What is Performance Testing & Why it’s Important

What is Performance Testing?

Software performance testing is a type of non-functional testing that focuses on determining how a system performs in terms of responsiveness and stability under a particular workload. It's not just about finding defects in the code — rather, it's about identifying the performance bottlenecks and ensuring the application meets the performance criteria and provides a positive user experience.

Performance Testing vs. Performance Engineering

Similar to the relationship between quality assurance and quality engineering, performance engineering is a broader and more proactive planning approach to ensuring software performance. Performance engineering focuses on preventing issues before they occur (through practices like performance-friendly design, continuous monitoring, and feedback loops), while performance testing is used to detect existing issues later in the development process.

Why is Performance Testing Important?

Performance testing is crucial because it directly impacts the user's satisfaction and the system's credibility. Software performance testing is critical for several reasons:

Why performance testing is crucial block diagram

User Satisfaction & Experience

Performance directly impacts how users perceive the software. Slow or unresponsive applications often lead to frustration and dissatisfaction, driving users away. Making sure that the software performs well under various conditions is crucial for maintaining a positive user experience and brand reputation for high-quality products that meet (or surpass) expectations.

Scalability

Performance testing helps to determine if the software can handle the expected number of users and transactions — while maintaining acceptable performance levels. This is essential for planning scaling strategies and ensuring that the software can grow with the user base or data volume without degradation in performance. Scalability is also important for the longevity of a product, verifying that ongoing use at expected levels doesn’t diminish the performance or outpace necessary resources to run the software.

Reliability & Stability

This process also identifies and rectifies stability issues under different load conditions. As a result, the software remains reliable and stable, even when usage spikes or during unforeseen events (such as launches or major updates). Similar to user experience, this is a crucial part of maintaining a strong reputation.

Optimization

Identifying bottlenecks and areas for improvement helps in optimizing code, databases, and infrastructure can be beneficial for the quality of the final product, code management, and more. This leads to more efficient resource utilization, which can reduce operational costs and improve response times for a better user experience.

Quality Assurance

Performance testing is a part of overall quality assurance to verify that the software not only functions correctly but also delivers performance metrics that meet or exceed the requirements and expectations. This type of testing should be part of any modern QA practices to find any potential opportunities for improvement.

Competitive Edge

In a competitive market, the performance of your products can be a significant differentiator — users will often choose the software that is faster and more responsive. Using performance testing to establish a good user experience can give you a major edge over competitors (and can even be used in areas like marketing and sales).

Risk Mitigation

This helps in identifying and mitigating potential risks related to performance before the software is deployed. Doing so can help prevent unexpected failures, downtime, and delays that might otherwise occur in production. Failure to mitigate these risks may lead to loss of revenue, reputation, and customers.

Regulatory & Compliance

Certain applications, especially in industries like finance, healthcare, and telecommunications, need to meet specific performance standards (particularly around security and availability) as part of regulatory requirements. Performance testing catches these issues before launch to minimize the chances of non-compliance.

Helps Optimize Costs

By understanding and improving the performance of the application, it helps avoid over-provisioning resources, saving on infrastructure costs. This means a more informed and efficient allocation of your team’s time and budget for more successful projects and post-launch support.

Performance Testing Process

When implementing performance testing into your development, it’s important to follow key steps in order to maximize the value of your testing.

1. Identify Test Environment

To begin, it’s critical to identify and define the purpose of this testing. From there, look at available resources — what software, hardware, tools, and more are available for this? What will you need to set up a test environment that aligns with the testing goals? Servers, databases, load balances, network characteristics, and software versions are all important to consider. The end result of this step should be a strong understanding of the environment that simulates real-world use (or excessive use depending on the test).

2. Select Acceptance Criteria

From there, the team should collaborate with stakeholders to choose the most relevant metrics and benchmarks for the testing goal. This selection and criteria can also be based on industry standards, such as expected response time. It should also be clear and measurable, for example “page load time less than 3 seconds with 1,000 concurrent users.”

3. Design Tests

Now that tests and criteria have been identified, a more technical look at test design can begin. This includes identifying specific scenarios, test types, and actions that will need to be considered so the development of these tests can begin. By the end of this process, you should have a test plan with various test types, individual test cases, anticipated load levels, and key metrics or objectives.

4. Configure Test Environment

With all of that information organized, the creation and configuration of testing environments can begin. This means installing all necessary software, preparing the test data, allocating hardware resources, and setting up server needs. Any additional security settings, network permissions, etc. should also be established.

5. Develop Test Designs

Before actually running the tests, they’ll need to be developed. This means the specific test scripts and configurations that are based on the design stage from earlier. While this can be done manually, it’s often easier to automate the creation of various test cases (including edge cases) to bolster test coverage. These should accurately simulate user actions and expected load. By the end of this creation step, the test environment and tests should be accurate to real-world interactions.

6. Execute Tests

It’s finally time to run the designed tests in your test environment — begin with baseline tests to get a control data group. From here, start gradually increasing the load levels and observe the data as this ramps up. Make note of any slowdowns, errors, or crashes to make the analysis step (next) easier.

7. Analyze Results

Once all of the performance testing is complete and data is available, go through and identify any areas of concern (bottlenecks, crashes, unanticipated errors, etc.). This should be done as a group so multiple perspectives can contribute to the analysis. Compare the results to your benchmarks from Step 2 and check whether acceptable thresholds were surpassed. This evaluation should also include an explanation of whether any data points were anomalous or if any tests didn’t result in the expected data to improve future testing.

Primary Attributes of Performance Testing

The major aspects of performance testing analysis include:

Speed: How fast does the application respond to specific events or requests? This could mean how quickly a web page loads or how fast a transaction is processed.

Scalability: How well does the application handle increasing loads? Can it accommodate a growing number of users or transactions without significant performance degradation?

Stability: Is the application stable under varying loads, or does it crash or behave unpredictably?

Reliability: Can the system consistently perform well over an extended period?

Types of Performance Testing

Performance testing typically involves several different types of tests:

Load Testing: This involves simulating real-life loads on the software to understand how it behaves under normal and anticipated peak conditions.

Stress Testing: This involves putting the system under extreme conditions (well beyond peak load) to see where it breaks. This helps identify the system's "breaking point" or "failure point."

Endurance Testing (Soak Testing): This tests the system's ability to handle a continuous expected load over a long period. This can help identify issues like memory leaks.

Spike Testing: This tests the system's reaction to sudden large spikes in the load generated by users.

Volume Testing: This tests the system's ability to handle a large volume of data. This can include database testing in terms of size and complexity.

Configuration Testing: This involves testing the application with different configurations to determine the optimal settings.

What Metrics Matter?

When creating benchmarks, some measurements can be more useful than others. Some of the most popular and useful metrics for performance testing include:

Throughput: Number of requests or transactions processed by the application per unit of time.

Active Threads: Number of virtual users or threads actively interacting with the system at any given time during testing.

Memory Usage: Amount of memory consumed by the application during testing.

Availability: Percentage of time the application is accessible and functional during testing.

Response Time: Time it takes for the application to respond to a user request.

Request Rate: Frequency at which requests are sent to the system, typically measured as requests per second.

Network Bandwidth: Rate of data transfer across the network during testing.

Average Latency: Average time it takes for a request to travel from the user to the server and back.

Average Load Time: Average time required to load a page or complete a user action.

Peak Response Time: Longest time taken for a request to be processed and a response sent during testing.

Error Rate: Percentage of requests that fail or return errors during testing.

Max Concurrent Sessions: Highest number of user sessions or connections the application can handle simultaneously.

Max Wait Time: Maximum time a request waits in a queue before being processed.

QA Your Software on All Fronts

Performance testing is about ensuring that the application will perform well under expected and unexpected conditions, providing a good user experience, maintaining operational stability, and helping to manage costs effectively. However, not every performance testing tool is created equal — our test automation and test management software integrates seamlessly with the best platforms available (like JMeter and NeoLoad). They also offer a host of other features to enhance your development QA and testing for higher-quality software that surpasses user expectations. To learn more about SpiraTest and Rapise, visit their pages below: