Kubernetes vs Docker: Know Their Major Differences!

Keeping up with new technologies is more critical than ever for companies, which means that DevOps Engineers are highly sought after—and well-compensated. According to ZipRecruiter, the average salary for a DevOps Engineer in the U.S. is more than $130,000 a year, with some DevOps specialists earning up to $178,000. 

For DevOps Engineers, keeping up with all the tools surrounding new technologies is more important than ever. Two essential tools these days are Kubernetes and Docker, which are used to get the software to run reliably when it needs to be moved from one computing environment to another—say, from a testing environment into an actual production environment, or an on-premises computer to the cloud. These environments might not be the same, which can cause issues in how the software runs. That’s where containers, and Kubernetes and Docker, come in, and in this article, we will understand the difference between Kubernetes and Docker.

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What is a Container?

A container encompasses an entire runtime environment. It’s a bundle that includes not the application but the associated dependencies, libraries, and other configuration files. Containerization is an evolution of virtualization, and containers have several advantages over virtual machines—for example, they are more efficient, using far fewer resources than virtual machines. They’re also lightweight, so one server can host many more containers than virtual machines.

If you’re in the field of information technology and considering container platforms (and who isn’t these days?), you’ll undoubtedly come across the Kubernetes vs Docker debate or a variation of the question “Is Kubernetes better than Docker?” But those are misleading because although Kubernetes and Docker are both highly popular container-related solutions, they aren’t used for the same things and aren’t in competition. They’re often used together. Let’s dive in.

What is Kubernetes?

Kubernetes is an open-source container management tool, also called a container orchestration tool. It’s used for things like automating container deployment and scaling and descaling containers. It is not a containerization platform but rather a tool used on a containerization platform. Why would you even need a content management tool? Well, consider that you’re probably not going to be working with just one or two containers. More likely, you’ll have dozens or hundreds of them—and you’ll need some way to manage them. That’s where Kubernetes comes in. This tool, introduced by Google in 2014 and widely considered the most popular of its type right now, is offered on many public clouds—perhaps most notably on Amazon Web Services (AWS). 

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What is Docker?

So you want to use Kubernetes to automate and scale all of your container scheduling and deployment instead of having to script each task individually, thus saving you a huge amount of work and stress. Now you’ll need a platform to package up your application with its dependencies—that is, create the containers that Kubernetes will automate. That’s where Docker comes in, as Docker is a containerization platform. It’s open-source (like Kubernetes), and the technology has taken off since Docker, Inc. introduced it in 2013. Lyft, Uber, eBay, and PayPal are just a few of the companies that use Docker, according to Contino.

So, as you can see, the debate about Kubernetes vs Docker is intrinsically invalid, because these solutions aren’t comparable. However, there is a Docker version of a container management tool called Docker Swarm that is comparable to Kubernetes so that we can discuss Kubernetes vs Docker Swarm.

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Kubernetes vs Docker Swarm

Both Kubernetes and Docker Swarm are open-source container orchestration tools—meaning we’re now comparing apples to apples instead of apples too, say, apple trees—and both are major players in the container ecosystem. But they have some fundamental differences in how they’re set up and how they operate. Before we discuss the ins and outs of Kubernetes vs Docker Swarm, you should know that Docker Swarm, often just called Swarm, is the native clustering engine by and for the Docker platform. Because Docker Swarm can turn a group of hosts into a single virtual host, it’s especially handy if you want to keep deployment simple. Kubernetes, on the other hand, are generally considered more complicated (but it can also meet more complex/higher demands).

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Here’s a basic breakdown of the significant differences between Kubernetes vs Docker Swarm.

  • Concept

    Kubernetes utilizes pods as its basic scheduling unit. A pod is composed of one or multiple containers that are located on the host machine and share resources. Docker Swarm uses clusters. A cluster is a group of machines running Docker that are joined together.
  • Installation

    Simple for Docker Swarm; complicated for Kubernetes. And setting up clusters in Swam requires just two commands, whereas setting up pods in Kubernetes requires several steps.
  • Container Setup

    Swarm offers a lot of functionality familiar from Docker, but its application programming interface (API) doesn’t entirely encompass all the Docker commands. With Kubernetes, you can’t use Docker Compose or Docker CLI to define containers, because Kubernetes uses its YAML (that is, language), API, and client definitions. 
  • Graphical User Interface (GUI)

    Docker Swarm has no GUI at all(!); Kubernetes utilizes a simple-English dashboard for ease of use.

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  • Networking

    In Kubernetes, all the pods interact on a flat network, usually implemented as an overlay. Docker Swarm uses Linux tools to virtualize multi-host overlay networks.
  • Scalability and Autoscaling

    Here, it comes down to whether speed or stability is more relevant to you. Both are highly scalable, but Docker Swarm is much faster because Kubernetes is slowed down due to the way it firmly guarantees the cluster state. And Docker Swarm can’t do autoscaling, while Kubernetes can. 
  • Load Balancing

    To load-balance traffic between containers in different pods or clusters, you’ll sometimes need to manually configure settings with Kubernetes. Docker Swarm does automatic load balancing as long as all the nodes are connected to the group, which is a lot easier than doing a manual intervention.
  • Rolling Updates and Rollbacks

    Both tools support rolling (that is, gradual and progressive) updates. But in the event of a failure, Docker Swarm doesn’t do an auto rollback to the previous working deployment, while Kubernetes does.
  • Logging and Monitoring

    Kubernetes has built-in tools for this, while with Swarm, you’ll have brought in a third-party tool such as ELK. 

So what’s the verdict in the Kubernetes vs Docker debate? The answer, as you’ve probably guessed by now, is that it depends on your specific needs and skill set. If you’re a beginner to containerization and your needs are minimal, it’s hard to beat the simplicity of Swarm. But if you’re more experienced, if your containers are going to be highly complex, if you may need to utilize rollback quite a bit, or if stability is a high priority, Kubernetes is the way to go.

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Are you interested in learning more about Docker or Kubernetes? Sign up for Simplilearn’s Docker Certified Associate (DCA) Certification Training Course or Certified Kubernetes Administrator (CKA) Certification Training. And if you want to become an expert and advance your career in DevOps, consider the DevOps Certification Training course

Simplilearn's DevOps Engineer Masters Program and the Post Graduate Program in DevOps in collaboration with Caltech CTME helps you develop the vital skills required to become a DevOps Expert. You will master configuration management, continuous integration and continuous deployment, continuous delivery, and continuous monitoring using DevOps tools such as Git, Docker, Chef, Jenkins, Puppet, and Nagios in a practical, hands-on, and interactive approach.

About the Author

Shivam AroraShivam Arora

Shivam Arora is a Senior Product Manager at Simplilearn. Passionate about driving product growth, Shivam has managed key AI and IOT based products across different business functions. He has 6+ years of product experience with a Masters in Marketing and Business Analytics.

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