in the software development life cycle nowadays.

What is the Importance of Performance testing?

 

The following are some of the reasons why a company might decide to implement performance testing:

 

Ensures System Reliability: Finds performance issues and fixes them before end users are affected. makes sure the program functions properly even under heavy consumer demand, increasing its dependability.

Validates Scalability: Checks the system's capacity to manage higher data volumes or user demands. Ensures that the application can expand with the company without affecting functionality.

Optimise resource utilisation: When system resources are unused, it increases the possibility of achieving possible cost savings through improved performance and aids in making wise decisions about investments in hardware and infrastructure.

Support the business goal: Increase client retention and happiness, which in turn promotes the product's commercial success and improves the brand's reputation through dependable, high-performing applications.

 

How to Conduct Performance Testing?

 

Step 1: Identify Performance test scenarios.

Identify the most frequently used pages, features, or workflows (e.g., login, checkout, search).  Pay attention to tasks that are essential to achieving company goals or ensuring user approval. High-priority features should be tested first, but make sure all application pages are also tested based on the business needs.

 

Step 2: Performance test script creation.

When writing scripts, use right Tools  such as Gatling, LoadRunner, K6, or JMeter. Simulate actual user behaviours, such as uploading files, submitting data, and browsing. When simulating actual behaviour, include characteristics such as think time (the amount of time the user pauses between actions). In order to support different test situations, make sure scripts are reusable and modular.

 

Step 3: Setup Test data.

Create accurate test data that captures real-world use trends. Make sure databases have enough records to replicate situations at the production scale and sensitive data is categorised or hidden, and take data privacy laws into account. 

 

Step 4: Configure Concurrent Users and Ramp-Up Time

Establish User Load: Determine how many users can be active at once depending on anticipated traffic.

Ramp-Up Time: To replicate actual traffic growth, step up the user load gradually over a predetermined amount of time.

Peak Load: Model as much traffic as is anticipated during peak hours.

Stress Testing: Find the system's breaking point by exceeding the peak load. Accurately adjust these values by using performance tools.

 

Step 5:  Environment Setup

Before deployment, a production replica that replicates real-world conditions is called Preprod or staging environment. Determine that the performance test environment is isolated and dedicated, meaning that no other processes or users should disrupt the testing process. To avoid unexpected activities during testing, such as database alterations or system upgrades, restrict access to the environment. The performance Test scripts should always run in a dedicated environment where the Software team should not use.

 

Step 6: Run the tests.

Execute the performance test scripts with the specified number of concurrent users, ensuring that the application's functionality is tested under expected load conditions. Additionally, verify that the records generated during the performance tests are accurately created.

 

Step 7: Evaluate the Performance Metrics

Identify performance bottlenecks thoroughly evaluating key metrics such as response time and throughput time through the generated report. Analyse how the system handles varying loads to pinpoint areas of delay or inefficiency. This detailed assessment helps uncover performance constraints and provides insights for optimisation.

 

Step 8: Continuous Monitoring and Testing

Performance testing should be incorporated into the CI/CD pipeline for routine evaluations. Keep an eye on the system when it's in use to spot any performance issues. The Performance Test Scripts should be updated when there is an application change.

 

Explaining the Various Types of Performance Testing

 

1. Load Testing

Load testing aids developers in understanding how a system behaves when subjected to different load conditions. An organisation replicates the anticipated number of concurrent users and transactions over a period of time in order to confirm predicted response times and identify issues throughout the load testing process.  

Prior to a system or program becoming live, this kind of test assists developers in figuring out how many people it can support. A developer can also suggest load features of an application that are specialised to testing, like a checkout cart on a website. 

 

2. Stress Testing

To evaluate a system's performance beyond its expected capacity limitations, technicians subject it to higher-than-expected traffic volumes. Soak and spike tests are the two subtypes of stress tests. Software developers may learn about the scalability of a workload by doing stress testing. In order to identify the possible breaking point of an application based on resource utilisation, stress testing places a demand on hardware resources. Solid-state drives, RAM, hard drives, and CPUs are examples of resources. 

 

3. Endurance Testing

A product is tested with a high workload across an extended period of time in endurance testing, a non-practical type of programming testing. The behaviour of programming programs that are not supported is evaluated in this way. In order to ensure that the application can handle the increased load without experiencing a breakdown in reaction time, this testing is essential.

 

4. Scalability Testing

Software's capacity to scale performance metric characteristics up or down is the basis for scalability testing. For instance, a scalability test based on the quantity of user requests may be conducted by testers.

 

5. Capacity Testing 

Similar to stress testing, capacity testing evaluates traffic loads according to user count, though the amount of traffic varies. A software program or environment's capacity is tested to see if it can manage the volume of traffic that it was designed to handle.

 

About the Cloud Performance Testing

 

Cloud-based performance testing is also available to developers. Cloud performance testing has the advantage of allowing for larger-scale application testing while preserving the financial advantages of cloud computing. Initially, companies believed that transferring performance testing to the cloud would simplify and optimise the process. 

The idea was that they could move the process to the cloud, which would take care of all of their issues. But as soon as they started doing this, businesses discovered that there were still problems with cloud performance testing since they lacked complete white box knowledge of the cloud provider.

 Complacency is a problem when transferring an application from an on-premises setting to the cloud. Once the program hits the cloud, developers and IT professionals could believe that it functions the same way. They may decide to move forward with a rapid deployment while limiting testing and quality assurance. Testing may be less accurate than on-premises testing since the program is being tested on hardware from a different manufacturer.

 

What are the Best Tools for Performance Testing?

 

JMeter: JMeter is an open-source performance testing tool. It is possible to create load tests for web and application services using JMeter, an Apache performance testing tool. In addition to covering topics like graphs, thread groups, timers, functions, and logic controllers, JMeter plugins offer versatility in load testing. Both a command-line mode for load testing Java-based operating systems and an integrated development environment for recording tests for web apps or browsers are supported by JMeter.

LoadRunner:Applications' performance under load is tested and measured using LoadRunner. In addition to simulating thousands of end users, LoadRunner can record and analyse load testing. 

NeoLoad: Neotys created NeoLoad, a tool for load and stress testing web and mobile applications that is especially intended for DevOps and continuous delivery applications. Web, database, and application servers may be monitored by an IT team using the software. NeoLoad can run testing on-site or in the cloud and can replicate millions of users.

K6: Developed for modern DevOps procedures, K6 is an open-source performance testing tool. This developer-focused tool is designed to test the scalability, performance, and dependability of web apps, microservices, and APIs. Scripts are written in JavaScript, so developers that know the language may use it. Also, makes performance test definition simple and easy using its scripting interface.

 

Conclusion

 

In conclusion, performance testing is an essential procedure that tests an application's scalability, stability, and speed under various circumstances. It ensures the best possible user experience and system dependability by locating any bottlenecks and making sure the program satisfies performance standards. Additionally, it increases resource efficiency, avoids expensive downtime, and promotes business continuity, making it an essential part of modern software development. Performance testing should be given top priority to make sure your application is prepared to satisfy user demands and succeed in the harsh digital market of today.