Software is eating the world, as they say. You don’t need to be a tech company for software to run your universe. Last year, 3.7 billion people were affected by software failures. $1.7 trillion was lost due to, yes, software failures. One unfortunate financial services company lost $2.3 billion in just one day, all because of software failures.
Software failure is no joke. The implications are serious: reputations shatter, stocks tank, careers end. Performance testing is the best line of defense, which is why performance testing matters so much – and with the shift to Agile and DevOps methodologies – performance testing will have to be automated.
All enterprises carry out some level of performance testing. Mention it and the response is usually, “Oh yes, we do that.” But when quizzed by Forrester less than a year ago about the level of performance test automation they had achieved, over 40% of respondents said, “Below 10%”. Doubling down on that statistic, when asked what percentage improvement they had experienced in performance test automation in the last 12 months, the number replying “below 10%” rose to nearly half of all respondents.
As you can see here, the maturity of their performance automation is not where it should be. For mission-critical applications, base level performance testing – executing test scripts in the test environment and on test devices – is simply not enough.
End-to-end performance monitoring
Performance testing should begin much earlier in the software cycle. Right at the start of the design phase, enterprises should be upfront about addressing performance requirements. Once these SLAs are in place, they will inform what tools to select, what test environments to procure and install, and the test data to define, populate and record. Fine-tuning performance shouldn’t stop when the tests have run. Your data holds the insights to unlocking future issues too, so risk mitigation strategies play a vital role in managing performance. Risk mitigation, planned and effectively deployed, is the difference between software slowing down a bit, and the kind of epic fail that gives rise to really bad headlines.
Leverage AI and analytics
Taking a holistic, end-to-end approach is a great start, but performance testing maturity also involves deploying the best tools available. With the relatively new advances in artificial intelligence (AI), machine learning (ML) and big data analytics, which are impacting every aspect of software development and testing, tool selection becomes critical. We are proud of Infostretch’s own AI-powered suite of solutions, ASTUTE, as it is the only one in the market to address every stage of the testing cycle. Leveraging the power of AI technologies results in significantly better outcomes, both in terms of operation efficiency (speeding up releases) but also in quality improvement terms. A lot of that is down to advanced analytics that predict faults and prescribe fixes. Test data doesn’t just describe what’s happened, it can predict the future. For instance:
– Coverage analysis identifies optimal coverage, ensures end-to-end traceability and predicts risk
– Defect identification is a powerful technique for predicted anomalies, bugs and performance failures
– Defect prevention deploys model-based resources, effort and time allocation.
Real-life performance testing
Traditionally, performance testing has fallen to automation engineers to enhance and maintain. It has relied on their ability to combine different sets of tools and to derive actionable intelligence from the disparate parts. If you didn’t have black-belt integration skills, you likely did not have particularly advanced performance testing.
AI-powered testing is changing all that. AI test bots can be set up quickly and require no specialist knowledge. In combination with our partners, HP, IBM, SOASTA, PlatformLab and Compuware, we can answer questions like: What should we expect once the application is in production? Where are the potential bottlenecks? How to tune application parameters to maximize performance?
Mission-critical applications need a mature approach to performance testing and monitoring. Software glitches waste time for all concerned – staff and customers alike – and that’s the best-case scenario. At the worst, failure has catastrophic consequences: customers leave, the brand is in tatters, investors wobble, value is lost… not to mention career damage.
No organization can afford to hit the headlines for all the wrong reasons. We have developed a specialized online assessment that examines an organization’s digital maturity. Take the test today to figure out if your performance testing needs to evolve. To speak to Infostretch about leveraging the latest AI techniques in performance testing, contact us about our AI-powered software testing solution, ASTUTE.
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