Kubernetes, a container management tool that provides a platform for automation of scaling, deployment, and operations of application containers across host clusters. It eliminates all the manual operation processes involved with containers and lowers the cost associated with them.
This article will explain you what are Kubernetes, and answer the following questions:
- What Purpose Are Kubernetes Used For?
- What Issues Does Kubernetes Solve?
- How Do They Save Time and Money For Large Scale Systems?
- What Startups Don’t Need To Care About Kubernetes?
What Are Kubernetes?
Developed by Google, Kubernetes (k8s) is an open-source container management (orchestration) tool for application deployment, scaling, and management. Featuring a cloud-agnostic design, it makes containerized applications run on any platform without introducing any changes in the code.
With Kubernetes, you can cluster together a group of hosts, manage them. The clusters then span hosts across private, public or hybrid clouds.
There it serves as an ideal platform for large cloud-based applications that require large scaling.
What Is Their Purpose?
Large apps use multiple containers. These containers are to be deployed on multiple server hosts. With this, containers get multilayered, and their security gets complicated.
That is where Kubernetes come into action.
They give you all the management and monitoring capabilities that are required to build, deploy and scale containerized workloads. It also allows the user to develop application services that span, schedule, and scale those containers in a cluster and manage their health over time.
Other purposes of Kubernetes include:
Packages your application automatically and schedules the containers based on their requirements. For complete utilization, it also maintains a balance between critical and best effort workloads.
Kubernetes manages batch and CI workloads, thus replacing the containers if needed.
- Automatic Rollouts & Rollbacks
It rolls out the app changes and configuration in a manner by ensuring that not all the instances are killed at the same time.
Lets you mount on the storage of your choice. You can either choose local storage or a shared network system or public cloud provider.
- Managing Services Declaratively
This management approach ensures that applications are running in the same manner how you deployed them.
What Issues Do They Solve?
There are companies with large scale systems who use Rocket, Docker or maybe just a simple Linux container for containerizing their applications.
Regardless of whatever it is, they use it on a massive scale.
These enterprises have 100’s and more containers for load balancing the traffic. As traffic increases, they have to scale the number of containers to service the requests that come in every second. Then, they have to scale down the containers during less demand.
Although this scaling can be done by Rocket or Docker, Kubernetes supports auto-scaling and cuts down on all your manual effort.
The ReplicationController handles the application scaling and ensures that a number of pod replicas (a group of containers deployed to a single node) are running, as needed. If there are too many pods, ReplicationController terminates the extra ones, and vice versa.
Other issues that Kubernetes solve include:
Your application is up and running. But now you need to ensure that the client load is spread equally among the nodes in your cluster. You also don’t want some containers working in the application while others are sitting idle.
In Kubernetes, load balancing is handled by the service. For each service, you can select a label selector that is used to identify the pod’s replicas. The scheduler uses the label selector that selects the right service for request, ensuring that client load is always balanced.
Kubernetes also assign a DNS name for a set of containers and IP address to containers, which load balances the traffic inside a cluster.
- Cluster Management and Monitoring
When large applications are running on a massive cluster, they require proper monitoring and management.
Kubernetes Dashboard is a web-based UI that deploys a containerized application to a cluster, monitor the metrics like memory usage and CPU, and manage the cluster resources. However, the dashboard is not deployed by default, use ‘kubectl’ to deploy the dashboard and then use it.
You need to ensure that your containerized application run on the right machines in your cluster, rather than running on all.
Pod (a group of containers) is the unit of scheduling in Kuberenetes. As a Pod is created, the scheduler finds the suitable node on which it should run. The ‘kube-scheduler’ component selects the node and ensures that resources needed by the node are the same as required by containers.
By solving all the above issues, they save time and money for the enterprises running large scale systems.
Why Don’t Startups Need To Care About Kubernetes?
Although Kubernetes runs the containerized applications seamlessly; for smaller applications or start-ups running them, they only add more cost and complexity to the project.
- Does not deploy source code.
- Does not provide the application level services including middleware, databases, caches, and data processing frameworks.
- Does not adopt any maintenance or machine configuration systems.
- Does not work for monitoring or logging solutions.
Since Kubernetes operates only on a container level, it only offers the features that applicable to PaaS offerings such as deployment, scaling, load balancing, and monitoring.
Moreover, small businesses have to work through reorganization, when using Kubernetes with their existing applications.
The Final Words
Kubernetes is a platform that allows the users to run and scale containerized workloads on an abstracted platform. It helps you to implement and rely on container-based infrastructure in production environments.
While its components like pods, master, node, replication controller, and more can seem daunting at first, the feature set works exceptionally for large-scale applications. However, the small-scale applications don’t require Kubernetes as they only add to its complexity and expenditures.