Forecasted Top Five Developments in Load Testing for the Year 2016
The digital landscape is rapidly evolving, and businesses are increasingly relying on various channels to generate revenue. According to Andrew Voysey, Head of Software UK at Hewlett Packard Enterprise, this shift requires a focus on performance engineering, a cultural shift that drives informed decisions centered around end-users and their experiences.
In today's competitive market, a web outage can lead to significant financial loss, with an average of $2 million per hour in losses for surveyed companies. Yet, the web remains critical to the way organizations conduct business, with the majority of retail revenue still generated via the web channel.
However, the distribution of traffic and revenue is shifting, with mobile users accounting for a higher percentage of traffic despite only contributing to 30 percent of revenue on average. This underscores the importance of performing complete mobile performance testing to ensure a seamless user experience and drive sales.
In 2016, organizations are predicted to move their software load testing to the cloud for cost-effectiveness and quick simulation of real-world user traffic. The cloud offers elasticity and scalability, allowing load testing to emulate large, real-world user bases by scaling test environments up or down dynamically.
The rise of the cloud also enables on-demand resources and automation, with cloud services enabling automated environments and tools to spin up testing instances rapidly, integrate with CI/CD pipelines, and support autonomous testing frameworks to deliver quick feedback.
Top predictions for software load testing in 2016 emphasized a shift towards more autonomous, continuous, and integrated testing approaches. Autonomous testing tools, such as test.ai, are anticipated to reduce manual effort and accelerate testing cycles.
Testing is also expected to be fully integrated into continuous delivery pipelines to enable faster and higher-quality deployments, reducing Mean Time To Repair (MTTR) and enhancing customer satisfaction by catching performance issues earlier.
Traditional load testing tools, often heavy and with long turnaround times, are expected to be supplemented or replaced by real-time monitoring solutions that provide immediate performance insights during and after deployments.
Modern deployment approaches using feature flags and canary releases require sophisticated, production-level testing to ensure new features do not degrade performance or cause failures. Synthetic testing running alongside real user traffic becomes essential to validate performance under realistic load conditions.
Lastly, cloud-native tools often integrate observability features to measure application performance in real time, helping teams detect subtle degradations early and improve reliability metrics such as failure rate and MTTR.
In sum, 2016’s top load testing predictions foresaw a move beyond traditional scripted load tests to ongoing, intelligent performance validation enabled by cloud infrastructure that supports elasticity, automation, and real-time monitoring—thereby driving improved system and application performance.
In the evolving digital landscape, businesses are leveraging data-and-cloud-computing technology to optimize their performance engineering, with a focus on cloud-based software load testing for cost-effectiveness and real-world user traffic simulation.
As companies adjust to the shift towards complete mobile performance testing, the importance of technology in enabling on-demand resources, automation, and real-time monitoring becomes increasingly evident.
