Kubernetes vs. Docker: Understanding the Differences

What Is Kubernetes (K8s) and Where Is It Being Used?

It’s a term that might feel overwhelming just from its definition. But don’t you worry; in this blog post, we’re going to explore everything you should know about this—what it is, how it is being used, and what you can do with it

What Is Kubernetes (K8s)?

To get started, let’s look at the definition. According to its definition:

“It is an orchestrated containerized cloud-native microservices application.

While this might be a perfect definition, it makes very little sense at first glance. So let’s break it down and approach it from a practical standpoint. By the end of this blog, you’ll understand the definition and its significance.

Time to move on to it. K8s is a powerful tool that groups containers supporting microservices or single applications into a pod. The apps running in K8s act as a single unit, although they may consist of several loosely paired containers. It runs over multiple computers or nodes, and the collection of nodes is called a Kubernetes cluster. It’s a powerful tool that groups containers supporting microservices or single applications into a pod. The apps running in K8s act as a single unit, although they may consist of several loosely paired containers. It runs over multiple computers or nodes, and the collection of nodes is called a Kubernetes cluster.

Its Features

Auto-scaling: Adapts automatically to changing tasks.
Rollouts and Rollbacks: Supports automated rollouts and rollbacks.
Pods: Logical groups of containers sharing resources like memory, CPU, storage, and network.
Self-healing: Monitors and restarts containers if they break down.
Load Balancing: Allocates requests to available pods.
Storage Orchestration: Allows users to mount the network storage system as a local file system.
Configuration Management and Secrets: Keeps classified information under a module named Secrets.

Applications and Microservices

Web applications have evolved significantly. In the past, we used to pack everything into a monolith application and deploy it on servers. Today, things have shifted to microservices—where each part of the application is built independently by specialized teams.

What is Docker?

Docker is an ecosystem where you can create containers and run them. But then, why do we need it? We can talk about Docker in detail, but the main question is: why do we need Dockers?

Think about this: as a developer, tester, or operations team member, the ultimate goal is to provide software that your users can use. I’m talking about web applications or web services. Normally, the development team builds a software application, which then goes to the testing team for testing. If everything is fine, it moves to the operations team for deployment on a production server. Of course, depending on the company, this process might vary, but the main steps remain: build the application, test it, and ship it to production

Docker and Its Ecosystem-

Docker uses images to create containers. For instance, you can create a container with your application, dependencies, and frameworks as a developer. This container is then packaged into an image shared with the testing or production teams. They can use this image to create multiple instances, ensuring consistency across environments, Docker also provides a public repository, Docker Hub, where you can find pre-built images for various applications and frameworks, such as Redis, Node.js, or Windows.

Benefits of Docker-

Lightweight: By simply sharing the OS kernel, containers save resources
Consistency: Applications behave the same across development, testing, and production environments.
Reusability: Developers can create images once and use them repeatedly.
Flexibility: Docker allows you to build and share custom containers tailored to your needs.

I always seem to be running into whether or not you should use Docker vs. Kubernetes. I think there’s a small misconception out there: You have to use one or the other. However, the truth is that K8s lets you use your current Docker which containers & workloads while addressing some of the complexity problems that arise while scaling.

Let’s begin with the basic cloud-native application that has been sketched out & here to properly answer this topic. Let’s simply assume that we are used to React with Node.js to create the application’s front end. J.S. We will say that this database access app. — I’m fond of using Java for database access. so, we will say Java up here. In Addition, we may utilize Flask & a Python program that enables us to provide REST endpoints, to contact external APIs.

Docker Deployment

So, considering my role as a Docker operations engineer (hell yeah) and deploying an application that only employs Docker, we’re going to take this application and go to a sample server. , stack that we have illustrated here. On every server stack, you’re going to have the basics, right? So, we will have the hardware. We will have the OS, which is generally going to be Ubuntu when you are working with the Docker. We will have the Docker daemon installed on that OS – that is what allows us to spin up great containers.

Docker provides us with several advanced tools for working with our containerized apps. After creating fresh Docker containers from the apps we created then we will perform Docker build and Docker push-up to a registry. We can then SSH into our stack and execute Docker “run” commands or even spin up our containers using the Docker platform Compose.

Let’s now examine what it would entail. Our team of Python applications, our Java application, and our.js application are all available. And let’s scale out each of these components as well to maximize the most of what we have at our fingertips ..So, we’ll scale them out. To make perfectly efficient use of all the resources at our disposal &, let’s assume that we scale them out twice for the time being, but we are free to repeat this as many as we want.

Kubernetes vs Docker: Statistics

Whether you use Kubernetes or Docker, here are some compelling statistics to watch in 2025:

In global surveys, K8s is used by more than 60% of companies and 96% of enterprises. 53% of developers use Docker in their workflows, making it one of the most popular tools among developers today.

According to daily activity, more than 10 million container images are pulled from Docker Hub every day. For enterprise-level applications, K8s is generally preferred by Fortune 500 companies that have already integrated it into their operations.

Globally, the K8s market is forecast to reach USD 7.8 billion by 2030, growing at a CAGR of 23.40% between 2022 and 2030. Globally, 56 million developers are already using K8s, and 31% are using it for backend development. With an impressive market share of 83.18%, Docker has over 55,887 customers in the containerization space.

Source: Kubernetes vs Docker: Statistics

Docker vs. Kubernetes Comparison

Now that you know what Docker and Kubernetes are, it’s safe to say these two different technologies were created to work together. In light of that, here are the following distinctions exist:

Docker is used for packing and shipping your application.
K8s is used to deploy and scale applications.
Docker operates on a single node, however K8s was designed to run across a cluster.
Without K8s, Docker may be relied on independently. Although Kubernetes and Docker are different technologies, bringing them together ensures a well-integrated platform for container deployment, management, and orchestration at scale.

Scaling

Therefore, a straightforward deployment is rather simple when utilizing Docker & the tools that Docker provides. But let us imagine that our application starts to get tons of load — a good number of people are hitting it, and we realize now we need to stretch out to provide a better user experience which inhance the quality.

As an engineer, my first instinct might be “Hey, I have already got scripts to make this stack(which is great), let us just easily get brand new hardware and Perform the same deployment several times. When you start scaling, this might go wrong for some different kinds of reasons. For ex., what if a team of Development has to develop a new microservice to support a new requirement? Where do we piece those in, if you already have that effective use of hardware? The Operations engineer would have to surely find that out.

The ability to scale out individual components is a significant benefit of microservice-based solutions.y. So that’s another thing the Operations engineer would have to write scripts for and find the most effective way to scale things out in response to load to identify and highlight user experience problems when moving to a broad scale.

Orchestration

So, this is how an orchestration tool comes in. Something like K8s, which is going to use your already existing Dockerized apps but orchestrate them and make them much more effective use of your space and server.

What we have sketched out down here is several boxes representing a server stack; but in the K8s land, we call them worker nodes. We are going to have K8s installed on each one of these worker nodes, and the best one is going to be the master node (whereas the others are workers). This master node is perfectly connected to every worker node and decides where to host our applications (our Docker containers), how to piece them together, and even manages to orchestrate them starting, stopping, updating, that type of thing.

Deployment

I’d say there are 3 major advantages that K8s provides that I want to walk through: deployment, making development easier, and providing monitoring tools.

The 1st step, as expected, is going to be deployment. Coming back to our application architecture — let’s say we want to deploy that React application about 8 times. We’ll say we want 8 instances. Every one of them, let’s say, we expect to consume about 128 MB. Then, we can specify a few other policies and parameters in there as well, when to restart, that kind of thing. When we finally box that up, what we get is a K8s deployment.

A K8s deployment is not a one-time thing, but it’s something that grows, lives, and breathes with the application and our full stack. For example, if the React application happens to crash, K8s will automatically restart it to get back to the state we identified when we first created that deployment. Our application is constantly expanding and living in deployment mode. Therefore, I believe we can argue that it has made both scalability and deployment much easier.

Development

We have several different microservices with multiple endpoints once we have developed the installation processes for each of these separate services and scaled them all out, just in case those of you were wondering. For example, if our front end needs to access the database, there might be 8 different versions of that Java application that talk to that database. We have to talk to one of them to get our request fulfilled, right?

So, what K8s does is deploy all the load balancers for all of our microservices so that we can scale out. In addition, it takes advantage of service registry and discovery capabilities to allow our applications to talk to each other using something called a K8s service. K8s will also generate the service name for each of them in their final days which we can just call “Service to Others A,” “B,” and “C.” Of course, you can additionally provide those more significant names. Quite simply, these apps can communicate with each other by simply using the service names that are specially laid out in K8s. So, happily, I can say that K8s have made development much easier.

Monitoring

Finally, I would want to discuss monitoring. Many built-in features in K8s let you view logs and CPU load in a clean user interface. But sometimes, there is more you want to see with your application. The open-source community out there has developed several amazing tools to give you introspection into your running application. The top one I am thinking about is Istio and although that is a bit more of an adv. topic, we will likely see that in a future whiteboarding session.

Conclusion

So, back to our main topic is using. Docker vs Kubernetes. It’s one of those things where K8s allows you to take advantage of your existing Docker workloads and run them at scale — tackling real complexities. K8s is best to get started with, even if you’re creating a small application if you anticipate that one day you’ll have to move to scale up. If you’re already taking advantage of Docker and containers with your applications, moving them onto K8s can help you tackle some of the operations overhead that essentially every application is going to face when expanding.

 

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