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Performance Testing Metrics- A Detailed Guide for Businesses

The triumph of any application or website depends on various factors and testing. A quality assurance team performs the testing of any app or software. ‘Performance Testing’ is a software testing method. It is a non-functional method that checks the speed, scalability, reliability, and performance of an application or website.

These performance testing ascertain the application performance under different circumstances like fluctuating networks, varying user loads, etc. During performance testing, some key performance indicators are used to measure the effectiveness of the testing method. These key performance indicators are known as ‘Performance Testing Metrics.’

What are Performance Testing Metrics?

‘Performance Testing Metrics’- The measures or parameters collected during the performance and load testing process. These Metrics help the performance testing engineers or QA teams to determine the success of the testing process and focus on the critical areas in the software.

What is the need for performance testing metrics?

It shows the current performance of the application. Simultaneously, it improves the effectiveness and efficiency of the software testing process. Performance testing metrics help in decision-making for the further testing process.

The primary function of this testing is that it decreases the error rate in the software testing process. As a result, QA teams can give attention to the critical areas in the software.

Importance of Performance Testing Metrics

1. CPU Utilization

This metric measures the percentage of CPU utilized in processing.

2. Memory Utilization

It is a method to measure the utilization of primary memory in the process.

3. Response times

It measures the time between sending the request and receiving the response. It will be better if it has a better response time.

4. Average load time

It measures the time taken to complete the loading process and appears on the user screen by a webpage.

5. Throughput  

It measures the number of transactions produced or handled during the process.

6. Average latency or Wait time

It measures time spent before getting processed.

7. Bandwidth

It measures the volume of data transferred per second.

8. Requests per second

It measures the number of requests per second handled by the application.

9. Error rate

It measures the percentage of errors compared to the total number of requests.

10. Transaction Passed or Failed

It measures the percentage of passed or failed transactions against the total number of transactions.

What are the Two Main Categories of Performance Testing Metrics?

Client-Side Performance Testing Metrics: 

Client-side performance testing metrics test the client-side performance of the software. It evaluates the response of the application of different clients through different platforms like smart tv, desktop, mobile, etc.

Some client-side performance testing metrics are:
  • Time to first byte
  • Page size/weight
  • Time to Interact
  • Time to Render
  • Speed Index
  • Load Time
  • PayLoad
  • Some client-side performance testing tools:
  • Lighthouse
  • GTmetrix
  • Pagespeed Insights
  • YSlow

Server-Side Performance Monitoring Metrics:

Server-side performance monitoring metrics are responsible for evaluating the logical scenario. It affects the performance of the application. Therefore, it focuses on application behavior.

Some key server performance monitoring metrics are:
  • Requests per second
  • Error rates
  • Uptime
  • Thread counts
  • Peak Response Time
  • Throughput
  • Bandwidth
Server-Side Performance Monitoring Tools
  • New Relic
  • AppDynamics
  • Datadog
  • SolarWinds NPA and DPA
  • Dynatrace

Some Important Performance Automation Testing Tools


JMeter is an open-source performance testing tool. It is a java-based software used to measure the performance of applications and software. This tool can effectively track, interpret, and analyze performance testing results. 

Some key metrics of JMeter are:
  • Elapsed Time
  • Latency
  • Connect Time
  • Median
  • 90% Line (90th Percentile)
  • Standard Deviation
  • Thread Name
  • Throughput, etc.

Load View:

It is a browser-based performance testing tool. With the help of this tool, we can see a graphical representation of the execution plan, average response times, and errors.

Some key metrics of Load View:
  • Load injector CPU usage
  • The average response time of transactions
  • DNS Time
  • Connect Time
  • SSL Time
  • Number of sessions
  • Session errors

Load Ninja:

It is a cloud-based performance testing tool for web applications and web services.

Some key metrics of Load Ninja:
  • Virtual users
  • 90th Percentile Duration
  • 95th Percentile Duration
  • Standard Deviations
  • Total Iterations
  • Total Timeouts
  • Total Page errors

So, this was an overall analysis of Performance Testing Metrics and its key performance indicators. These metrics help the testing engineers and QA teams to determine the success of the performance testing process. Moreover, the article also concluded the importance of performance testing metrics during testing any application or software.