Serena Gray's Blog

  DevOps has brought about a revolution within the IT industry around the world. Because it brings together developers, IT operations teams, and QA, DevOps is often called culture in companies rather than technology. Implementing DevOps has led to a significant increase in productivity, delivery, team coordination, and work culture. This has also resulted in a better customer experience. We will now explore this method in greater detail to see how it affects QA testing. What is DevOps ? What is the best way to get started? This is an evolution of agile methodology. It's a software development approach that bridges developers, QA, and IT operations teams. This methodology aims to remove the silos between IT operations and developers to enable continuous delivery of value to end-users by enabling a CI/CD process. This method brings together individuals, processes, products, and software to produce more efficient software and of higher quality. This helps speed up the development of a...

 DevOps, an IT methodology and culture now about 10 years old, still feels fresh -- and challenging -- to many people in IT. That is because DevOps methodology tools, and cultural principles keep morphing and enhancing. "Its entire purpose is to evolve and change over time." How can you keep up with the changes and remain conscious of the latest lessons learned from DevOps professionals? Our DevOps manual for IT leaders brings you the latest and best information out of our continuing coverage, which means it's possible to have a deep dip in 1 spot. Let's delve into specialist advice and evaluation from DevOps experts and best CIOs. Why is DevOps popular in business IT? DevOps continues to win fans in enterprise IT to get a few important explanations. This manner of working prizes rate, experimentation, and cooperation, all happening on cross-functional teams. All these factors suit the business goals of the instant: Transform the company -- so that it can quickly chan...

So what exactly is DevOps? Let's take a small hypothetical example to illustrate. Let us say there's a small startup that assembles AI-enabled cleaning robots. There are 3 programmers (let's be lazy and simply call them Team D) who compose and execute the code to produce the robots and 2 operational people (Team O of course) who maintain the robot infrastructure in the real-world environment and supply aid for the robot consumers. Team D has only spent 8 months producing the latest robot. It can recognize individuals, take orders from Alexa devices, and clean like a boss. Team D has spent time producing this robot into their controlled dev environment and everything seems to be working smoothly. They couldn't be prouder. They hand over their production to Team O that immediately takes it out to the real world. That's when the problems start. It turns out that the perfect cleaning robot isn't so perfect after all. It does not recognize everybody, it can follow Al...