Performance Testing vs Load Testing: A Detailed Comparison
Performance is an essential aspect of any successful system. When it comes to terminology, it is important to make clear distinction between performance testing and load testing. Put simply, performance testing encompasses a broader scope than load testing. Performance testing checks the system performance under normal and abnormal conditions, while load testing only focuses on normal conditions.
In this article, we will learn more about the differences between performance testing vs load testing.
What is Performance Testing?
Performance testing is a type of non-functional testing where testers evaluate the responsiveness and stability of a system under a wide variety of load conditions.
The end goal of performance testing is to ensure the system availability to support the business’s needs. Insights found during performance testing guide the optimization and maintenance process of the system’s infrastructure.
Example: You are running performance tests for an eCommerce website. You want to identify bottlenecks on the site to optimize its performance, which contributes to positive user experience and eventually the bottom line. Here are the test cases you want to run:
- Simulate the expected user load during low and normal usage hours to see the system’s response time
- Simulate the maximum expected user load during peak usage hours to see if the system can handle the peak load
- Apply a constant load on the system over an extended period to assess its stability
- Apply a sudden burst of traffic to see how well the system responds to rapid load changes
- Distribute virtual users across different geographical locations to assess global accessibility
- Test the system’s responsiveness when there is extensive file uploads
- Execute many complex workflows at the same time
- Introduce a server outage or a database connection issue to check if the system can recover from failure
What is Load Testing?
Load testing is a type of performance testing where testers evaluate the system under expected load conditions.
The end goal of load testing is to evaluate the system behavior under normal, expected usage. Its scope is more specific than performance testing. There is a high degree of realism when it comes to load testing, which is why it is a great option for performance metric measurements. Load testing also helps QA teams assess the scalability of the system.
What is Stress Testing?
Stress testing is a type of performance testing where testers evaluate the system under extreme or unfavorable conditions. The goal of stress testing is to identify the system’s breaking point. This provides insights into the system’s limitations and evaluates its behavior when subjected to stress beyond normal capacity.
Stress testing and load testing is both performance testing, yet stress testing explores the system “at its edge”, while load testing is only limited to the system’s normal capacity.
Performance Testing vs Load Testing: Key Differences
To better understand the differences between load testing and performance testing, you can have a look at this table:
Evaluate overall system performance under various conditions, including load, stress, and endurance.
Specifically assess how the system behaves under anticipated load conditions.
Response time, throughput, resource utilization, stability.
Primarily response time, throughput, and system behavior under specific load levels.
Includes load testing, stress testing, endurance testing, and more.
A specific type of performance testing, focusing on the expected load.
Response time, throughput, resource utilization.
Response time, transactions per second, concurrency.
Broader, covering various performance aspects.
More focused on the system's ability to handle a specific load.
Examples of Tests
Load testing, stress testing, scalability testing, endurance testing.
Peak load testing, spike testing, stress testing.
Apache JMeter, LoadRunner, Gatling, etc.
Read More: Top 15 Performance Testing Tools To Use
Similar tools, with a focus on load testing, such as Apache JMeter, LoadRunner, k6.
Timing of Tests
Throughout the development lifecycle, especially before major releases.
Often performed before major releases or when anticipating increased user activity.
Simulates various user behaviors and system interactions.
Primarily focused on mimicking the expected user load.
Covers a wide range, including different types of testing scenarios.
Emphasizes scenarios related to user load and concurrency.
Ensure the system meets performance criteria, identify bottlenecks, and optimize for efficiency.
Verify that the system can handle expected user loads without performance degradation.
In short, performance testing is a more comprehensive term than load testing. Performance testing evaluates the system at various load conditions from expected to unexpected usage, while load testing only focuses on normal usage.
1. When to do load and performance testing?
Load and performance testing should be conducted throughout the software development lifecycle, from the early stages of development to pre-production and post-production phases.
It is essential to perform these tests before major releases, during system upgrades, and whenever there are significant changes to the application or infrastructure. Additionally, load and performance testing are beneficial when anticipating increased user activity or when aiming to identify and address performance issues proactively.
Read More: Test Cases For API Testing (With Template)
2. Is load testing part of performance testing?
Yes, load testing is a subset of performance testing.
Performance testing can include:
- Load testing
- Stress testing
- Endurance testing
- Volume testing
- Scalability testing
- Concurrency testing
Load testing specifically focuses on evaluating the system's behavior under expected load conditions.
3. What is scalability testing?
Scalability testing is a type of performance testing that assesses how well a software application or system can scale up (or scale out) to handle an increasing amount of workload. The goal is to determine the system's ability to maintain or improve performance as the workload grows.