Kubernetes is an open-source platform used to automate the operations of Linux containers. It eliminates the manual process of scaling and deploying containerized applications and also manages the clusters efficiently. Those clusters host public and private clouds; hence Kubernetes is referred to as an ideal platform to host cloud-native applications for rapid scaling. Google engineers designed Kubernetes. Google was an earlier contributor to Linux container technology, and it can generate more than 3 billion deployments of Linux containers in a week.
Here are some of the Kubernetes features:
Here, are some of the advantages of Kubernetes:
The latest version of Kubernetes: 1.17 was released last month (December-2019). It consists of 22 enhancements, out of those, 14 are stable, 4 in alpha and 4 in beta. Kubernetes 1.17 version improves scalability in the cluster network. Also, it introduces the pod schedule, cluster storage, and runtime options for custom resource support.
Most of the storage systems like Amazon Elastic Storage, Google Cloud Disk create persistent volume snapshots to represent a point time in volume copy. This snapshot is used to restore the existing volume to the previous state. Kubernetes volume plugin provides an abstraction to automate the provision and attachment of the storage file.
Kubernetes also creates an abstraction layer between underlying systems and distributed application systems to agnostic the cluster specifics and application deployment. SIG, which is a Kubernetes storage, identifies critical functionality of snapshot operations for stateful workloads. Kubernetes users can handle use cases without API by providing trigger snapshot operations. At present, Kubernetes users empowered snapshot operations with clusters regardless of storage underlying. Also, Kubernetes snapshot acts as building blocks to develop storage administration and enterprise-grade features with backup solutions.
Kubernetes provides volume plugin systems in which “in-tree” was code for the core Kubernetes. As we know, to add new volume, support was a tough challenge. Vendors wanted to support the storage system to Kubernetes, but it was not possible. Besides, the storage in the third-party code causes security issues and reliability issues in core binaries and the code were complicated to test. Later on, Container Storage Interface solves those issues. As there were many CSI drivers, the production became ready for the CSI model benefits. However, we didn’t force users to make the workload changes by breaking available API storage. The only possible way is to replace “in-tree plugin” with CSI.
CSI(Container Storage Interface) migration enables in-tree storage plugin replacement with corresponding CSI drivers. Users cannot be able to identify the differences if CSI migration works properly. Users may depend on the in-tree storage functionality with the existing interface. If Kubernetes updates the cluster to enable the migration of CSI, then the stateful workloads and deployments continue to function behind the scenes of storage management operations. Kubernetes 1.17 version ensures storage APIs stability for the smooth upgrade promise. This involves backward capabilities. Existing feature behaviors, and API stability.
The volume snapshot feature depends on a common snapshot controller to the CRDs. Both the CRDs and snapshot controller are independent of CSI driver. There must be only one instance snapshot controller to install CRDs per cluster. Hence, Kubernetes distributors deploy the CRDs as the cluster management process. Kubernetes supports Flex, in-tree, and CSI volume plugins. But, whereas snapshot supports CSI drivers to use Kubernetes features on the cluster. The following CSI drivers support volume snapshots:
We have discussed the features of the Kubernetes 1.17 release. These features enable user’s access with a single-line command to the latest upstream in 60 seconds. Snap store proxy controls the `Kubernetes-worker` charms, and CIS (Center for Internet Security) maintains the benchmark of Kubernetes 1.17. This is how Kubernetes 1.17 works.
Anji Velagana, a graduate in Electronics and Communication Engineering from Jawaharlal Technological University, Kakinada. He is currently working as a Digital Marketing Analyst and Content Contributor for Mindmajix. He writes about various platforms like Data Science, Servicenow, Kubernetes, Business analysis, Performance testing, Mulesoft, Azure, SaltStack, and a few other courses. Contact him via anjivelagana@gmail.com and LinkedIn.