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Load Testing Metrics: How to Verify Success of Performance Testing

Feb 26, 2020
6 min read

One of the major problems affecting a website’s performance and competitiveness is its inability to cope with the burden of heavy traffic. This in turn leads to an inability to meet all users’ demands without cracks, temporary display errors or response speed. Consequently, the burden on the site is essential in determining its success and profitability.

Before launching a website, you need to make sure it can handle the expected level of activity without a slowdown or downtime. Load testing allows you to see how your site responds to the real situation and helps you figure out where to make changes to avoid unexpected problems when the site goes online.

In this article, we will explore the role of load testing in software development, the different load testing metrics that need to be considered for testing, and how to ensure its successful completion.

The Role of Performance Testing in Software Development

In general, we perform a load test at the end of the development of a version, just before launching the software in real production phase. In recent years, as part of agile development processes, several companies have performed their load tests much earlier. This allows problems to be identified and repaired as soon as possible, thereby reducing correction costs and avoiding last minute delays.  When businesses do not perform load testing right at the beginning of the software development life cycle (SDLC), then there potentially could be heavy costs involved.

Therefore, it is crucial for businesses to characterize and be aware of the peak traffic condition and to evaluate their website’s performance under both peak as well as normal conditions. Furthermore, businesses need to establish the maximum operating capacity of the web application during SDLC in order to prevent website downtime and crashes post-production.

As companies have already moved to a digital age, Load Testing has become the commonly used Performance Testing procedure to assess the stress taking capacity of a website. Load testing is executed in a simulated environment where the company’s website is flooded with incoming traffic to guarantee that it will continue to operate routinely when the site is bombarded with visitors.

In a situation where the website does not react normally to the flood in traffic during the testing process, the issue can be resolved by making the necessary changes or increasing the number of servers and then making the site live.

A widespread misconception amongst people is that Load Testing can be performed at the end of SDLC. For this reason, they wait till the very last moment for performance tests to be developed and executed by another company. However, this practice will certainly result in last minute failures. 

When bottlenecks and performance issues are recognized during the development phase of SDLC, it is easier for programmers to fix the performance bottlenecks without devoting extra time and effort.  Conversely, developers have to put in extra time and effort to fix performance issues once the web application is deployed.

Load Testing Metrics Checklist

There are a number of load testing performance metrics that show how a web application or website is performing. The performance measurement of an application is represented by response metrics which reflects the user’s perspective, while the traffic generated for the web application is represented by volume metrics. Different response and volume metrics are described below. There exist three response metrics:

  • 01
    Average Response Time
  • 02
    Peak Response Time
  • 03
    Error rate

and three volume measurements:

  • 01
    Concurrent Users
  • 02
    Requests per Second
  • 03

Average Response Time

Once you measure the start of every request to the finish of every response to those requests, you will have the data relevant to the round trip of what is delivered from the browser and the time needed for the target web application to deliver what was required.  Average Response time is calculated from the beginning of every request and every reaction to that will request, which gives the information of a round vacation from your browser and typically the time it requires to acquire the response. The average answer time is attained by calculating the imply of most request/response cycle. Typically the obtained value shows the speed from the web program being tested, i. at the. how well the internet site is performing through the user’s perspective.

Peak Response Time

Similar to Average Response Time, Peak Response Time measures the duration of a request/response cycle. The peak indicates the interval where the cycle was the longest. The Peak Response Time reveals which one of the resources is potentially problem some and can arise as a result of various anomalies within the web application.

Error Rate

When an application is under load it may provide some expected errors while handling requests. The error rate is computed as a percentage of problems requested in comparison to all requests. These errors are most experienced when the application reaches a point after which the web application cannot handle anymore requests. The error rate is  crucial in measuring an application’s efficiency, as it measures the “performance failure” of an application.

Concurrent Users

Concurrent users are a typical method to enumerate the load which is being applied throughout a test. This metric measures the number of virtual users active at any point in time. However, it is not equivalent to RPS because a user can create a high number of requests, while the virtual users will not generate consistent requests.

Requests per Second

RPS is the measurement associated with the count of requests that are sent to the target server. This includes requests for Flash/multimedia data files, Web Page stylesheets, images,  JavaScript libraries, XML documents, HTML pages, and any other required resource.


Throughput is measured in units of kilobytes per second. It quantifies the bandwidth consumed during the test and measures the amount of data that flows back and forth between servers.

How to Reach KPI of Load Testing?

1)    Determine your business objectives

In order to determine whether your load testing was successful, you will first need to establish your overall business objectives. One of the key questions you will need to answer is how does your testing relate to the overall business objectives. Also, you will want to ask yourself “How will my application perform under a load test?” Moreover, when establishing your test environment you will need to consider what aspects of the user experience will help establish business metrics and what basic user requirements are related to these business metrics.

2)    Evaluate whether KPIs for your application and web performance have been met

Once you have established your business objective you want to come up with some basic KPIs in order to measure real-time performance with performance objectives. Some examples which are listed above include Error Rate, Requests per Second and Peak Response Time.

3)    Familiarize Yourself With your load environment

Always remember the intention of load testing is to replicate your production environment. Even a small change to hardware or configuration can have a big effect on your test results. Therefore, ensure that you are aware of the hardware limits of your test environment and look for bottlenecks in advance.

4) Focus on your end-users

Without any regular customers or site visitors you would not be able to generate any revenue, therefore, setup your load testing in a way in which you keep the end-user experience at the forefront of any concerns. Once each load test is completed, evaluate the results. Moreover, assess performance against previously identified business objectives and KPIs to ensure that your benchmarks were met. The primary aim of load testing should be that you keep your customers wanting to return to your site while keeping them engaged with your product, service and brand.

5) Execute the load test incrementally

Ideally not everything should be tested initially. Begin by starting with a small number of distributed users and gradually increase the number of users incrementally. In doing so, you will increase your ability to identify bottlenecks and the point when your system crashes. After you have ran the first test, stop and complete analytics on each cycle. Before proceeding to the next testing scenario, ensure you fix any bottlenecks.

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Load tests consider a wide variety of metrics relating to performance. The most critical performance-related metric are the “Load Curves”. Load Curve measurements explore performance limits by testing capacity of the web application, response time and stability.

Load tests are utilized by businesses to find out the traffic and maximum workload their software implementations can sustain, as well as, how efficiently the platform performs under pressure.

PFLB has served over 500 companies across all domains, from finance and healthcare to retail and technology since its inception. It is one of the pioneering software testing services in the industry.

Besides Test Automation, the company has expertise in other core software testing services, such as Performance Testing, Mobile Testing, Integration Testing, Usability Testing, and much more

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