Last Updated on by Kumar Raja

Understanding Kubernetes

Kubernetes is an advanced tool in the DevOps software development ecosystem which can isolate an application. It can be easily scaled by creating new containers. Speaking of containers, the commonly heard questions are how many servers should we have to create? Who will be addressing the monitoring operations? How to effectively handle app updates? The perfect answer to all these questions is Kubernetes.

To excel in career as a DevOps expert, having knowledge of Kubernetes is very crucial. Build real-time expertise in handling Kubernetes by joining for the best DevOps Training In Hyderabad program by Kelly Technologies.

What is Kubernetes?

Kubernetes can be interpreted as an open-source tool in the DevOps ecosystem. It is an advanced container-orchestration system using which we can completely automate the application deployment process. Having initially been developed by Google, Kubernetes is now managed by the Cloud Native Computing Foundation.

Kubernetes provides a number of advantages for the developer community. It makes it easy for the developers to control the entire system as it gives high-level API. This frees developers from the burden of worrying about the number of nodes, understating where the containers are initiated, or how they interact. As everything gets automated there’s no need to worry about hardware optimization or malfunctioning nodes.

Use Cases Of Kubernetes-

Microservices

Microservices is a major aspect in the enterprises software development process using which applications can easily handle several requests by horizontal scaling. With Kubernetes, enterprises can be benefited from fault tolerance & high availability. Also, several thousands of nodes can be easily updated with configured CI process.

Machine Learning

Machine Learning has now gained a lot of prominence in handling complex real-life challenges. However the process of building a powerful AI model is a very complicated task. A lot of research work is being carried out to develop tools that can simply this process. Kubernetes is one of such advanced tool sets that helps in simplifying the process of training & building a AI model. With Kubernetes all that Data Scientists or ML engineers need to do is preparing the data & building the code. The rest will be handled by a toolkit based on Kubernetes.  

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