Stress testing takes an important place in software testing. In this article, we will discuss what stress testing is, why it is important, its goals, types, and metrics. We will also explain the difference between stress testing, load testing, and performance testing, and provide insights on how to effectively perform stress testing to achieve optimal results.
Table of contents:
- What is stress testing?
- Why is it important to stress test software?
- Goals of stress testing
- How stress testing differs from load and performance testing
- Types of stress testing
- How to perform stress testing
- Stress testing metrics to monitor
What is stress testing
Stress testing is an extremely important type of software testing that checks the stability and reliability of a system under increased or extreme load conditions. Stress testing is especially necessary for critical software but is also applied in other cases.
During stress testing, special attention is paid to reliability, availability, and error handling under high load, rather than correct behavior in normal situations. In the course of stress testing, various scenarios are simulated in order to push the software beyond its normal operating capabilities: a sudden increase in the number of users, data volumes, traffic, etc. In this way, testers identify bottlenecks, memory leaks, performance degradation, and potential failures that may occur under stressful conditions.
Ultimately, stress testing plays an important role in ensuring that software systems can meet the demands of real-world use, providing end users with reliable and high-performance applications. Stress testing is an important part of performance testing and is also known as endurance testing, fatigue testing, or torture testing.
Why is it important to stress test software?
Typically, most systems are designed to operate in normal mode. Even if developers optimize their code and pay attention to its performance, taking into account high load, their calculations are often purely theoretical or approximate. Regular tests do not reveal all errors and defects in the system's operation.
Imagine a scenario where thousands of fans are simultaneously trying to buy concert tickets the moment they go on sale. The surge of traffic can overwhelm the ticketing system, causing it to slow down or crash, leading to a frustrating experience for users. Or consider an ecommerce platform during a major sales event like Cyber Monday. The sudden influx of millions of shoppers can strain the system, resulting in slow load times, failed transactions, and inventory management issues.
Stress testing helps identify such problems and weaknesses in the system before it is deployed in a real environment. By simulating an influx of customers, developers and testers can check how the system will perform under extreme loads and make the necessary changes or improvements. Identifying and resolving these issues at an early stage allows organizations to avoid costly downtime and expenses associated with urgent troubleshooting caused by system failure.
In addition, stress testing ensures system reliability, which is especially relevant for a company's critical systems such as servers, databases, and networks. In turn, reliability means, among other things, constant availability and high efficiency of the system, in other words — meeting customer expectations. This increases their level of satisfaction with your product.
Goals of stress testing
The main goal of stress testing is to ensure that the software system is capable of withstanding the loads it may encounter. If the system cannot cope, stress testing allows you to identify ways to solve the problems that have been discovered. With stress testing, you can:
- Determine the system's limitations, i.e., identify performance threshold values.
- Assess the system's stability: understand how the software behaves under extreme conditions, allowing you to detect potential failures, memory leaks, or performance degradation.
- Identify areas for improving and optimizing system performance.
Stress testing helps you uncover various issues such as corrupted data, security weaknesses, or hardware that cannot withstand peak loads.
How stress testing differs from load and performance testing
In addition to stress testing, there are other types of testing that check the reliability and functionality of software under increased load conditions. These are performance testing and load testing. However, there are differences between them.
Stress testing is usually performed as a one-time event and simulates extreme conditions. On the other hand, performance testing and load testing are usually performed as part of the regular testing process. Performance testing measures the responsiveness, stability, and speed of a program under typical operating conditions, while load testing evaluates the efficiency of an application under anticipated and expected user load.
Suppose you have a popular online application for purchasing tickets to events. Let's look at how different types of testing would be performed for this application.
Stress Testing is designed to evaluate the application's performance under extreme conditions, beyond its normal operational capacity. For example, let's imagine a scenario where the application is subjected to an unexpected and massive surge in traffic. This could happen when 1 million users simultaneously try to purchase tickets for a highly anticipated event. The objective of stress testing is to determine the application's breaking point and identify how it handles high-stress conditions, such as whether it crashes, slows down significantly, or manages to stay operational.
Performance Testing assesses the application's responsiveness, stability, and speed under typical, everyday usage conditions. For instance, suppose the application regularly handles around 10,000 users purchasing tickets for various events throughout the day. Performance testing would measure how quickly pages load, how fast ticket searches are executed, how promptly payment transactions are processed, and how stable the application remains under this normal user flow. The goal is to ensure that the application performs well and meets user expectations for speed and reliability during standard operations.
Load Testing evaluates the application's performance under expected peak or heavy load conditions. For example, consider a scenario where it is anticipated that approximately 100,000 users will try to purchase tickets simultaneously for a highly anticipated football match or a major concert in a large stadium with a seating capacity of around 100,000. Load testing examines whether the system can handle this volume of concurrent users without significant slowdowns or errors. It ensures that critical functions such as searching for events, selecting seats, and processing payments remain operational and efficient under peak load conditions.
Types of stress testing
There are several types of stress tests.
Distributed stress testing
In distributed client-server systems, stress testing is performed on all of the server's clients. The role of the stress server is to distribute a set of stress tests among all stress clients and track the clients' status. After the client accesses the server, the server adds the client's name and begins sending test data. Meanwhile, the client machines send a signal or heartbeat indicating that they are connected to the server. If the server does not receive any signals from the client machine, it needs to be investigated for debugging.
Application stress testing
This type of stress testing is aimed at identifying defects related to data locking, network issues, and application performance bottlenecks. Its goal is to identify vulnerabilities affecting the functionality and performance of the application.
Transaction stress testing
This includes testing one or more transactions between multiple applications. Its goal is to fine-tune and optimize the system by analyzing the performance, scalability, and reliability of transactions in the application ecosystem.
System stress testing
System stress tests are performed on multiple systems running on one server and aim to identify defects when data processing by one application can interfere with or block the operation of another application. This testing checks the system's ability to handle parallel processes and prevent data conflicts.
Exploratory stress testing
This type of stress testing involves testing the system with unusual parameters or conditions that are unlikely to occur in the real world. Its goal is to identify defects and vulnerabilities in unexpected scenarios, such as a large number of users logging into the system simultaneously or running a virus scanner on all machines at the same time.
Spike testing
Spike testing is also a type of stress testing, where the application is repeatedly loaded with large loads (within the maximum allowable limits), and sometimes the load on the application is increased beyond the maximum allowable limit for a short time.
How to perform stress testing
Stress testing should be conducted at certain stages of the software development lifecycle to ensure that applications can handle the demands of real-world scenarios. First and foremost, this includes:
- The production preparation stage. By subjecting the system to extreme loads, potential issues can be identified and resolved early, preventing unexpected failures and performance degradation.
- After major updates. Stress testing helps check if any unforeseen issues have arisen as a result of the changes that could affect the system's performance and stability.
- During scaling. Stress testing is necessary to assess the system's ability to handle increased user load, data volumes, or transactions.
- When transitioning to new infrastructure. For example, when changing servers, databases, or network configurations, stress testing assesses the software's performance in the new environment and identifies compatibility issues or performance bottlenecks.
- Specific situations. For instance, when ecommerce sites or online stores announce a sale during a festival, which may cause a spike in traffic, or when a leading newspaper publishes a sensational article that could lead to an unexpected influx of traffic.
Planning
Clearly define the goals and objectives of stress testing. Identify specific performance metrics, non-functional requirements, and threshold values that need to be measured. Define stress scenarios and workload models that need to be simulated, and specify the target environment and infrastructure for stress testing.
Failure to plan and clearly define the goals, scope, and test scenarios for stress testing can lead to incomplete or ineffective testing.
Creating automation scenarios
Develop or configure automation scenarios to model the desired stress scenarios. This includes developing test cases representing various stress conditions and load levels, as well as configuring test data and the test environment for stress testing. Ensure that the automation scenarios accurately reflect the expected stress scenarios.
It is important that the test data accurately reflects the expected volumes, diversity, and complexity of data to ensure an adequate assessment of the system's performance and identify potential issues. Create a test environment that exactly replicates the production environment, including hardware and software, network configurations, and data volumes. This will help ensure accurate modeling of real-world conditions and more reliable performance assessment.
Executing test scenarios
Execute the scenarios, tracking and measuring the system's performance metrics throughout the process. After each test, create logs, reports, and data for further analysis.
Keep in mind that using an inadequate test environment that does not accurately copy the production environment can lead to erroneous or inaccurate results. The use of unrealistic or inadequate workloads during stress testing may lead to inaccurate performance assessments. The inability to reproduce real scenarios, user behavior, or data volumes may result in missing performance issues that may arise in real-world conditions.
Analyzing results
Analyze the performance metrics and measurements collected during stress testing. Identify all bottlenecks, failures, and anomalies in the system's operation. Compare the observed performance with the specified metrics and thresholds, and analyze the root causes of performance issues to identify areas for improvement.
Neglecting proper monitoring and analysis of system metrics during stress testing can limit the effectiveness of the testing process. Without comprehensive data collection and analysis, it becomes difficult to identify performance bottlenecks, resource constraints, or areas requiring optimization.
Prioritizing fixes and optimizations
Based on the identified performance issues, prioritize fixes and optimizations that will have the greatest impact. Eliminate critical bottlenecks and performance constraints to ensure immediate improvements and more stable system operation.
Repetition and iteration
Stress testing can be repeated to verify the effectiveness of the optimizations. Treat stress testing as an iterative process. Analyze the test results, identify areas that need improvement, and refine the test scenarios and workloads during the testing process. Constantly repeat the stress testing process to confirm the effectiveness of optimizations and ensure consistent system performance.
Stress testing metrics to monitor
Developers use various metrics to evaluate system performance during stress testing. These metrics help assess whether the system meets expected standards and identify potential bottlenecks or areas for improvement.
Scalability and performance metrics:
- Number of pages requested by the application per second
- Throughput - the amount of data in responses per second
- Number of concurrent users or sessions
- CPU and memory utilization
- Database query response times
Application response metrics:
- Hit Time - the average time required to retrieve an image or page
- Page viewing time - the time required to retrieve all information from the page
- Server response times
- Application-specific business transaction response times
Failure metrics:
- Number of failed connections rejected by the client
- Number of failed rounds or requests
- Number of failed system attempts: e.g., broken links
- Error rates and exception counts
Monitoring and analyzing these metrics during stress testing helps developers identify performance bottlenecks, resource constraints, and potential failure points. By comparing the observed metrics against established thresholds and benchmarks, developers can pinpoint areas requiring optimization and ensure the system meets the desired performance and scalability targets under extreme load conditions.
Stress testing helps you prepare software for extreme conditions
Stress testing in software engineering is crucial for ensuring the reliability, stability, and performance of software systems. By subjecting the system to extreme conditions, stress testing exposes its limits, identifies bottlenecks, and pinpoints potential failure points. This rigorous testing process provides developers with invaluable insights into how the software behaves under increased loads, enabling them to optimize performance, enhance scalability, and improve the overall user experience.
Developers must prioritize stress testing to uncover critical performance issues that could otherwise lead to system failures, crashes, or dissatisfied users. By proactively conducting stress testing, developers can mitigate these risks before deployment, ensuring their software can robustly handle unforeseen spikes in traffic, data volumes, or resource demands. Furthermore, stress testing allows developers to fine-tune their applications, optimize system efficiency, and guarantee uninterrupted operation for users.
In essence, stress testing serves as a vital tool in the software development lifecycle, ensuring that applications not only meet but exceed performance expectations in real-world scenarios. By investing in thorough stress testing practices, developers uphold the reliability and resilience of their software, ultimately enhancing user satisfaction and trust.
