Kubernetes runs on Google technology. Before Kubernetes, Google used an even more complex system called Borg, which ran all of Google’s wide array of services like Google Maps and Gmail. Kubernetes aims to accomplish this enormous task, this time for container systems. Here’s why you should use it to Dockerize your applications.
When applications are tested, developers move them from one environment to another to check that they run accordingly. Of course, this means setting up all kinds of test environments with varying security and network settings, as well as multiple operating systems.
By packaging development environments in containers, you do away with infrastructure differences altogether. Since each container would contain all you need to run an app, developers may deploy applications consistently, rapidly, and reliably. Containers are also lighter than virtual machines, consumes fewer resources, and can be installed anywhere. Hence, usage of container services like Docker have gone through the roof.
But with Kubernetes, Docker is doubly useful.
Supporting Container Systems
The difference between Kubernetes and Docker is that the former is a container management tool. As a container system, Docker can modularise applications into smaller parts. But you still want to manage, monitor, and integrate these parts. You will want to track them for resource usage and allocate more where needed. Which is what Kubernetes does.
Kubernetes architecture organises and co-locates the containers into logical units called pods. They share resources such as IP addresses, file systems, and storage. You don’t have to stuff a container image with too many objects, making it lighter and more manageable.
Superior Container Management
Kubernetes Deployment Controller helps ease the management of containers:
Kubernetes is excellent for integration into a Continuous Integration, Continuous Deployment pipeline (CICD). It handles a lot of the heavy lifting required with classic infrastructure as code (IaC) environments. It’s built-in deployment model is very well thought out and used by many clients. The current and recommend way to use deployments is to use the deployment functionality as a controller. The deployment controller defines how an application should be structured (for example a three-tier app) and what pods need to be launched and how they communicate with each other. This allows you to upgrade applications very easily either with a rolling-update functionality or with a simulated blue/green deployment model.
- Scaling – It lets you do first-time deployment of software across pods, and you may scale the deployments in or out as needed. You may even pause and resume a deployment.
- Horizontal Scaling – You may also scale the number of required containers up or down, either manually or automatically, depending on CPU usage.
- Version Control and Upgrading – You may update pods to the latest versions of applications, or you may downgrade as needed.
- Visibility – You can immediately identify successful and failed deployments using status queries. Kubernetes automatically restarts failed containers to the desired state in order to maintain applications. Should a node in the cluster die, then its containers get rescheduled to different nodes.
With Kubernetes, you are not relegated to just using Docker. You may use Kubernetes in conjunction with Azure Container Service, AWS EC2, IBM, RackSpace, and more. Kubernetes also supports a wide variety of applications without setting limits on things like application frameworks and supported language runtimes—if it runs on a container, it should run on Kubernetes. It also supports various types of workloads (stateless, state-ful, data processing).
For a deeper look at Kubernetes architecture, read our introduction to this system and follow this in-depth guide. You can also find a Kubernetes tutorial on running it in AWS. Finally, if you would like to get your enterprise started on Kubernetes, read about how you can do at our PolarSeven webpage.