What is a Kubernetes Cluster?
A Kubernetes cluster is a combination of a master node and a number of worker nodes that run containerized applications. The nodes may be either virtual machines or physical computers, depending on the cluster.
How does a Kubernetes cluster work?
To run applications in a Kubernetes system, a container runtime, such as HPE Ezmeral Runtime Enterprise, directs communication between a master and worker nodes.
A master node controls the state of the entire cluster, issuing all task assignments, such as configuring, maintenance, scheduling, and updates. It acts as the control plane for the cluster and maintains a record of all Kubernetes objects, automatically responding to any changes.
A number of secondary nodes, called worker nodes, run on each cluster. They maintain network connections, administer network rules across nodes, and make sure the containers are all running according to specified metrics.
What should I consider when implementing Kubernetes clusters?
Kubernetes arranges containers into pods, which run on clusters of nodes. When setting up your Kubernetes system, you need to consider the relationships between pods, nodes, and clusters, including the following aspects:
· Scalability: Each application has a different ability to scale under load.
· Capacity: By creating redundancy with master node components, you can ensure high availability to balance pod-to-node mapping.
· Security: Throughout your environment, you should create multiple layers of security, including regularly scanning container images, ensuring signed certificates are enforced, and updating images.
What makes up a Kubernetes cluster?
There are six main components in a Kubernetes cluster:
1. etcd: A lightweight configuration store called etcd is the most basic component. It stores configuration data for all clusters to access.
2. API server: A RESTful interface for command-line tools called a Kube-APIserver provides a way to manage tools that control and configure Kubernetes clusters through REST-APIs.
3. Controller: The kube-controller-manager maintains the state of the entire cluster, constantly monitoring for any variations, such as the number of replicas, and executing procedures to ensure the desired state.
4. Scheduler: The kube-scheduler sets the order for containers that are handling cluster workloads, using the containers’ configurations, resources needed, and workload-specific metrics to determine the scheduled runtimes.
5. Proxy: A kubeproxy manages network connectivity, relaying requests and performing load balancing with consistent rules and one Kubernetes Service concept across the entire cluster.
6. kubelet: An agent/service called a kubelet interacts with the Docker engine to make sure that all containers in a pod are fully operational and running according to a specified set of PodSpecs.
What are the benefits of containers?
Containers offer developers many advantages because of their:
If you want to use your own images—not the default ones that download automatically—you can pull custom images from a repository.
Initialize the control-plane node
kubeadmin init runs a series of prechecks to make sure your machine is ready before downloading and installing the components.
Install a Pod network add-on
For Pod communication, kubeadmin sets RBAC (role-based access control) as the default method of communication. Make sure your Pod network plugin supports it before installing, and then confirm the CoreDNS Pod is working.
When you initialize your control plane, kubeadmin outputs a join code, which is used for mutual authentication between the control-plane node and the nodes you’re connecting. Be sure to keep this token safe because anyone with the token can add nodes to your cluster.
To run workloads, you need to join worker nodes to the control plane. For each machine, you should enable SSH, input “become root,” install runtime if needed, and then run the command that was output by kubeadmin init.
HPE and Kubernetes clusters
For decades, HPE has delivered hardware and software combined with compute, networking, memory, and storage solutions at scale, including ProLiant, Apollo, Synergy, Nimble, SimpliVity, and 3PAR. Now, the HPE Container Platform offers CICD solutions for the machine learning and AI your DevOps teams use.
With a flexible set of services, the HPE Container Platform connects the hardware and the software with a virtualization layer that is abstracted away from them, delivering the scale and stability needed to manage distribution of Kubernetes-based orchestration across multiple platforms, for multiple business units and multi-tenancies. The platform offers a global namespace so all your apps have the same data access no matter where they’re located. And you can also instantiate others in the control plane, which enables you to scale your Kubernetes containers. With enterprise-grade strength on networking identity and access management, you can run Kubernetes at scale.
In addition, HPE offers expert services to help organizations with their containerization projects. From planning to application, migration, and development, to proof of concept, to production, HPE Pointnext Services for containers helps you accelerate the transformation of your technology, people, and economics so you can move fast as you drive innovation.