Top Performance Testing Challenges and Their Solutions

Performance Testing Challenges and Solutions

Software development always needs the support of robust software testing to release flawless and secure applications. It involves testing the developed software and making sure that it functions as per the requirements and is foolproof for end-users. Software testing is categorized into two major types – non-functional and functional testing.

Functional testing includes integration, unit, sanity, system, interface, smoke, acceptance, regression, and more. Common non-functional testing types are endurance, reliability, recovery, localization, performance, security, and more.

Out of these, performance testing is one of the most crucial testing processes. It ensures the stability of the software under various load conditions.

What is Performance Testing?

Also known as load testing, performance testing includes the processes through which applications are tested to evaluate their system performance. The system is significantly tested under various network and load conditions to check out the time taken by the app to respond under different loads.

Performance testing is done to ensure the performance of an application is not affected by various factors including bandwidth availability, network fluctuations, load traffic, and more. In a nutshell, it identifies the speed of the system along with identifying issues including latency, speed, throughput, response time, bandwidth issues, load balancing, and more.

Multiple types of performance testing are leveraged including load testing, endurance testing, stress testing, volume testing, spike testing, scalability testing, and more. These methods help in determining the responsiveness and speed of the application, website, or network.

Why is Performance Testing Essential for Testing Business Websites and Mobile Apps?

Performance testing is done to calculate the speed, reliability, scalability, and stability of the application under multiple load conditions. In order to deliver a flawless performance, every app needs to be stable and capable of delivering consistent results at any point in time.

This becomes, even more, business-critical with banking and eCommerce apps that receive a large amount of footfall on a regular basis. Any glitch or performance issue can dent the brand reputation of the business.

Hence, it is crucial for applications to work efficiently under the stress of a large number of users to ensure business continuity. This is why performance testing is one of the crucial parts of the software development lifecycle (SDLC).

Performance Testing Process Overview:

Here are a few key steps that are executed in a performance testing cycle:

  • Analysis of the existing environment
  • Collect performance characteristics of the system
  • Define load distribution and usage model
  • Performance acceptance criteria
  • Develop test plans, test assets, test scripts, and scenarios
  • Configuration of load generation environment
  • Execution of tests
  • Monitoring application servers, web servers, database server performance counters
  • Analyze and correlate results
  • Generate detailed reports
  • Give performance improvement recommendations
  • Retest if required

The QA team is significantly involved in performance testing while following all the required steps to achieve effective results. However, teams might face certain challenges in performance testing that might impact the performance testing results.

Let us take a look at these performance testing challenges (and some best practices too) and how to resolve and leverage them.

1. Selection of Wrong Performance Testing Tools

Appropriate selection of a performance testing tool depends on multiple factors including application technology stack, communication protocol, the skill level of performance test engineer, and licensing cost among others.

Selecting the wrong tool can result in loss of testing days. 


QA teams and the QA manager need to thoroughly evaluate the app under test (AUT) while calculating the licensing costs as well as the tool capabilities, to select the appropriate performance testing tool.

2. Lack of Proper Test Strategy and Coverage

A lot of effort and time goes into designing an effective and comprehensive test strategy to identify and prioritize project risks. Proper test strategy and coverage help in identifying application performance characteristics, planning of appropriate tests, simulation of real-user interaction, API services testing, and testing whether all the services are working as per the expectation or not.

In the absence of proper test coverage and strategy, it can become cumbersome to get effective performance test results.


The performance testing team needs to invest time in understanding and analyzing the application architecture along with other performance factors including the geography of usage, load distribution, usage model, resilience requirements, availability requirements, tech stack, reliability requirement, and more.

A clearly thorough strategy should be implemented to test all the required performance metrics for effective results.

3. Time and Budget Constraints

To achieve effective results, load testing demands both budget and time. In the absence of proper planning during the development stage, the allocation of resources for performance testing can be scanty. It leads to greater dependency on low-skilled resources who are not able to understand the entire scope of performance testing.


It is crucial to thoroughly plan for performance testing at the beginning of the project including the required resources, time frame, and appropriate budget.

4. Lack of Knowledge About the Need for Performance Tests

Many stakeholders do not understand the criticality of performance testing during SDLC. In several cases, performance issues crop up in the post-production release of the software which might crash the app and bring disrepute to the brand.


Product owners, stakeholders, or test architects need to plan thoroughly for performance testing and treat it as an integral part of the end-to-end testing process. The apps should be tested for performance by exercising databases, web servers, and third-party apps for effective performance.

5. Improper Analysis of Performance Test Outcomes

A good amount of application and system knowledge is crucial to properly analyze the test results. Improper analysis can lead to performance glitches.


Performance analysis should be handled by seasoned performance engineers who have a thorough understanding of the product workflows, architecture and test processes. Test engineers need to be well aware of the application architecture.

An experienced tester would be well aware of web architecture, OS concepts, networking concepts, OSI model, data structures, client-side performance concepts, and server-side performance concepts. The performance expert would analyze the test results efficiently.

6. Challenges in Conducting Performance Tests on Production Environment

Executing load tests in a fully functional production environment can be challenging. While performing the test in such a situation, any change to the production environment can affect the user experience for real-time users.


Close monitoring of trends in the production environment is crucial to identify irregularities. Hence, it is advisable to plan performance tests in a production-like environment instead of a real production environment.

In case business requirements ask you to execute performance testing in a real production environment, then you should conduct the test during off business hours with sufficient time for any corrective measures in the event of any crash.

Also, developers often use cache data for testing that is not able to give a real-world scenario. Hence, it is advisable to leverage the GET data during production and use different data sets for multiple tests.

7. Testing Scenarios

Executing performance tests considering different scenarios is crucial to ensure app’s reliable performance in any situation.


Test engineers should test the application in different scenarios including spike testing, load testing, endurance testing, and reliability testing. Also, make sure that all the tests are done on real-time production data.

You can also prioritize the scenarios by diving them into more often and less used features. In short, heavily used features like user log in, menu etc. should be tested more, and scenarios like buying a subscription that is used less can be tested fewer times. The load patterns and test scope can be aligned accordingly.

8. CPU Utilization

Identifying the CPU utilization of each and every server is crucial to identify the effectiveness of your performance tests.


CPU utilization helps you understand how tuning changes have affected the performance of the system. If the CPU hits 100 percent of its capacity then it can not process more data and throughput flattens. Hence, the best practice should be to keep the CPU utilization below 80 percent for each processor.

Analyze the CPU utilization of all servers that are used in the application under test (AUT) infrastructure. CPU utilization is a crucial key metric that can help you easily identify the servers that are causing performance issues and could be a potential bottleneck. It is also essential to monitor memory and heap size to ensure the efficient run time.

9. Understanding of Business Logic

Understanding complex business logic for apps to effectively write test cases can be challenging.


You can leverage a logical process flow diagram consisting of complex requirements including multiple branches, nodes, and decision boxes to understand the project requirements. You can also use the decision table method to consider all the inputs, validations, and results that are required to conduct the test efficiently.

10. Break Points

Identify the maximum load-bearing capacity of an application. It is also known as Fatigue Test.


Many times, test engineers just tend to test the application for the expected number of users. However, it is essential to identify the break points of an application and ensure whether the servers are tuned enough in the event of an abrupt spike in traffic.

It can also be used to identify the response time of applications at different numbers of concurrent users or calls. You can monitor application behavior, analyze components that fail first, determine the impact of the failure, and find out tuning opportunities.

11. Representation of Result Data

With heaps of data present in complex spreadsheets, presenting the data in an easy-to-understand manner to the client is always a performance testing challenge.


Performance testing teams can create an interactive dashboard capable of reflecting test data in real-time. You can use graphs and charts to present all the test data in an easy-to-understand manner. It would also enable the client to access data at any point in time and from any location easily.

You can also use the data reporting tool for efficient comparison with different test results including baseline.

In Summary

Performance testing is responsible to identify the reliability, scalability, speed, and resource usage of the application. It is essential for corporate websites especially mobile apps and eCommerce websites to ensure they are capable of scaling up in the event of an abrupt spike in traffic.

QA teams adopt several performance testing methods to achieve optimum results. However, during performance testing they also face several challenges and to achieve quality at speed, above mentioned measures are taken.

About the Author

QA InfoTech

QA InfoTech

Established in 2003, with less than five testing experts, QA InfoTech has grown leaps and bounds with three QA Centers of Excellence globally; two of which are located in the hub of IT activity in India, Noida, and the other, our affiliate QA InfoTech Inc Michigan USA. In 2010 and 2011, QA InfoTech has been ranked in the top 100 places to work for in India.

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