Endurance Testing - A Complete Guide in 2024

QASource Engineering Team
QASource Engineering Team | January 2, 2024
a-complete-guide-to-endurance-testing

When it comes to software testing, endurance testing is a vital and rigorous examination of an application's ability to handle heavy loads. This type of testing is critical in evaluating software reliability and performance. This guide will delve into the fundamentals of endurance testing, including essential monitoring procedures and testing methods, real-world examples, and recommended tools.

This comprehensive guide covers everything you need to know to create an endurance test strategy, including:

  • What is endurance testing in software testing?
  • What to monitor during endurance testing?
  • How trending technologies increase the need for Endurance Testing
  • Planning and Designing Endurance Tests
  • Identify endurance testing scenarios with real-time example situations
  • Benefits of Endurance Testing
  • Endurance Testing vs Load Testing: The Main Differences
  • Which UI automation testing tools are best for endurance testing
  • How QASource Can Help You

What is endurance testing in software testing?

Endurance testing in software testing is a non-functional test performed to evaluate the software applications’ behavior under high loads for an extended time. It is performed during the last stage of the performance run cycle and can sometimes last for as long as a year.

 

What To Monitor in Endurance Testing

Endurance tests are conducted to find unusual behavior in the system that occurs over extended periods of time when loads are high. Your system may run just fine during typical situations but may crumble in certain areas during high peak volumes, and that’s where endurance testing comes in.

Before we describe every endurance test with example scenarios, let’s look at what you should monitor when running endurance test cases:

  • Memory Leak: Is there any memory leakage in the application? This can often crash your application or operating system.
  • Normal Response Times: Prolonged use of your software can impact your system’s performance, leading to less efficient response times.
  • Successful Closure of Test Database: Your application is prone to system crashes if the connection fails to close successfully.
  • Closure of Connection Between System’s Layers: Different parts of the system’s module may get stalled if the connection between the layers is not closed properly.
 

How trending technologies increase the need for Endurance Testing

Trending technologies often introduce increased complexity, dynamic scalability, and new challenges in software development. Endurance testing becomes essential to validate the long-term performance, stability, and reliability of software systems built on these technologies, ensuring that they meet user expectations and function smoothly over extended periods. Below are some points that support this change in Endurance testing.

  • Complexity of Systems: Trending technologies such as microservices, containerization, and serverless computing introduce greater complexity into software systems. These technologies often involve multiple components or services working together. Endurance testing is essential to ensure these intricate systems maintain stability and reliability, especially when subjected to prolonged usage and varying loads.
  • Dynamic Scalability: Many trending technologies enable the dynamic scaling of software resources based on demand. Endurance testing is crucial to confirm that these auto-scaling mechanisms function correctly and efficiently, preventing issues like resource exhaustion or slowdowns during fluctuations in user traffic.
  • Real-time Data Processing: Technologies like IoT and edge computing involve real-time data processing, where systems continuously collect and process data from numerous sources. Endurance testing helps verify that software can sustain this constant data influx without performance degradation or bottlenecks over time.
  • Serverless Architectures: Serverless computing platforms automatically manage server resources and require thorough endurance testing. These platforms often charge based on usage, making it essential to ensure that functions or services are efficient and that they scale gracefully under sustained workloads.
  • Machine Learning and AI Integration: Applications integrating machine learning and artificial intelligence models must undergo endurance testing to assess how well these models perform over time. It helps identify issues like model drift or resource consumption as models continually learn and adapt.
  • Decentralized Technologies: Emerging blockchain and decentralized technologies, which involve distributed networks of nodes, require endurance testing to validate the long-term stability and reliability of blockchain-based applications and smart contracts.
  • User Experience Expectations: With user experience a paramount concern, trending technologies often aim to deliver seamless and responsive interfaces. Endurance testing ensures that applications maintain the desired user experience under sustained usage, preventing issues like slow page load times or unresponsiveness.
 

Planning and Designing Endurance Tests

  • Understanding Objectives: Determine what specific aspects of the software or system's performance you want to evaluate over an extended period.
  • Identifying User Scenarios: Define realistic user scenarios that mirror how the software is expected to be used in production. Consider factors like user interactions, data input, and navigation patterns.
  • Setup Test Environment: Set up a test environment that closely resembles the production environment.
  • Determining Load Levels and Test Duration: Decide on the desired load levels and test duration that your software or system should endure during testing. Consider factors like business cycles and peak usage periods.
  • Setting Monitoring Parameters: Establish performance metrics and key performance indicators (KPIs) you will monitor during the test. These metrics may include response times, CPU utilization, memory usage, etc.
  • Developing Test Scripts: Create test scripts or scenarios that automate the user interactions and load patterns defined earlier.
  • Defining Stop Criteria: Establish criteria for ending the test. This could be based on reaching a specific time duration, achieving certain performance thresholds, or identifying critical issues.
  • Resource Allocation: Allocate resources, such as servers, network bandwidth, and monitoring tools, according to the test plan and load levels.
  • Risk Assessment: Identify potential risks and challenges that may arise during the endurance test and develop mitigation strategies.
  • Review and Validation: Review the test plan with relevant team members and stakeholders to ensure it aligns with the project's goals and requirements.
 

Identify Endurance Testing Scenarios with Real-time Example Situations

Here’s an endurance test with an example situation many of us understand: memory leakage.

A memory leak occurs when weak programming code fails to release objects that are no longer used. Available memory wears down gradually over time, which can slow down your application and, worse, stop it entirely from working.

The goal of running an endurance test is to prevent such scenarios. In endurance testing, your QA team runs your system for an established amount of time under certain amounts of load to see if any leakage in memory occurs.

 

Benefits of Endurance Testing

There are many reasons why endurance testing should be included in your QA test strategy. When best practices are applied, your team can expect endurance testing to:

  • Find performance-related problems in order to maintain the software’s durability
  • Detect bugs related to memory leaks
  • Confirm to your development team that your application can perform as expected for long periods of time without maintenance
  • Prevent scenarios that would result in reputation damage or customer dissatisfaction
  • Reduce maintenance costs by addressing issues early before they evolve into severe system damage
  • Improve infrastructure by addressing time-related faults and bugs
  • Stability Validation:

    • Verifies the sustained stability and reliability of your software over prolonged usage
    • Verifies issues like memory leaks or performance degradation over prolonged usage
  • Realistic User Emulation:

    • By replicating genuine user interactions and continuous engagement, endurance testing delivers a precise depiction of software performance in a real-world scenario
  • Early Detection of Problems:

    • Endurance testing has the potential to identify and address potential issues before they impact users, reducing the likelihood of disruptive failures or reputation damage
 

Endurance Testing vs. Load Testing: The Main Differences

Put simply, an endurance test is a sub-type of load testing. Load testing, when leveraging the cloud, is meant to test your application by increasing the load on your system constantly and steadily until it reaches the threshold limit. Endurance testing takes this concept further to ensure your software behaves as expected when under heavy loads for extended periods of time.

Here’s a breakdown to help you remember the difference:

Endurance Testing Load Testing
Workloads during testing are natural, expected loads. Tests may or may not run under specified load limits.
Workload during testing is unexpected and varies over time to examine how your system handles the situation.
Tests for problems that grow over time and can lead to system crashes, including memory leaks and system degradations.
Tests for problems that occur in real time, including immediate system crashes and response time delays.
 

Endurance Testing Tools

The best way to run endurance test cases is with the support of endurance testing tools. Endurance testing already requires long periods of time for testing, so running these tests manually can take your QA team too much time to complete without a guarantee of test accuracy.

There are many things to consider when choosing a test automation tool for endurance testing. Our experts at QASource recommend checking out these testing tools for your QA strategy.

  • JMeter: This open-source software is freely available and platform-independent. Apache JMeter is a great performance testing tool that can run endurance testing with real-time example scenarios. This testing tool easily integrates with Selenium and can also perform unit testing.
  • LoadRunner: Considered a leader in performance testing, LoadRunner supports scripts from Selenium and JMeter by declaring an interface library. Like JMeter, this endurance test tool also excels at running integration and unit testing. LoadRunner may not be a free tool, but it does allow free trials to a certain number of users.
  • Appvance: Alongside endurance testing, Appvance can be used for security, performance, and functional testing. This AI-driven automation tool provides a virtual user dashboard and real-time analytics.
  • OpenSTA: Open System Testing Architecture - commonly known as OpenSTA - is written in C++ by CYRANO and supported by Microsoft Windows OS. This open-source tool can be used to perform scripted HTTP and HTTPS heavy load tests with performance measures.
  • WebLoad Professional: This endurance testing tool supports both Perfecto Mobile and Selenium. You can expect various pricing plans for this performance testing tool. Like NeoLoad, WebLoad Professional offers a free plan with limited users.
 

How QASource Can Help You

How Endurance Testing Elevates App's Excellence

Our team of performance testing experts boasts extensive experience in various types of performance testing, including Endurance testing. Given that Endurance testing necessitates continuous server-side monitoring, we incorporate our experience, skills, and knowledge to ensure the application's performance remains unaffected during extended testing periods.

 

Conclusion

Endurance testing is crucial to ensuring software reliability and performance. By subjecting software to heavy workloads and prolonged usage, we can uncover potential vulnerabilities, optimize system performance, and deliver high-performing applications that stand the test of time. Embrace endurance testing as a fundamental aspect of your software testing strategy to ensure the robustness and reliability of your applications.

Frequently Asked Questions (FAQs)

What is the primary objective of conducting endurance testing in software testing?

The primary goal of endurance testing in software testing is to ensure that an application can consistently handle its expected workload over an extended period without performance degradation or failures, thereby verifying its stability and reliability under sustained usage for extended periods.

What is the difference between load and endurance testing?

Load testing assesses an application's performance under expected loads for a short duration, while endurance testing evaluates how well it sustains a specific load over an extended period. Load testing focuses on immediate performance, while endurance testing examines long-term stability and reliability.

What are the key reasons for choosing endurance testing as a testing strategy?

Choosing endurance testing as a strategy for performance testing is to uncover long-term performance issues, verify system stability under sustained loads, and ensure reliable and consistent performance over extended durations.

What approach do we follow when conducting endurance testing?

When conducting endurance testing, we focus on applying sustained or near-production-level loads for extended durations to evaluate the system's stability, performance, and resource usage over extended durations.

Disclaimer

This publication is for informational purposes only, and nothing contained in it should be considered legal advice. We expressly disclaim any warranty or responsibility for damages arising out of this information and encourage you to consult with legal counsel regarding your specific needs. We do not undertake any duty to update previously posted materials.