SD Times Editor-in-Chief David Rubinstein caught up with Lance Knight, SVP & GM, ConnectALL at DevOps Enterprise Summit 2019 in Las Vegas to record an episode of the podcast series What the Dev(Ops).
Even as DevOps reaches a pinnacle in acceptance (as of 2018, only three percent of firms had not adopted DevOps and had no plans to do so), many organizations are still struggling to get high-quality software out the door. DevOps has been promoted by many experts and consultants as a solution to the cumbersome inefficiencies that were common with waterfall methods.
Over the last few decades, DevOps and agile have reached a noteworthy level of recognition: Some 80% of firms have adopted the principles of one or both at some level.
This success has been driven, at least in part, by leadership that has viewed these approaches as the silver bullet that would produce more efficient, less defect-prone software, enabling the firms to deliver greater value to internal and external users more quickly.
It’s a given for web and mobile application development that performance testing is critical to application success. Yet, for organizations wishing to customize third-party (3P) software as a service (SaaS) rather than running it out of the box as written, performance testing can be problematic.
As most organizational leaders recognize at some level, the increasing dominance of web and mobile applications has completely turned the software world on its ear. The number of critical business functions that are processed via a browser or mobile device is escalating, and inaccurate results, aberrant behaviors, and security flaws can all be absurdly costly.
In today’s threat-laden environment, where production data is one of the chief targets of hackers, organizations developing software must expend both time and resources securing their production data. One of the simplest ways to ensure security for software testing activities is through the use of targeted, advanced data-handling solutions that can synthesize and virtualize production data.
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