Boost Efficiency with Automated Performance Testing

Performance testing aims to identify and eliminate performance bottlenecks in software applications in order to guarantee their software quality and ensure optimal user experiences with operating systems.

Testing plays an integral part in making sure systems run effectively - without it, users may experience slower response times or inconsistency within their operating systems which would ultimately have detrimental repercussions.

User experience (UX) testing can help determine whether or not your system can meet speed, stability and responsiveness requirements under heavy workloads, to create a positive user experience for all concerned parties.

Once functional testing is completed, performance tests should also be run.

Agile Developers may create performance tests as part of the code review process and they can be moved between environments as required - for instance between teams testing live environments and those monitoring them - as performance test cases move around easily.

Performance testing may include quantitative laboratory or production environments.

Performance tests must identify and satisfy requirements. Parameters that should be covered during performance assessments include processing speed, throughput bandwidth of networks, workload efficiency and reliability.

An organization may use response times of programs in response to user inquiries for actions as one means of measuring success; similar techniques could also be implemented at scale and developers should identify bottlenecks if their responses take too long to process.

Why Perform Performance Testing?

Performance testing can be used for a variety of reasons, including:

1. Bottleneck analysis can be used as a diagnostic tool in systems, where bottlenecks exist as single components or points that detract from overall system function and negatively affect performance.

   Even fast computers will struggle online if bandwidth drops below 1 megabit per sec - whether due to hardware limitations such as too many programs running simultaneously, browser bugs, or corrupt files in browser software.

2. Software testing can assist organizations with pinpointing performance-related software issues by pinpointing areas where applications might fail or lag, providing valuable preparation time before an anticipated major event takes place.
3. Vendor claims are verified by automated testing to ensure that the system is in line with what its manufacturer or seller has claimed. This testing process compares two or more devices, programs or other items.
4. Updates on application performance related to speed, stability, and scalability are disclosed to project stakeholders.
5. To avoid a bad name, an application that is released without performing performance testing may run poorly and cause negative word-of-mouth.
6. An organization can evaluate the speed, responsiveness, and stability of the software by contrasting two or more systems.

Get a Free Estimation or Talk to Our Business Manager!

Performance Testing Metrics

The key performance indicators or performance metrics can be used to evaluate the current performance of an organization.

Performance metrics include:

1. Throughput- The number of units of data that a system can process in a given time.
2. Memory- Memory is the working storage space that a processor, or workload has available.
3. Latency, or response time-The time between the users request and when a system responds to it.
4. Bandwidth- Data volume per second, which can be moved between workloads across a network.
5. interruptions caused by a central processing unit (CPU) per second. The number of hardware interrupts received by a process per second.
6. Average latency- Also known as wait time, this is the time taken to receive the initial byte following a request.
7. Average load time
8. Response time at its peak- The maximum time it takes to complete a request.
9. Error rate- Percentage of all requests that are incorrect compared to other requests.
10. Disk time.
11. The maximum number of sessions that can be open at one time.

These metrics, along with others, help an organization to perform different types of performance testing.

How To Perform Performance Testing

The process can be very different because testers may use different metrics to conduct performance tests. A generic process might look something like this:

1. Identifying the testing environment - This includes any source load testing tools, as well as the test and production environments. Understanding the configuration of hardware, software, and networks can help identify performance issues as well as create better tests.
2. Identifying and defining acceptable performance criteria - The process of identifying and defining acceptable performance criteria should take into account performance goals and metric limitations. As an example, performance criteria can include response time, resource allocation, and throughput.
3. Plan your performance test- Test all use cases. Performance measurements should be the foundation for test cases and scripts.
4. Set up and use the testing environment. Arrange resources for the preparation of the test environment and then implement the design.
5. Test the code- Developers should monitor the code as they test it.
6. Analyze and Retest- Review the test results and share them with the team. Retest after any fine-tuning to determine if performance has increased or decreased.

Performance testing should be automated by organizations using the best testing tools. Do not change the testing environment between tests.

Performance Testing Types

Load and Stress testing are two primary forms of performance testing; there are also various other testing agile methodologies developers may employ in measuring performance.

Performance tests may be divided into various types, including:

1. Load testing- allows developers to gain a clear picture of how a system reacts under various loads, simulating concurrent users over an extended period. In load-testing, organizations simulate this number over time in order to measure response times and identify bottlenecks - this helps developers determine how many users their app or system can support before going live, load testing also serves to assess specific functions within an application - for instance shopping cart functionality on websites - as part of continuous integration processes which use automation tools like Jenkins to test codebase changes immediately.
2. Stress testing- entails subjecting a system to higher traffic loads than anticipated in order to gauge how it performs above its capacity limits. There are two forms of stress tests: soak testing and spike testing. Software teams can leverage stress tests to evaluate scalability of workloads. Stress tests involve testing hardware resources like hard drives, CPUs and memory for any potential signs that an application might become unstable; such resources might include hard disks. System strain may result in data exchange problems, memory shortages and data corruption. Stress tests are effective tools for measuring how quickly KPIs return to normal after an incident; stress tests should be run both prior to launch of the system as well as post launch. Chaos engineering, an advanced form of production-environment stress testing using specialist tools, is one example of stress testing. Organizations often conduct such assessments before major events - like Black Friday on an ecommerce application - are predicted. Tools designed specifically for load testing also come in handy for simulating anticipated loads.
3. The soak test- or endurance test, simulates an increase in end users over a period of time to determine a systems sustainability. During the testing, the engineer will monitor KPIs such as memory usage and check for any failures like memory shortages. Soak tests analyze response and throughput times after prolonged use to determine if they are in line with their initial status.
4. Spike Testing- Another type of stress test evaluates how well a system performs when subjected to big and unexpected increases in simulated users. Spike tests are used to determine whether a system is able to handle a sudden, dramatic workload increase repeatedly over a short time period. An IT team will often perform spike tests in the same way as stress tests prior to a major event where a system is likely to experience higher traffic than normal.
5. Scalability testing- measures performance by evaluating the softwares capability to increase or decrease performance attributes. Software Testers could, for example, perform a test of scalability based on user requests.
6. The capacity testing- is similar to the stress test in that the traffic load is based on users, but the amount of traffic tested differs. Capacity testing examines whether software applications or environments can handle the traffic they were designed to handle.
7. The volume testing- or flood test, measures how well a software program performs when faced with different amounts of data. Volume tests involve creating a file with a certain size of data, or even a large volume. Then, the application is tested to see how it performs.

Cloud Performance Testing

Developers can perform performance testing of applications using cloud services to maximize efficiency while still taking advantage of cost savings associated with cloud environments.

Initial assessments suggested that outsourcing performance testing to cloud computing would simplify and accelerate their testing processes, helping organizations scale faster while solving all their performance testing needs.

Unfortunately, due to lacking white box knowledge of their provider there were still issues when carrying out performance testing in the cloud.

Complacency can be one of the greatest hurdles to transitioning an on-premises application into the cloud, leading IT staff and developers to assume it will continue working correctly after moving it across.

Some IT staff may choose to minimize testing and quality assurance control in order to speed up rollout, testing accuracy could decrease as hardware from different vendors runs the application.

To maximise security and user pleasure, development and operations teams should map server ports and pathways, run load tests, evaluate scalability, look for security flaws, and consider UX design principles.

Cloud migrations may lead to serious communication challenges between applications. Cloud environments typically feature stricter security restrictions for internal communication; prior to moving applications onto the cloud, organizations should draw out an inventory map showing all servers, ports and communication pathways the app uses; performance monitoring could also prove invaluable.

Read More: How to develop an API test automation strategy

Performance Testing Challenges

Performance testing is a complex area.

1. Some tools only support web-based applications.
2. Some paid tools are expensive, while others may work better than free versions.
3. Some tools may be limited in compatibility.
4. Some tools can make it difficult to test complex applications.
5. Watch out for performance bottlenecks that occur in the following areas:
   1. CPU.
   2. Memory.
   3. Network utilization.
   4. Disk usage.
   5. OS limitations
6. Some other common performance issues include:
   1. Long loading times
   2. Long response times
   3. Hardware resources are insufficient
   4. Scalability is poor.

Performance Testing Tools

IT teams can choose from a wide range of performance testing tools depending on their needs and preferences. Performance testing tools include the following examples:

1. Akamai- CloudTest can be used to test mobile and web apps for their performance and functionality. It can also simulate millions of simultaneous users for load tests. The features of the tool include customizable dashboards, stress tests on AWS and Microsoft Azure clouds and more; a visual test creator; and a visual playback editing.
2. BlazeMeter- is a load and performance test tool that was acquired by Perforce Software. It supports real-time reporting, and is compatible with open source software and application programming interfaces. This service offers features like continuous testing of mobile and mainframe apps, real-time analytics and reporting, and real time reporting.
3. JMeter- is an Apache tool for performance testing. It can be used to generate load tests for web and application services. JMeter plug-ins offer flexibility for load manual testing, covering areas like graphs, timers and functions, as well as thread groups and thread groups. JMeter provides an integrated development environment (IDE) for recording tests for web browsers and web applications. It also offers a command line mode for testing Java-based operating systems.
4. Micro Focus LoadRunner- measures and tests the performance of applications when they are under load. LoadRunner is able to simulate thousands of users and record and analyze load tests. The software simulates user actions such as key clicks and mouse movements. LoadRunner is also available in versions for cloud-based use.
5. LoadStorm- is a cloud-based, scalable testing tool developed by CustomerCentric for mobile and web applications. It is designed for large applications that receive a lot of traffic every day. To perform real-time testing, it simulates multiple virtual users. The scalability check on mobile and web applications, and the reporting of performance data for load tests are important features.
6. We are a load and stress test tool for mobile and web applications. It was developed to help DevOps teams and continuous delivery. The program can be used by an IT team to monitor database, web and application servers. We simulate millions of users and can be used to test in-house, or through the cloud.

Automated Performance Testing

Many organizations are aiming for automation, which is a hot-button topic within the testing community. Its also a sort of holy grail when it comes time to understand performance over time.

Its not always clear where to begin, what tool to use, or how to achieve this goal. This is especially true if you have little experience with performance engineering.

This guide will outline the steps to automate performance testing.

Why Automate Performance Testing?

Lets begin by looking at why you might consider automating performance tests. We need to go back and review why we perform performance tests.

1. Avoid launch failures that can lead to missed opportunities and wasted investment, e.g. Your app or website crashing at a high-profile launch event.
2. You can avoid a bad user experience that will lead visitors and customers away from you and to the competition. This could result in revenue loss. You may lose customers that you have worked hard to win.
3. As code changes are deployed into your production system, and the end users are exposed to them, it is important to avoid performance regressions. This guide is primarily intended for this purpose.

The decision to automate testing should be clear now:

1. Performance testing should be done as early as possible in the development cycle, to give developers a feedback loop on performance issues.
2. Add performance regression checks to the Continuous Integration and Deliver (CI/CD).

Its true that not all performance tests can be automated. A/B tests are one type of test for which automation isnt necessary unless the goal is to compare performance between A and B in time.

Knowing Your Goals

Documenting your goals for performance testing automation projects is the single most essential factor to their success.

Consider what metrics and values matter most to you, your team, and the business when planning.

Starting your software

There are programming languages expressly for smart contract development, but you can also use general-purpose languages like C++ and Java.

Projecting off right by creating Service Level Agreements is always rewarding, providing an ideal chance for stakeholders and decision-makers to come together and talk about goals that need to be set for creating an efficient performance-based culture.

An initial baseline test can provide you with an effective starting point to set goals and measure progress toward them.

As this experiment involves only one or very few participants, VUs Youll know your system can handle it without issue while getting accurate numbers about response time and latency from it. Just ensure your baseline doesnt lead to unwanted errors that could compromise its functionality accuracy!

We have provided some guidance on human perception abilities that may be helpful when deciding what latency and reaction time to target:

The user can feel the system reacting instantly if it is less than 0.1 seconds. This means that there is no need for any special feedback other than to display the results.

Even though the user may notice the delay, a delay of 1.0 seconds is the maximum that will not disrupt the flow of the users thoughts.

Normal delays are less than or equal to 1.0 seconds, and no feedback is required. However, the user loses the sense of being able to operate directly on the data.

The user should be able to focus on the dialogue for a maximum of 10 seconds. Users will be tempted to do other things while they wait for the computer, so it is important to provide feedback on when the computer expects the task to be completed.

It is important to provide feedback during a delay, especially if there is a high likelihood of the response time being highly variable. Users will not know what they can expect.

You can specify the criteria for passing or failing by defining thresholds. Below is more information on this.

How to Automate Performance Testing

Learn how to automate performance tests using Perfecto and We. This example uses an ecommerce website. Continue reading to learn how you can automate performance tests.

Watch the webinar to learn how this is done.

1. Build And Launch Tests

Youll first need to download the latest version of your code from your versioning system and test it.

Youll then generate the test cases and trigger the tests over Perfecto. After the test case has passed, you can proceed to front-end performance testing.

2. Create A Junit Report

Its now time to use Jenkins to create a Junit Report.

This can be done by opening your IDE. Then, go to the Perfecto class.

Youll learn how to define a driver here:

1. Selenium Remote WebDriver.
2. Neotys Remote webdriver

Select the devices you want to test.

You can then go to the Perfecto dashboard and see the live streaming of the test.

3. Deploy Load Testing Infrastructure

Youll then deploy the We Load Generator to load tests.

We also use Jenkins.

Youll find two different types of users in the We test case:

1. Browser: The one who simply browses the website.
2. The buyer is the person who will put items in a shopping cart and make a purchase.

You can measure the user experience. You can view the results of the tests you have run in the We dashboard.

4. Run A Load Test

Now it is time to run a load-test in We using Perfecto as part of their integration, to assess user experience. While We provide updates about protocol changes, Perfecto provides feedback about its evaluation.

Get a Free Estimation or Talk to Our Business Manager!

The Conclusion Of The Article Is:

Software development teams can utilize automated performance testing as an invaluable way of early identification and response for performance issues in applications.

By employing automated performance tests into their development process, software teams can save both resources and time while optimizing applications to their fullest efficiency.

Automated tests enable software teams to focus on prioritizing improvement areas that make use of data analysis; additionally they test software performance under high loads/stress levels; helping businesses produce high-quality apps that exceed user expectations while remaining cost competitive.

References

1. 🔗 Google scholar
2. 🔗 Wikipedia
3. 🔗 NyTimes