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Performance Test vs Load Test vs Stress Test: Ultimate Guide

So you're building out that software project after months of planning, back-and-forth, and hard work. You're getting close to launch. Suddenly, you're faced with a question: how do I make sure my software runs up to standards?

The answer lies in software performance tests. Because first impressions last. And the last thing you want is to have worked so hard on a project, only to have it crash and burn due to performance issues.

At CyberMedics, we're going to go over three distinct types of software performance testing that you need to understand for your own software project: Load testing vs stress testing vs performance testing.

You will learn:

  • What they are

  • What metrics to look for

  • How to do these tests

  • Some tools to help you

Ready? Let's go.

The short answer: Stress testing vs Load testing vs Performance testing

The main difference between stress testing, load testing, and performance testing is the scope of what's being tested.

  • Stress testing ensures that services can handle peak loads. It pushes systems to their limits so you can test what happens when they are overloaded with requests or data.

  • Load testing simulates real-world scenarios. It tests the system’s response to a certain number of concurrent users accessing the software. Think: how many people can be using your software at the same time without breaking it?

  • Performance testing evaluates response times and system performance in real time. These tests measure individual components, such as memory usage or database queries, so you can fine-tune software and ensure it meets performance standards.

So, essentially: stress testing measures the maximum load capacity of your system, while load testing simulates how a real-world scenario would affect your system, and performance testing evaluates speed and usability.

Let’s dive deeper into each of these software performance tests.

What is stress testing?

You know when you walk into an elevator, and below the floor buttons, there's an engraved sign telling you the maximum capacity of that elevator? That's stress testing in a nutshell.

In the context of software performance testing, that means pushing your system as far as it can go to test the upper limits of what it can handle without crashing.

The purpose is to study how your application behaves under unexpected traffic spikes (e.g. maximum number of requests per second, how long user requests take to be processed before they're kicked off, etc.) and how it recovers when you back go to normal – is the response time the same as it was before the load spike?

This kind of performance testing looks for memory leaks, security issues, slowdowns, data corruption, and hardware bottlenecks.

Stress testing metrics

  • Average transaction response time – how long it takes on average to perform a transaction during each second of the scenario run.

  • Transactions per second – the number of times each transaction has passed, failed, or stopped during each second of the scenario run.

  • Total transactions per second – total number of transactions that passed, failed, and stopped during the scenario run.

  • Page views per second – how many pages were requested by the virtual users in each second of the scenario run.

  • Error rate – what percentage of errors happened during the test run?

  • Hits per second – the number of HTTP requests that were sent out by the virtual users in each second of the scenario run.

When to perform stress testing

  • When you're launching a new application, so you can measure the peak performance of your system with stress tests.

  • Whenever you make changes to the underlying architecture of your system (e.g. server upgrade, changes in software code, etc), a spike test is in order.

  • Near times of the year when you're expecting a surge in traffic (e.g, Black Friday, ticket-selling for a popular concert, election season, and whatever else is related to your industry)

How to conduct a software stress test

So now that you know what each of these tests involve, let's talk about how you can go ahead and conduct them. How do you do a stress test?

  1. Identify your testing environment: Find out what hardware, software, network configurations, and tools you need to stress test.

  2. What does a successful test look like? Define it. Determine which metrics are used to analyze the application's performance under stress. Indicate the stress test success criteria (maximum load required to fail, etc.)

  3. Set up your testing environment: Gather your testing tools and configure them to simulate a stress test. So that might look like creating custom scripts to generate traffic, or having users perform a set of tasks. You could also use tools like JMeter or WebLoad for this.

  4. Setup the test parameters: Decide how many concurrent users you want to simulate, what type of data should be used and which resources should be tested.

  5. Run the test: Monitor your application to ensure it's performing as expected. During the test, you should also be tracking performance metrics like response times, CPU load and memory usage.

  6. Analyze results: Once the testing is complete, review the data to identify any problem areas that need to be addressed or optimized.

Stress testing tools

  • Telerik Test Studio – A great test automation platform for web, desktop, and responsive web applications. Test Studio helps you tackle the biggest challenges of modern testing, whether it's improving test coverage across UI, RESTful APIs, and load scenarios, cutting bottlenecks with regression testing, or keeping the whole team informed throughout the entire cycle. It also has a handy playback feature that lets you record your test and use automated playback to craft your test and then run that same script to test multiple browsers.

  • WebLoad – An easy and flexible tool of choice for web applications, complex testing, and heavy user load. Users can do stress testing on cloud machines while being able to define automatic correlation, DOM-based playback, and JavaScript. The tool gives a clear picture of performance, bottlenecks, and errors that hinder response time.

  • SmartMeter – Here you can create a simple test that can be deployed in many test scenarios without coding. It's a mostly graphical user interface with no plugins and no proxy setup. It pulls in all the information about the test automatically. It generates graphs, comparison charts, statistical information, and trend evaluations for multiple tests based on auto-evaluated criteria.

  • LoadUI Pro – A wide variety of API formats are supported by LoadUI, including SOAP, REST, MQTT, and JMS. A user-friendly interface makes LoadUI simple to use for beginners and offers advanced coding features with minimal experience. For load testing, global or local distributors can be configured easily and existing test cases can be re-used from SoapUI NG Pro and SoapUI.

What is load testing?

Load testing is the practice of simulating real-world scenarios, and understanding how your system performs under these conditions. This is different from stress testing because a real-world scenario doesn't necessarily mean peak traffic – it could be any kind of situation that replicates the everyday usage of your application.

For example, if you're launching an e-commerce store, you'd want to measure things like how quickly customers are able to add items to their carts, select payment options, check out and go through the checkout process as well as test whether the application is capable of handling a high (again not necessarily max) number of concurrent users.

The idea behind this kind of software performance testing is to understand the limits of what your system can handle with minimal to acceptable performance degradation. It tends to involve running multiple tests with different user loads over a period of time, so you can truly understand how your application behaves under different circumstances.

That way, you can be sure that your software is ready for whatever the world throws at it – no matter what kind of load or stress it gets put under.

Load testing metrics

  • Average response time – In the average response time calculation, a round trip is determined from the beginning of every request and every reaction to that request, providing the information of how long it takes for your browser to respond back to your request.

  • Peak response time – The peak marks the longest interval of the cycle. Using the Peak Response Time, you can tell which resource is potentially problematic due to various anomalies within the web application.

  • Error rate – Under load, an application may give you some expected errors. Error rates are calculated as a percentage of problems compared to all requests, and they're key to measuring its efficiency, as it measures its failure to perform.

  • Concurrent users – A test's load is typically determined by the number of concurrent users – it measures how many virtual users are active at any given time. It's not the same as RPS (requests per second), though, because virtual users won't make consistent requests, whereas users can make a lot of requests.

  • Requests per second – RPS is the number of requests sent to the target server. A few examples of resources included are Flash/multimedia files, style sheets, images, JavaScript libraries, XML documents, HTML pages, and more.

  • Throughput – A throughput measures the speed of data transfer over a network (units of kilobytes per second). It measures the amount of data flowing between servers and the bandwidth consumed during the test.

When to perform load testing

  • When you need to measure the response times of your current application.

  • If you're launching new features and want to ensure that they can handle expected traffic levels. For teams that follow the waterfall project management method, you should load test each time you release a version. Even if you’re going agile, you should still load test every sprint.

  • To measure the impact of marketing campaigns on your website or application's user base.

How to conduct a load test

  1. The first step in conducting a load test is to identify what you're trying to achieve. Create a realistic performance goal that accounts for any changes or fluctuations in usage that might occur.

  2. Next, define your user scenarios. This will help you establish the environment your application needs to operate under. Make sure each of these scenarios includes a list of tasks and user journeys that are likely to be performed.

  3. Once you've got your performance goals and user scenarios in place, you can start designing the load tests themselves. Set up virtual users with realistic traffic patterns, and then run a series of tests with different levels of load on the system. This will provide insights into how the application behaves under various conditions.

  4. Finally, analyze the data you've collected and make any necessary changes in order to optimize your system's performance. This could include optimizing database queries, tweaking server configurations, or adding new hardware.

Load testing tools

Some tools will let you do both load and stress testing. Others are more specific, allowing you to focus on a single aspect of the process.

  • LoadRunner – performs load testing in web applications, ERP software, legacy system applications, as well as Web 2.0 technologies – so it's good for old-fashioned proprietary protocols. You can use the tool to detect bottlenecks before the application is implemented, so each component can be tested individually before it goes live. Furthermore, it forecasts expenses for up-scaling application capacity using highly advanced predictive features.

  • Gatling is an open-source code-based load testing tool perfect for Scala developers. Using only a few load generators, it allows you to simulate thousands of requests. You can also embed continuous integration processes using Jenkins. Test results are presented in a colorful, dynamic report – making it easy for you to analyze.

  • BlazeMeter is highly customizable and provides detailed analytics. There are lots of advanced features, like application performance monitoring (APM), real-time reporting, distributed testing, and integration with developer tools for continuous integration (CI). Plus, it integrates with many popular CI/CD tools like Jenkins, Bamboo, and TeamCity – making it easy to integrate load testing into your existing workflow.

What is performance testing?

Performance testing is a way to evaluate how well your software meets user expectations in terms of speed, usability, and reliability.

In software performance testing, you'd simulate different kinds of usage scenarios, then measure the results. You could test things like page load times, response times for web requests, availability during peak hours, and data transfer speeds. Basically, you'd try to find out how quickly and reliably your software performs under different conditions.

The goal is to ensure that your application or website is functioning as expected and that user experience remains consistent throughout. This helps you identify problem areas early on, so you can make changes before they become an issue for end-users.

Performance testing metrics

  • Time to first byte (TTFB) – Measures how responsive the web server is, from when the user makes a request to when the first byte of the page is received by the client.

  • Memory utilization – This measures the amount of RAM your application uses, which can be useful for tracking down memory leaks.

  • CPU utilization – how much processing power (percentage of CPU capacity) your software uses. It's important to ensure that your application is not hogging up too many resources, as this can slow down other processes.

  • Average load time – The average load time is the length of time it takes to complete a request, from start to finish. It should be as low as possible, since it affects the user experience.

  • Request rate – This is how many requests your application can handle per second. It measures how quickly your application can process requests, as well as how quickly it can send out responses.

  • Network latency – This is the amount of time it takes your application to process a request, from the moment it is received to the moment a response is sent back. It's important to ensure that your network latency stays as low as possible.

  • Bandwidth – This measures how much data your application can transfer at any given time.

When to use performance testing

  • You should always use performance testing when launching a new application or website.

  • Before and after making changes to your software architecture.

  • When you're expecting more traffic than usual, such as during an event or a marketing campaign.

How to run performance tests

  1. Identify the test bed – The first step is to decide where you'll be conducting the performance test. You should use a testing environment that closely resembles the production environment, as this will give you more accurate results.

  2. What are your performance metrics? – Decide on the metrics you'll be testing and what thresholds (success criteria) you want to set for each of them. We've provided you with a list of some key metrics for performance tests.

  3. Create a test plan – Flesh out your performance test scenarios and make sure to include all functionality that needs to be tested. This should include details about the tests to be conducted, such as the number of users, request rate, etc., as well as any assumptions or hypotheses that need to be made.

  4. Execute the test – Once everything is in place, it's time to execute your tests. Make sure to monitor the tests closely and take note of any anomalies or unexpected results.

  5. Analyze the results – Now that you've completed your performance test, analyze the results. Look for any areas where performance could be improved and identify any bottlenecks in your system.

Performance testing tools

  • Apache JMeter – A popular open-source tool used for performance testing from HP, offering various features such as load balancing and automated test scripts. You can use it to test Servlets, Perl scripts, and Java objects for functionality. It works under Unix and Windows OS, as long as you have JVM 1.4 or higher.

  • NeoLoad – Developers and testers can design automated tests, simulate user behavior, perform root cause analysis, and integrate the entire SDLC toolchain. You can reuse and share test assets and results between functional testing tools and analytics tools. To cover all enterprise-level testing needs, NeoLoad supports mobile, web, and packaged applications.

  • HeadSpin can help you monitor and optimize performance across the entire user journey. The data comes from thousands of devices, networks, and locations, so there's no ambiguity. By using advanced AI capabilities, users can find performance issues during testing before they affect users.

Make sure your software project is ready for the real world with CyberMedics

Load testing and stress testing are both important aspects of software development, but serve different purposes. Load testing is used to determine the maximum capacity of an application or system by simulating multiple users accessing it at once. Stress testing is used to identify how much load an application can take before it fails. And performance testing is used to measure the speed, scalability, and stability of an application or system.

By combining all three types of tests, you can ensure that your software project is ready for the real world.

When you build your software project with CyberMedics, we help you monitor and optimize software performance across the entire user journey. So make sure your project passes with flying colors and get in touch with us today.


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