Forget Kubernetes vs Docker: What You Must Know Instead

Containers are fast and lightweight because they run directly on the host machine’s kernel, without the overhead of a hypervisor like virtual machines require. These containers include everything your app needs: code, runtime, libraries and dependencies.

It offers a consistent runtime, so your app runs the same across development, test, and production – regardless of the system or environment.

How does Docker work? 

Docker is the foundation for building and running containerised applications. It packages your app and everything around it into a container. Within Docker’s architecture (see below), the Docker client tells the daemon what to do by running commands (build, pull, run). 

The Docker daemon pulls images from a registry (right side of the diagram). Registries like Docker Hub store reusable images (like Ubuntu). Once the daemon has the image, it creates a container from it.

In short:  
Client commands → Docker daemon → pulls image → creates containers → runs your app. 

That’s where Kubernetes comes in, which we’ll get into next… 

What is Kubernetes? 

So, what is Kubernetes exactly? Let’s make it not harder than it has to be: 

Kubernetes (K8S) is an open-source platform for automating, managing, and scaling containerised applications.

Its flexibility and ability to handle large-scale workloads has made it become the standard for container orchestration today. It handles scaling, load balancing, and even self-healing.

How does Kubernetes work?

Once you have containers, Kubernetes manages them across multiple machines. The Kubernetes cluster groups containers supporting microservices or single applications into pods, which run on nodes.

• Pods: Pods are the smalles unit in Kubernetes and share the same network and storage, which makes it ideal for tightly coupled apps that need to communicate.  
• Nodes: Nodes are worker machines (like virtual machines) that host pods. 

Apps running in Kubernetes act like a single unit, although they may consist of loosely paired containers.

In Kubernetes, a deployment manages your app's desired state. It defines how many pod replicas should run and maintains this number.

YAML

apiVersion: apps/v1
kind: Deployment
metadata:
  name: my-deployment
spec:
  replicas: 3
  selector:
    matchLabels:
      app: myapp
  template:
    metadata:
      labels:
        app: myapp
    spec:
      containers:
        - name: myapp-container
          image: myapp:1.0

Kubernetes Deployment YAML

Deployments handle stateless workloads and support declarative updates, making it easy to roll out changes or scale your app. Behind the scenes, the deployment uses a replica set to keep the correct number of pods running. If a pod crashes or is deleted, the replica set automatically replaces it. 

As a developer, you define the desired state in a deployment. The deployment controller then matches the actual state you’ve described. 

It does this using a control loop. The controller constantly checks the cluster’s current state via the API server, and if something’s off, it makes the necessary changes to bring the system back in line with the desired state.

Kubernetes also automatically balances network traffic across pods, making sure no single container is overloaded with requests. Moreover, it automatically scales pods based on traffic load: Learn more about scaling the cloud native way on Kubernetes.

Docker’s role in Kubernetes 

While Docker used to be the default container runtime for Kubernetes, it now has supported other runtimes through the Container Runtime Interface (CRI), like containerd and CRI-O for a while now. 

This shift began with the deprecation of Dockershim in Kubernetes v1.20 and its removal in v1.24, allowing Kubernetes to streamline its architecture and improve performance. 

Although Docker is still widely used for building and managing containers, Kubernetes no longer relies on it directly to run containers.

Use Cases for Docker and Kubernetes 

Now that you know the basics of how Docker and Kubernetes work, let’s break down the use cases for both: 

What Docker is Used For 

• Proxying requests to and from containers 
• Managing container lifecycle 
• Monitoring and logging container activity 
• Mounting shared directories 
• Putting resource limits on containers 
• Building images using the Dockerfile format 
• Pushing and pulling images from registries 

What Kubernetes is used for 

So, what is Kubernetes used for? Let us break it down: 

• Auto-scaling: Automatically adapts to task demands 
• Rollouts: Supports automated rollouts and rollbacks 
• Pods: Logical groups of containers sharing memory, CPU, storage, and network 
• Self-healing: Restarts containers if they break down 
• Load balancing: Allocates requests to available pods 
• Storage orchestration: Mounts network storage systems as local file systems 
• Configuration management and secrets: Stores sensitive information in a secure module called "Secrets"

What is the difference between Kubernetes and Docker?

Let’s explore how they compare against each other because that’s why you came here. 

There’s a bit of an overlap between them: both allow you to run containers.

One difference is that:

• Docker is used to pack and ship your application
• Kubernetes is used to deploy and scale applications

However, the biggest difference is in scaling. If you want to run four containers on your local computer that don’t have complex needs, Docker run is probably fine.

But if you want to run 20,000 containers across 500 servers in three different data centres, you will need an orchestrator. 

One may argue that you can run Docker containers without Kubernetes. However, Kubernetes is essential for large-scale distributed systems. 

To clarify the differences even further, we’ve compiled a comparison table that breaks down the differences between them: 

Kubernetes vs Docker Comparison Table

Kubernetes or Docker: Which one is right for you? 

When to choose Docker 

Docker can be great choice for single-container apps or local development environments with tools like Docker Compose. It doesn’t have the orchestration power of Kubernetes, of course, but it’s great for spinning up multi-container environments locally, especially in development.  

Docker is mostly involved during the development and testing phase of an application. Examples include: 

• Creating consistent development environments. 
• When developing a microservice on your local machine, you can run the service and its dependencies like a database or cache in their own containers. 
• Also super useful in CI/CD pipelines, where you get consistent builds and testing across different environments. 

But it falls short if you want to build scalable, complex, distributed apps. This is because it cannot hold multiple containers spread across many servers. 

Example: if you want to run, let’s say, 20000 containers across 500 servers, you need an orchestration platform like Kubernetes.

When to choose Kubernetes 

Kubernetes comes into play when you deploy an application to production or other environments. 

Kubernetes is super useful when you want to: 

• Deploy multiple microservices with high availability 
• Manage data stores with strong durability guarantees 
• Run big data workloads like Apache Spark 
• Or even run something smaller like cron jobs 
• Why use Docker and Kubernetes together 

In the end, the ultimate question is: “Why use Docker and Kubernetes together?”.  

The answer = when you need to manage and scale many containers, Docker alone won’t be sufficient. These two technologies were created to work together: 

• Docker runs the containers 
• Kubernetes handles the orchestration, ensuring those apps run reliably at scale 

Together, they are essential for production environments where automated scaling, failover and management across multiple machines are required.  

Now let’s look at a simple workflow of Docker and Kubernetes: 

1. Developers use Docker to package the application into a container, including all dependencies 
2. The Docker image is pushed to a container registry  
3. Kubernetes pulls the image from the registry and deploys it as a pod 
4. Then Kubernetes will monitor the traffic and scale the pods horizontally, adding more containers as needed 
5. It will also ensure the incoming traffic is routed to healthy containers 
6. And if any container crashes, Kubernetes automatically restarts it to ensure that the desired number of replicas is running 

Closing thoughts 

We’ve discussed Kubernetes and Docker and how choosing between one or the other is often not necessary since they serve different purposes. Instead of choosing one, they can go hand-in-hand, enabling you to create a powerhouse of infrastructure. 

Combining Kubernetes and Docker ensures a well-integrated platform for container deployment, management, and orchestration at scale. Together, they’re the backbone of modern cloud-native applications.