20 Key Performance Testing Metrics to Supercharge Your Software Testing Strategy

Performance Testing is the most important factor when it comes to determining the success of a website, application, or software. As it ensures that the performance of the software matches the end-user experience. In today’s tech-savvy and high-speed world, nobody wants to end up on a page that takes a long time to respond, load, or frequently crashes. To ensure that your target audience does not face such technical issues, there are a few combination performance tests that you must follow.

To conduct the required performance testing types, you must be aware of the performance testing metrics that are necessary for a particular software application. These metrics include factors like response time, throughput, error rate, CPU utilization, memory, network latency, and more. To help you have a deep understanding of each of these metrics, we are going to cover all the 20 Key Performance Test Metrics to make your software super reliable, scalable, robust, and user-centric.   

What are Test Metrics?

Performance testing metrics refer to the measures or the parameters gathered during the procedure of software testing. These metrics are important as they help the team of testing engineers determine whether the test has been successful or not, or they help identify whether there are any serious bottlenecks in the system or not. The reason these metrics are important is they help ensure that the quality of the software is robust, secure, and end-user-ready.

What are Software Testing Metrics?

Software performance testing metrics are crucial indicators of the performance of the application under test (AUT). It determines the test progress and the overall health of the application including factors like quality, productivity, security, and more. The reason we use the software testing metrics is because it helps us understand the areas of improvement, efficiency, and effectiveness. These metrics help testing engineers make better decisions for future testing scenarios as they offer accurate data. 

Overview of Key Performance Test Metrics

Different performance testing metrics are required to set up an efficient performance testing strategy. These key performance metrics depend on the various requirements of the software. For instance, a health and diet platform should have decent page speed for users to move around within the website. Whereas, banking software must have a robust security system to handle the confidential data of the users. 

This way, a specific software or application will have a specified requirement or need. This is the reason why the key performance test metrics will vary from one software to the other. So QA testers need to know about these metrics in detail. Let us explore these metrics in more detail in the next section.

1. Response time

Response time refers to the amount of time that software takes to respond to user requests. Response Time is measured from both the client’s side and the server’s side. There are usually four sub-categories of response time. They are as follows:

Minimum Response Time

Minimum response time is considered to be the best-case scenario. It is the amount of time that the system takes to respond to any user request.

Maximum Response Time

Maximum response time is considered to be the worst-case scenario. It is the longest amount of time that the system takes to respond to any user request.

Average Response Time

Average response time is measured by putting the Total Amount of Time taken / Total number of requests on the platform. It is considered to be the typical response time of a user.

90th Percentile

The 90th percentile is the amount of time that the system takes to respond to 90% of all user requests. 

2. Throughput

Throughput is one of the most important key performing metrics that is measured in performance testing. It is measured by the total number of users / total amount of time taken by the system. It is measured in bytes per second. 

3. Error rate

While conducting performance testing on a particular system, errors will always surface on the dashboard. Testers usually measure it by (number of failed requests/total number of requests) * 100. This key performance metric helps us understand the bottleneck in a system of software. 

4. Concurrent users

Concurrent users refer to the most or the maximum number of people who can use the system or the application simultaneously. Concurrent users help determine whether or not the application is ready to handle numerous user requests simultaneously, without any degradation or performance issues. 

5. Transaction Per Second (TPS)

Transaction per second refers to the number of transactions that the application or the software can complete in one second. It helps determine whether the software is on time or if there is any delay.

6. CPU Utilization 

CPU Utilization of software is measured by the following formula:

{1 – (idle time/total time)} * 100

CPU Utilization is an important metric in performance testing as it helps understand the percentage of CPU capacity utilized while processing user requests. 

7. Memory Utilization

To measure memory utilization, testers use the following formula:

(Used Memory/Total Memory) * 100

It is an important performance testing metric that helps determine the amount of memory that has been used owing to responding to several user requests, and the memory that is remaining in the software or the system.

8. Network Latency

Network Latency is the difference between the time taken for response and the time spent by the user. It is also known as Network delay or lag, as it determines the delay that occurs during the transmission of the data. 

9. Page Load Time

Page load time refers to the amount of time it takes for the page to appear on your screen. It is calculated from the point of initiation of the user request and the point of completion of loading of the page. 

10. Request Per Second

This metric in performance testing is extremely important as it helps determine how many user requests can the software or the application handle per second. 

11. Server Response Time

With server response time, testers can determine how long it takes for a device or a system to receive feedback from the server after the server has successfully received a request from the web page.

12. Database Query Time

Database query time refers to the time limit set for one database query.

13. Peak Response Time

Peak response time is the longest request/response time loop taken by the software or the application.

It helps understand the longest time that the software takes and why.

14. Scalability

Scalability refers to the ability of the software to maintain its optimum performance even when the load on the software gradually increases. It is one of the most important metrics of performance testing as it determines the capability of software under increasing load.

15. Virtual Users

A virtual user is referred to a set of behaviors that are virtually generated through the automated application. By checking the number of virtual users or virtual user requests that a software can deal with, at a particular amount of time, testers can determine the robustness of a system.

16. User Satisfaction

User satisfaction is measured through the number of user queries that the system can solve at a given period. There are several factors like the time taken to solve the queries, to respond, etc. that are used to determine this metric in performance testing.

17. Resource Utilization

Resource utilization is when you can measure the resources available in the system, that you have to use to continue a proper request/response cycle. It helps determine how fast the system uses up the resources available for the software to have its optimum performance.

18. Bottleneck identification

Identifying bottlenecks is very important during performance testing. It is required to know how many and in what areas there are bottlenecks in the software. Then these areas are improved or rather perfected to make the software end-user ready. 

19. Transaction Success Rate

The transaction success rate is another metric to determine the performance of software or an application. The system with a higher TSR is end-user-ready. The system with lower TSR needs improvement for end-users to use them.

20. Test Completion time

Test completion time is a good metric to test if the AUT is smoothly functioning or not. If it takes a lot of time, with a lot of bottlenecks and obstructions, then the software needs to be perfected further. Otherwise, it is ready to be launched into the market. 

Client-Side Performance Testing Metrics

There are a different set of metrics that the QA testers test from the client’s side of the browser. These are:

KPI Metric	Description
Time-To-First-Byte (TTFB)	It is a test done by the QA tester team, to understand the time taken by the client’s server to fulfill a request. The total time taken to complete one HTTP request and load the first byte of the page is called TTFB or Time-To-First-Byte.
Page Size/Weight	It refers to the entire size or the weight particular web page.
Interaction Time	It refers to the time taken by the software/application to fully interact with the user.
Render Period	Rendor period refers to the amount of time taken by the webpage to load or reload.
Speed Index	This metric refers to the amount of time the web page takes to show up on the user’s screen.
Load Time	It is the average amount of time a web page takes to fully show up on the end-user’s screens.
Payload	It refers to the difference that comes out of the essential piece of information and the information used to support it.

Server-side Performance Testing Metrics

As the performance of the server directly affects the performance of the website, make sure to check these server-side performance testing metrics:

KPI Metrics	Description
Requests Per Second (RPS)	It is mainly done for search engines to see the amount of requests it can handle per second.
Uptime	Refers to the overall size of a page.
Error Rates	Refers to the percentage of error compared to the number of requests made.
Thread Counts	Refers to the number of requests that an application can handle at one second.
Peak Response Time	The longest time that the server takes to finish one request/response cycle.
Throughput	Refers to the number of requests that an application can handle in one second.
Bandwidth	Refers to the maximum amount of data capacity that the server can transfer in one second.

Conclusion:

Performance testing is a non-functional software test that is used to test the software’s speed, scalability, reliability, responsiveness, and robustness. To make performance testing strategies beneficial for businesses, certain metrics are required to be known. These metrics are useful for effective tracking of the performance of the application under test. It is only when the software passes all these mentioned metrics that we can say that the software is ready to be released into the marketplace.