Load Test Scenarios

Load Test Scenarios are specific, defined sequences of user actions designed to simulate realistic user behavior under expected and peak load conditions to evaluate system performance, stability, and scalability.

Detailed explanation

Load test scenarios are the backbone of any effective load testing strategy. They represent the real-world usage patterns of an application, allowing testers to simulate the actions of multiple concurrent users and observe how the system behaves under stress. A well-defined load test scenario accurately reflects user behavior and helps identify performance bottlenecks before they impact real users.

Designing Effective Load Test Scenarios

The process of creating load test scenarios involves several key steps:

  1. Identify Key Use Cases: Start by identifying the most critical and frequently used functionalities of the application. These are the areas where performance is most crucial. Examples include user login, product search, adding items to a cart, and completing a checkout process.

  2. Define User Personas: Create user personas that represent different types of users with varying behaviors. For example, a persona could be a "casual browser" who spends a lot of time browsing but makes few purchases, or a "power user" who frequently uses advanced features.

  3. Model User Behavior: Based on the user personas, model the actions they would take within the application. This includes the sequence of steps, the frequency of actions, and the time spent on each step. Consider factors like think time (the time a user spends reading or thinking before taking an action) and pacing (the rate at which users perform actions).

  4. Determine Load Levels: Define the number of concurrent users to simulate for each scenario. This should include both expected load (the typical number of users) and peak load (the maximum number of users expected during busy periods). Also, consider ramp-up and ramp-down periods to gradually increase and decrease the load.

  5. Script the Scenarios: Translate the defined user behavior into scripts that can be executed by load testing tools. These scripts typically involve simulating HTTP requests, database queries, and other interactions with the application.

Practical Implementation with JMeter

JMeter is a popular open-source load testing tool that can be used to create and execute load test scenarios. Here's an example of how to create a simple load test scenario in JMeter:

  1. Add a Thread Group: A thread group represents a set of users executing the same scenario. Configure the number of threads (users), ramp-up period (the time it takes to start all threads), and loop count (the number of times each thread executes the scenario).

  2. Add HTTP Request Samplers: HTTP request samplers simulate HTTP requests to the application. Configure the server name, path, method (GET, POST, etc.), and any request parameters. For example, to simulate a user logging in, you would add an HTTP request sampler to send a POST request to the login endpoint with the username and password.

  3. Add Timers: Timers introduce delays between requests to simulate think time. The Constant Timer is a simple option that adds a fixed delay. The Gaussian Random Timer adds a random delay based on a Gaussian distribution, which is more realistic.

  4. Add Listeners: Listeners collect and display the results of the test. The View Results Tree listener shows the details of each request, while the Summary Report listener provides an overview of the test results, including response times, throughput, and error rates.

Here's a snippet of a JMeter test plan (JMX file) simulating a user accessing a website:

<HTTPSamplerProxy guiclass="HttpTestSampleGui" testclass="HTTPSamplerProxy" testname="Home Page" enabled="true">
  <elementProp name="HTTPsampler.Arguments" elementType="Arguments" guiclass="HTTPArgumentsPanel" testclass="Arguments" enabled="true">
    <collectionProp name="Arguments.arguments"/>
  </elementProp>
  <stringProp name="HTTPSampler.domain">example.com</stringProp>
  <stringProp name="HTTPSampler.port"></stringProp>
  <stringProp name="HTTPSampler.protocol">https</stringProp>
  <stringProp name="HTTPSampler.contentEncoding"></stringProp>
  <stringProp name="HTTPSampler.path">/</stringProp>
  <stringProp name="HTTPSampler.method">GET</stringProp>
  <boolProp name="HTTPSampler.follow_redirects">true</boolProp>
  <boolProp name="HTTPSampler.auto_redirects">false</boolProp>
  <boolProp name="HTTPSampler.use_keepalive">true</boolProp>
  <boolProp name="HTTPSampler.DO_MULTIPART_POST">false</boolProp>
  <stringProp name="HTTPSampler.embedded_url_re"></stringProp>
  <stringProp name="HTTPSampler.connect_timeout"></stringProp>
  <stringProp name="HTTPSampler.response_timeout"></stringProp>
</HTTPSamplerProxy>
<ConstantTimer guiclass="ConstantTimerGui" testclass="ConstantTimer" testname="Constant Timer" enabled="true">
  <stringProp name="ConstantTimer.delay">2000</stringProp>
</ConstantTimer>

This example shows an HTTP Sampler configured to retrieve the home page of "example.com" and a Constant Timer adding a 2-second delay.

Best Practices

  • Realistic Data: Use realistic data in your load test scenarios. Avoid using the same data for all users, as this can lead to caching effects and inaccurate results. Use CSV Data Set Config in JMeter to read data from a CSV file.
  • Correlation: Handle dynamic values, such as session IDs and CSRF tokens, by using regular expression extractors to extract these values from the server's responses and use them in subsequent requests.
  • Monitoring: Monitor server-side metrics, such as CPU usage, memory usage, and database performance, during the load test. This helps identify bottlenecks and understand the root cause of performance issues. Tools like Prometheus and Grafana can be integrated for real-time monitoring.
  • Incremental Load: Gradually increase the load during the test to identify the point at which the system starts to degrade. This helps determine the system's capacity and identify areas that need optimization.
  • Scenario Variety: Create a variety of load test scenarios to cover different aspects of the application and simulate different user behaviors.
  • Regular Execution: Run load tests regularly as part of the development process to identify performance regressions early on. Integrate load testing into your CI/CD pipeline.

Common Tools

Besides JMeter, other popular load testing tools include:

  • Gatling: A high-performance load testing tool written in Scala.
  • LoadRunner: A commercial load testing tool with a wide range of features.
  • k6: A modern load testing tool written in Go.
  • Locust: A Python-based load testing tool that allows you to write test scenarios in Python code.

By carefully designing and executing load test scenarios, you can ensure that your application can handle the expected load and provide a good user experience.

Further reading

Related Terms

A/B Testing

Acceptance Testing

Accessibility Tester