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Performance Testing vs Load Testing: A Detailed Comparison

performance testing vs load testing

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:

Aspect	Performance Testing	Load Testing
Objective	Evaluate overall system performance under various conditions, including load, stress, and endurance.	Specifically assess how the system behaves under anticipated load conditions.
Focus Areas	Response time, throughput, resource utilization, stability.	Primarily response time, throughput, and system behavior under specific load levels.
Types	Includes load testing, stress testing, endurance testing, and more.	A specific type of performance testing, focusing on the expected load.
Primary Metrics	Response time, throughput, resource utilization.	Response time, transactions per second, concurrency.
Scope	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.
Tools	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.
User Behavior	Simulates various user behaviors and system interactions.	Primarily focused on mimicking the expected user load.
Scenarios	Covers a wide range, including different types of testing scenarios.	Emphasizes scenarios related to user load and concurrency.
Goal	Ensure the system meets performance criteria, identify bottlenecks, and optimize for efficiency.	Verify that the system can handle expected user loads without performance degradation.

Conclusion

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.

FAQs

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.

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.