Trends in Performance Testing and Engineering - Perform or Perish

Ajay Kumar Mudunuri
Cigniti Technologies

Rising competition across the business landscape is forcing enterprises to up their ante and leverage cutting-edge technology to reach out to their target customers. On the customer's side, the amazing array of diverse products and services is enough to drive frenzy, confusion, and demand. The tech-savvy and highly demanding customers of today want every application to perform 24 x 7, 365 days a year across a plethora of devices, browsers, operating systems, and networks. Business enterprises are hard-pressed to cater to this segment of customers and are migrating to newer technology to stay relevant and competitive. They need to deliver products or services while focusing on personalization, customization, predictions, analytics, and user preferences, among others.


However, adopting the latest technologies can impact the performance of a software application in one way or another. It is only due to the improved performance of software applications that customers can adopt them and help businesses increase revenue. Performance testing services are an important part of the SDLC that help to determine if the performance of the software application is on target. Let us look at the performance testing trends that can help business enterprises score over their competitors and deliver superior customer experiences.

Leveraging performance testing services is necessary to prevent the software application from facing downtime, lag, or other issues. These services can help with easy tracking of issues that have the potential to impact the functionality, features, and end-user experience. The trends in performance testing and engineering are as follows:

Protocol-based load tests versus real browser-based tests

Traditionally, protocol-based load testing is used to test web pages and applications for multiple protocols such as IMAP, AJAX, and DNS. However, with React and Angular-based web development frameworks, a huge amount of computation has moved to the browser engine. So, neglecting performance load testing using real browsers can generate vague results and create performance issues. Since real users largely interface with browsers, QA testers should adopt browser-based load testing services, including choosing performance metrics for JavaScript and HTML/CSS code rendering. This will ensure the running of load tests that are very close to what real users are likely to face.

Shift-left testing

Here, application performance testing is run very early in the development cycle and is made part of each sprint. It aims to monitor performance metrics if and when a new feature is added to the application. This allows the QA testers to determine if the bugs or issues present in the code can cause performance degradation. A robust performance testing strategy should be set up so that performance tests are triggered at every new stage of development. Besides, the results of such tests should be compared to the performance trends of previous test runs.

Chaos testing or engineering

Chaos testing is about understanding how the application should behave when failures are randomly created in one part of the application's architecture. Since several uncertainties can take place in the production environment, chaos engineering can help identify such scenarios and the behavior of the application or system. It allows testers to understand if any cascading issues are going to be triggered due to the failure in other parts of the system. Such a performance testing approach can make the system resilient.

In other words, if one part of the web services or database faces sudden downtime, it should not affect the entire infrastructure. Chaos engineering can help find vulnerabilities or loopholes in the application so that any performance issues can be predicted and mitigated beforehand.

Automated testing using AI

Performance testing scripts are often changed based on customer behavior changes. However, with AI and machine learning, business enterprises can identify the patterns around the user journey and know what the real users are up to when using the software application or visiting the web platform. AI can help the QA team use a performance testing methodology to generate automated scripts that can eventually find new issues or vulnerabilities in the system.

Conclusion

The above-mentioned trends in performance testing can help business enterprises scale and adapt to the dynamically changing software development frameworks. By keeping abreast with the latest technologies and key testing trends, businesses can ensure stable applications, superior user experiences, and possibly customer loyalty.

Ajay Kumar Mudunuri is Manager, Marketing, at Cigniti Technologies

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Trends in Performance Testing and Engineering - Perform or Perish

Ajay Kumar Mudunuri
Cigniti Technologies

Rising competition across the business landscape is forcing enterprises to up their ante and leverage cutting-edge technology to reach out to their target customers. On the customer's side, the amazing array of diverse products and services is enough to drive frenzy, confusion, and demand. The tech-savvy and highly demanding customers of today want every application to perform 24 x 7, 365 days a year across a plethora of devices, browsers, operating systems, and networks. Business enterprises are hard-pressed to cater to this segment of customers and are migrating to newer technology to stay relevant and competitive. They need to deliver products or services while focusing on personalization, customization, predictions, analytics, and user preferences, among others.


However, adopting the latest technologies can impact the performance of a software application in one way or another. It is only due to the improved performance of software applications that customers can adopt them and help businesses increase revenue. Performance testing services are an important part of the SDLC that help to determine if the performance of the software application is on target. Let us look at the performance testing trends that can help business enterprises score over their competitors and deliver superior customer experiences.

Leveraging performance testing services is necessary to prevent the software application from facing downtime, lag, or other issues. These services can help with easy tracking of issues that have the potential to impact the functionality, features, and end-user experience. The trends in performance testing and engineering are as follows:

Protocol-based load tests versus real browser-based tests

Traditionally, protocol-based load testing is used to test web pages and applications for multiple protocols such as IMAP, AJAX, and DNS. However, with React and Angular-based web development frameworks, a huge amount of computation has moved to the browser engine. So, neglecting performance load testing using real browsers can generate vague results and create performance issues. Since real users largely interface with browsers, QA testers should adopt browser-based load testing services, including choosing performance metrics for JavaScript and HTML/CSS code rendering. This will ensure the running of load tests that are very close to what real users are likely to face.

Shift-left testing

Here, application performance testing is run very early in the development cycle and is made part of each sprint. It aims to monitor performance metrics if and when a new feature is added to the application. This allows the QA testers to determine if the bugs or issues present in the code can cause performance degradation. A robust performance testing strategy should be set up so that performance tests are triggered at every new stage of development. Besides, the results of such tests should be compared to the performance trends of previous test runs.

Chaos testing or engineering

Chaos testing is about understanding how the application should behave when failures are randomly created in one part of the application's architecture. Since several uncertainties can take place in the production environment, chaos engineering can help identify such scenarios and the behavior of the application or system. It allows testers to understand if any cascading issues are going to be triggered due to the failure in other parts of the system. Such a performance testing approach can make the system resilient.

In other words, if one part of the web services or database faces sudden downtime, it should not affect the entire infrastructure. Chaos engineering can help find vulnerabilities or loopholes in the application so that any performance issues can be predicted and mitigated beforehand.

Automated testing using AI

Performance testing scripts are often changed based on customer behavior changes. However, with AI and machine learning, business enterprises can identify the patterns around the user journey and know what the real users are up to when using the software application or visiting the web platform. AI can help the QA team use a performance testing methodology to generate automated scripts that can eventually find new issues or vulnerabilities in the system.

Conclusion

The above-mentioned trends in performance testing can help business enterprises scale and adapt to the dynamically changing software development frameworks. By keeping abreast with the latest technologies and key testing trends, businesses can ensure stable applications, superior user experiences, and possibly customer loyalty.

Ajay Kumar Mudunuri is Manager, Marketing, at Cigniti Technologies

Related Links

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When Automating Forever Becomes Faster Than Doing It Once

People want to be doing more engaging work, yet their day often gets overrun by addressing urgent IT tickets. But thanks to advances in AI "vibe coding," where a user describes what they want in plain English and the AI turns it into working code, IT teams can automate ticketing workflows and offload much of that work. Password resets that used to take 5 minutes per request now get resolved automatically ...

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Governments and social platforms face an escalating challenge: hyperrealistic synthetic media now spreads faster than legacy moderation systems can react. From pandemic-related conspiracies to manipulated election content, disinformation has moved beyond "false text" into the realm of convincing audiovisual deception ...

The 5 Pillars of Cross-Platform Observability

Traditional monitoring often stops at uptime and server health without any integrated insights. Cross-platform observability covers not just infrastructure telemetry but also client-side behavior, distributed service interactions, and the contextual data that connects them. Emerging technologies like OpenTelemetry, eBPF, and AI-driven anomaly detection have made this vision more achievable, but only if organizations ground their observability strategy in well-defined pillars. Here are the five foundational pillars of cross-platform observability that modern engineering teams should focus on for seamless platform performance ...

What's Blocking Scalable AI?

For all the attention AI receives in corporate slide decks and strategic roadmaps, many businesses are struggling to translate that ambition into something that holds up at scale. At least, that's the picture that emerged from a recent Forrester study commissioned by Tines ...

Not All Networks Are Built for the Edge

From smart factories and autonomous vehicles to real-time analytics and intelligent building systems, the demand for instant, local data processing is exploding. To meet these needs, organizations are leaning into edge computing. The promise? Faster performance, reduced latency and less strain on centralized infrastructure. But there's a catch: Not every network is ready to support edge deployments ...

Why Observability Is the Missing Piece in Your Business Growth

Every digital customer interaction, every cloud deployment, and every AI model depends on the same foundation: the ability to see, understand, and act on data in real time ... Recent data from Splunk confirms that 74% of the business leaders believe observability is essential to monitoring critical business processes, and 66% feel it's key to understanding user journeys. Because while the unknown is inevitable, observability makes it manageable. Let's explore why ...

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Organizations that perform regular audits and assessments of AI system performance and compliance are over three times more likely to achieve high GenAI value than organizations that do not, according to a survey by Gartner ...

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The more technology businesses invest in, the more potential attack surfaces they have that can be exploited. Without the right continuity plans in place, the disruptions caused by these attacks can bring operations to a standstill and cause irreparable damage to an organization. It's essential to take the time now to ensure your business has the right tools, processes, and recovery initiatives in place to weather any type of IT disaster that comes up. Here are some effective strategies you can follow to achieve this ...