Kubernetes is closely associated with containers and virtualisation. But what exactly is it? What is it used for? And what are its benefits? Find out here.
Lois Neville
Marketing
Kubernetes is closely associated with containers. Containerization is a form of virtualisation that packages up software with the dependencies needed to run it. Kubernetes is a framework that manages containers.
Kubernetes itself started life as an internal Google project. You may also sometimes see it called K8s. It was developed to address the need to coordinate and manage Google's vast container-based infrastructure. Kubernetes was then released as a full-blown open-source community project in 2014. It is maintained by the Cloud Native Computing Foundation.
We’ll introduce Kubernetes, and will go through how it works, what it does, and what it is suitable for. This guide is designed for those who are new to containerization and for anyone who wants to refresh their knowledge.
This is what we’ll cover:
How to pronounce Kubernetes
What is Kubernetes used for?
What is a Kubernetes pod?
What is a Kubernetes cluster?
Why use Kubernetes?
When to use Kubernetes
Use cases
Takeaways
At first glance, it may appear a little tricky to say. Phonetically, Kubernetes is pronounced as coo-ber-net-ees. You might sometimes see it referred to as K8s, which is pronounced kay-ates.
The name itself has Greek origins, and roughly translates to helmsman, sailing master, and/or pilot. As it’s a container management system, the name certainly represents what it does!
K8s is an abbreviation of Kubernetes. The 8 represents the eight letters between the K and the S.
Kubernetes is a container orchestration tool. It’s a system designed to manage multiple containers. Kubernetes automatically creates and scales containers, as well as oversees their storage.
So why is Kubernetes useful? Individual containers only perform a single function, so multiple containers are needed to run a lot of applications. In order to ensure all of these are running correctly, a container orchestration tool can be used. These tools automate operational and management tasks and generally manage the container lifecycle.
Kubernetes manages containers through a series of automated tasks. The system consists of:
Deployment tools. These are specialist, automated tools that perform tasks.
A centralised management system. This is called Kubernetes Master.
Access to multiple virtual and/or physical computing machines. These are called nodes.
The Kubernetes master, driven by the deployment tools, coordinates the rollout of containers to specific nodes. Basically, it organises what containers go where in order for them to do specific tasks.
Container images (which include everything containers need to run) are stored in Kubernetes’ centralised image registry. Whenever a new instance is required by an application, these container images are loaded from this storage repository.
It’s worth noting that if you only need one running container for your application, there’s probably not a compelling reason to use Kubernetes. Users usually only need a container orchestration tool if they have multiple running containers.
Kubernetes operates using clusters. These are selection nodes that run containerized applications. These nodes can either be virtual machines or physical machines (like a server). These nodes collate all of their shared resources together, which makes them pretty efficient. In each cluster, there’s at least one node.
Different Kubernetes systems can have different Kubernetes cluster set ups. They can use multiple nodes, which can be a mixture of virtual and physical machines.
A pod is the smallest unit that can be rolled out using Kubernetes. They’re an abstraction comprising a group of containers that share resources and that have a set way of operating. Containers operate inside of pods and pods execute on nodes.
Pods can be found in clusters. In these clusters, you’ll find replications of pods. This means that if your application is overwhelmed by traffic, duplicates of pods can be rolled out to keep the app running.
If you have multiple containers, having a container orchestration tool is a must. Kubernetes can help keep everything ticking, as well as perform certain functionalities. Let’s take a look at a few of these.
Kubernetes allows users to manage, scale up, scale down, and restart multiple containers. This removes the headache of manual container deployment, scaling, and management. This means users can build applications that use lots of different containers without having to manually manage them.
Kubernetes can automate workload rollouts. For instance, it can automate the creation of new containers, remove workloads that are no longer needed, and transfer these resources to the new container. Automation makes moving deployments between testing and production environments a whole lot easier. Automation also extends beyond workloads. Pods that are failing are automatically removed, which results in better performance and higher availability.
Kubernetes has the functionality to provision resources. For instance, you can dedicate a cluster to run a particular task, as well as stipulate the amount of resources they’ll have access to. This means that resources can be used more efficiently.
Kubernetes can store, manage, and update sensitive information, including secrets and application configuration requirements. It can do this without having to completely reconstruct your containers every time any of these change.
Kubernetes has dynamic storage functionalities that can scale. Kubernetes storage is based on volumes - either ephemeral (temporary) or persistent (long-term). Clusters can share and access these storage repositories. There is also the option to integrate external storage systems with Kubernetes, whether these are on-prem, in a private cloud, or in another computing environment.
If there’s too much network traffic to a container, workloads inside it can become less efficient and perform poorly. If this happens, Kubernetes can perform load balancing. This is a process via which traffic and workloads are distributed (balanced) across different computing resources. This means that no containerized workloads are overwhelmed by traffic. As mentioned previously, pods can help with load balancing too.
Kubernetes has self-healing capabilities. It can restart and replace containers that are failing. Users can also run health checks on the system, which can remove containers that don’t pass.
We’ve looked at what Kubernetes can do as well as touched on some benefits. Let's now look at some reasons why you’d want to use Kubernetes.
As we’ve discussed, Kubernetes automates the manual tasks required to deploy and scale containers. This can be particularly useful when it comes to navigating availability and performance. Kubernetes provides an additional layer of resilience. It automatically ensures that clusters, pods, and containers are stable, running efficiently, and scaling up and down when required.
This can be particularly useful for large applications which have a significant number of containers to manage. Keeping an eye on the life cycles of individual containers would be daunting. Kubernetes removes the need for this.
Kubernetes is a little like a restaurant manager. You need front of house staff to greet visitors and seat them quickly. You need servers to take the correct orders. You need bar staff to mix drinks correctly. And you need someone to ensure the kitchen is cooking the food correctly, and on time. Kubernetes ensures that all aspects of multiple containers are running efficiently.
In short, using Kubernetes results in an application that is:
More efficient
More stable
More future-proof
Kubernetes is often seen as cost-efficient, but only for large applications. This is due to its automated scaling functionality. A lot of Kubernetes tools are also open-source and so are free to use.
Kubernetes is most suitable for large and complex applications. As mentioned above, it’s not particularly useful for deployments involving a single container. It’s also worth noting that Kubernetes is supported by a number of large cloud vendors.
Let’s take a look at some use cases that Kubernetes could be used for.
Cloud migration for large scale applications.
Large scale applications that require high availability.
Large scale applications that need to be more efficient.
Large scale applications that require access to multiple resources.
Large scale applications that require scaling functionalities.
A container orchestration tool is fundamental to effectively using multiple containers in your application. Kubernetes is an option that provides scalability, resilience, and automation to elevate the burden of manually managing individual containers and their resources. It’s most suitable for large scale applications that have complex systems and multiple moving parts.
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