Concurrency Testing: Benefits, How-To, and Tools To use

Concurrency testing in software testing evaluates how the application under tests handles multiple concurrent users. With concurrency testing, testers and developers ensure applications and systems perform as expected under loads. 

In this blog post, we cover concurrency testing end-to-end, including why you should run this type of testing, pitfalls to avoid, a step-by-step tutorial, and recommended tools.

What is Concurrency Testing?

Concurrency testing tests two users on the same server. It assesses how well a software application or website can handle multiple concurrent users or processes using it simultaneously while performing the same actions. It is also known as multi-user testing.

Concurrency testing helps identify bottlenecks, performance issues, like locking and deadlocking, and other bugs, like single-threaded code. This ensures the application remains stable, responsive, and doesn't crash or produce incorrect results. To perform concurrency testing, simulate multiple users or processes interacting with the software the same way at the same time and monitor behavior under this load.

Benefits of Concurrency Testing

Concurrency testing offers several valuable benefits to testers and developers:

Enhanced Reliability

Testing how the software handles concurrent requests and interactions helps ensure that the software doesn't crash or slow down when subjected to heavy loads. This increases the reliability and stability of the application, resulting in faster response times and a smoother user experience.

Optimized Resource Usage

Understanding how the software uses system resources under concurrent conditions allows for more efficient resource allocation. This can lead to reduced infrastructure costs and better efficiency.

Improved Scalability

By determining the system's capacity to handle concurrent users or processes, concurrency testing provides insights into scalability abilities, limitations, and requirements. Developers can then scale the infrastructure or optimize the code to accommodate expected increased loads.

Resource Savings

When running concurrency testing early in the development process (shifting left) testers and developers can find and fix issues before pushing to production. This is more cost-effective than dealing with them after the software is deployed, since it reduces the risk of expensive downtime and the hassle of emergency fixes.

Concurrency Testing Drawbacks

While concurrency testing offers multiple benefits, it's also important to be aware of its potential drawbacks and challenges:

• Complexity -  Concurrency testing requires simulating multiple concurrent users or processes interacting with the software. This can make test case design and execution more complex and challenging, since it requires synchronization, overcoming time-related issues, and more. Therefore, it’s important to choose the right platform that will simplify the process.
• Resource Intensive - Running concurrency tests often requires a significant amount of computational resources, especially when simulating a large number of users. This can lead to higher infrastructure costs and longer test execution times. Some solutions, like BlazeMeter, run these tests in the cloud, relieving you of these costs.

How to Perform Concurrency Testing

Performing concurrency testing is a multi-step process that requires a systematic approach. Here's a step-by-step guide on how to perform concurrency testing:

1. Identify Test Scenarios

Determine the scenarios you want to test. Consider factors like the areas in your application that should be tested, the number of expected concurrent users, the types of interactions they perform, and the data they access or modify. These scenarios should reflect current and expected real-world usage patterns.

2. Choose Your Concurrency Testing Tool

Select the appropriate tools or frameworks for conducting concurrency testing. There are various tools available, such as JMeter, Gatling, and BlazeMeter (see next section), depending on your requirements and technology stack.

3. Create Test Scripts

Write test scripts that define the concurrent user interactions. These scripts should mimic the actions of real users, such as making HTTP requests, filling out forms (you might need test data for this), or accessing database records. You will need to specify parameters like the number of concurrent users, ramp-up time, and test duration.

4. Determine KPIs

Define success criteria and performance thresholds, such as response time, the baseline or error rates, which will determine whether the test passes or fails.

5. Execute Tests

Run the concurrency tests according to your defined scenarios and parameters.

6. Monitor and Analyze Results

Monitor the performance of the application closely during the test. Record metrics related to response times, CPU and memory usage, database performance, and any error or exception messages. Then, review the test results to identify performance bottlenecks or other concurrency-related issues. Compare the results against your predefined success criteria to determine whether the application meets performance standards.

7. Iterate and Optimize

If issues are identified, work with developers to address them. This may involve code optimizations, database tuning, or changes to the application's architecture. Re-run the tests iteratively to verify that the issues have been resolved and that performance has improved.

8. Automate Testing

Automate your concurrency tests by running them regularly as part of your CI/CD pipelines. Automation ensures that tests are run consistently and allows for quick feedback on code changes.

Concurrency Testing Tools

There are several concurrency testing tools available that can assist in simulating and assessing how your application handles concurrent usage. These tools vary in terms of features, capabilities, and compatibility with different technologies. Here are some popular and effective concurrency testing tools:

• Apache JMeter - A widely used open-source tool for performance testing and concurrency testing. JMeter allows creating test plans to simulate multiple users and their interactions with web applications, databases, and more. JMeter also has a vibrant community and there are plenty of online tutorials explaining how to use it.
• Gatling - An open-source load testing tool that uses a domain-specific language for test scripting and allows simulating multiple users.
• Locust - An open-source, Python-based tool for load and performance testing. It allows you to write test scenarios in Python code and provides support for distributing load across multiple machines.
• Taurus - An open-source automation-friendly framework that can work with various testing tools, including JMeter, Gatling, and others. It simplifies the process of creating and running concurrency tests.
• BlazeMeter - A comprehensive load testing tool that includes features for concurrency testing and continuous testing. BlazeMeter supports all open-source concurrency testing tools while providing advanced features like extended concurrency testing through scalability in the cloud, advanced monitoring, test data, and more. BlazeMeter can be used by testers and developers of any level of technological expertise. Finally, since BlazeMeter is a commercial tool (with a free tier) it has wide support and extensive documentation.

Bottom Line

Concurrency testing provides you with confidence that your application can handle all the users that will visit your website or application while providing them with a good user experience. Therefore, concurrency testing accelerates time to market while improving code quality. 

When choosing a concurrency testing tool, consider factors such as your project's technology stack, the level of expertise within your team, and the specific requirements of your testing scenarios. Additionally, evaluate the tool's documentation, community support, and scalability to ensure it aligns with your testing requirements. 

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