A contemporary application, packaged as a set of containers and deployed as microservices, needs an infrastructure robust enough to deal with the demands of clustering and the stress of dynamic orchestration. Such an infrastructure should provide primitives for scheduling, monitoring, upgrading and relocating containers across hosts. It must treat the underlying compute, storage and network primitives as a pool of resources. Each containerized workload should be capable of taking advantage of the resources exposed to it, including CPU cores, storage units and networks.

Kubernetes is an  open source distributed system that abstracts the underlying physical infrastructure, making it easier to run containerized applications at scale. An application, managed through the entirety of its life cycle by Kubernetes, is composed of containers gathered together as a set and coordinated into a single unit. An efficient cluster manager layer lets Kubernetes effectively decouple this application from its supporting infrastructure, as depicted in the figure, below. Once the Kubernetes infrastructure is fully configured, DevOps teams can focus on managing the deployed workloads instead of dealing with the underlying resource pool — CPU and memory — which is handled by Kubernetes.

Kubernetes Works Like an Operating System

Kubernetes is an example of a well-architected distributed system. It treats all the machines in a cluster as a single pool of resources. It takes up the role of a distributed operating system by effectively managing the scheduling, allocating the resources, monitoring the health of the infrastructure, and even maintaining the desired state of infrastructure and workloads. Kubernetes is an operating system capable of running modern applications across multiple clusters and infrastructures on cloud services and private data center environments.

Like any other mature distributed system, Kubernetes has two layers consisting of the head nodes and worker nodes. The head nodes typically run the control plane responsible for scheduling and managing the life cycle of workloads. The worker nodes act as the workhorses that run applications. The collection of head nodes and worker nodes becomes a cluster.

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