Kubernetes, or K8s for short, is a massively popular and developer-friendly cloud-based technology for deploying, scaling, and managing containerized applications, including software and, more recently, machine learning models. Kubernetes was originally created by Google for managing in-house application deployment, but now, Kubernetes is an open-source system maintained by the Cloud Native Computing Foundation (CNCF).
Kubernetes is a one-stop cloud-native platform for automating operations associated with container-based applications, like Docker. Its popularity and adoption in the software engineering and AI industry cannot be emphasized enough, with leading cloud providers, like AWS (EKS), Azure (AKS), and Google Cloud Platform (GKE), providing their own Kubernetes-based platform offerings.
It is important to consider the concept of containers that Kubernetes builds upon. Containers are a method of packaging apps, along with all their dependencies and configuration settings, so that the app can be seamlessly deployed across various runtime production environments. While alternatives, like virtual machines and Docker Swarm, abound, Kubernetes has emerged as the de facto platform of choice for container orchestration and management.
Swarm is Docker’s native platform for orchestrating clusters of Docker engines. Virtual machines are related to containers in that containers are more flexible, lightweight, and portable, as there is no need to install an OS in every instance. The evolution of virtual machines to containers to orchestration platforms like Kubernetes has helped organizations better manage their application deployment and operational workloads.
In this article, you will learn more about Kubernetes and its applications in the domain of software engineering and machine learning. Discover the many benefits that Kubernetes offers and why start-ups and enterprises should consider migrating their deployment systems to Kubernetes. You will explore a comprehensive overview of the key factors to consider and evaluate from an organizational perspective before making the decision of whether and when to migrate to Kubernetes from other architectures.
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