How Kubernetes allows developers to deploy without worrying about DevOps
Source – siliconangle.com
As an active distributor of the Kubernetes container orchestration management system, Canonical Ltd is giving developers a way to step up their game. The company is taking away the developer operations component to the developer job so they are free to focus on other important aspects of development that they have more expertise in, according to Stephan Fabel (pictured), director of product management at Canonical.
Fabel spoke with John Furrier (@furrier), host of theCUBE, SiliconANGLE Media’s mobile livestreaming studio, during the KubeCon CloudNativeCon EU event in Copenhagen, Denmark. They discussed Kubernetes and Canonical’s partnership using Kubeflow and the resulting efficiency for developers using those building blocks. (* Disclosure below.)
The “pinch-me” moment
One way that Canonical is working toward developer efficiency is prioritizing the enablement of Kubeflow, a composable, portable, scalable machine learning stack built for Kubernetes. Before Kubeflow, once a Kubernetes application was deployed, it was difficult to re-engineer the project to the cloud without completely redesigning it, and in the process, causing new issues and bugs. Kubeflow and Canonical worked to change that so that the focus is back on the developing of the application itself and making future transitions much easier, Fabel explained.
“The people who are actually writing those applications are not DevOps people, they’re data scientists, right? They shouldn’t have to learn how to deploy Kubernetes, how to create a container and all those things,” Fabel said.
This improvement in efficiency is one reason why excitement abounds at KubeCon 2018. Another reason, of course, is the community that gathers together to discuss innovations and establish partnerships, such as the one between Kubernetes and Canonical.
“Actually using things like Kubernetes as an effective building block to then build out web applications that use things like machine learning algorithms underneath. That’s a perfect use case for a next-gen workload and also something that we might use ourselves internally,” Fabel said.
The building block structure is making web applications more dependable and more able to easily transition without re-engineering the entire application. Furrier referred to it as “an almost … pinch me moment for the people in the industry.”