Before containers, running an app on a new machine could be a nightmare. That’s because apps often depended on specific software or configuration files. If those were missing or different on the new machine, the app wouldn’t work.
Docker changed this. It lets developers package the app with everything it needs so it runs the same in every environment.
Kubernetes came next. It helps teams run lots of containers at once and manage them at scale.
In this guide, we’ll explain Kubernetes vs Docker in simple terms, what they do, how they work together (or not), and how to decide what you actually need.
TL;DR: Differences Between Docker and Kubernetes You Need to Know
Docker is best suited for building, packaging, and running containers in local or single-node environments
Kubernetes is designed to orchestrate, scale, and manage containers across clusters in production
You can use Docker without Kubernetes (with Swarm), or Kubernetes without Docker (via containerd)
Most teams use Docker for development and Kubernetes for deployment to combine speed with scalability
What Is Docker?
Docker is a platform that helps developers run apps in a consistent way, no matter where they’re deployed.
It does this by using containers. A container is a lightweight package that holds everything an app needs (its code, settings, and supporting software). That way, the app behaves the same on your laptop, in testing, or during production.
Containers themselves aren’t new. They’ve existed for decades on systems like UNIX. But Docker made them easy to use.
With Docker, you can create a container using simple commands. You don’t have to worry about whether your system has the right version of Python or a missing library. Everything the app needs is already in the container.
Docker also made it easier to manage containers. Tools like the Docker Engine, Docker CLI, and Docker Compose allow you to build, run, and organize containers with only a few lines of code.
It also introduced a standard format for containers and made sharing easier through online libraries called registries.
Today, Docker uses a tool called containerd to run containers under the hood. This is the same core runtime used by Kubernetes and other platforms.
The big benefit?
You don’t have to manually install software, troubleshoot missing files, or set up separate environments. And unlike virtual machines, containers are lightweight—so they start quickly and use fewer resources.
How Does Docker Work?
Docker turns your app and its dependencies into a reusable package called an image. This Docker image is like a blueprint. It contains everything the app needs to run (its code, libraries, settings, and startup instructions).
These images are built in layers. Each instruction in your Dockerfile creates a new layer. These layers are cached, which makes future builds faster.
When you run an image, Docker creates a container. And when the container runs, Docker combines these layers into a single view so the app can access everything it needs as if it were one complete file system.
Here’s the difference:
The image is the packaged version of the app—ready to go, but not running.
The container is what you get when the image is running. It’s the live, isolated environment where the app actually executes.
Once Docker builds the image, it doesn’t change. If you need to make updates, you create a new version of the image.
In newer versions, Docker uses a tool called containerd to manage containers at the backend. This tool is also used by Kubernetes, which is why Kubernetes no longer needs the full Docker platform to run containers.
So, in simple terms:
You write a Dockerfile.
Docker builds an image from it.
You run the image to create a lightweight, reliable container.
Docker Architecture
Docker uses a client-server architecture. This setup includes a few key components that work together to build, run, and manage containers.
Docker Daemon
The Docker daemon is the background process that runs on your machine. It does the heavy lifting for Docker: building images, running containers, and managing them.
The daemon listens for commands from the Docker client. It also keeps track of containers, handles storage, and makes sure things don’t conflict (like two containers trying to use the same name or port).
Docker Client
The Docker client is the tool you use to interact with Docker. Every time you type a command like docker build or docker run, you’re talking to the client.
The client sends your instructions to the Docker daemon, which carries them out. You can run the client from your own machine or from another computer.
Docker Command Line Interface
The Docker Command Line Interface (CLI) is part of the client. It’s a text-based tool where you type commands to build images, start containers, and check their status.
Some common commands are:
docker build (to build an image)
docker run (to start a container)
docker ps (to list running containers)
Docker Compose
Docker Compose runs apps with multiple containers.
Let’s say your app uses a web server, a database, and a caching layer. Instead of starting each container one by one, you can use Compose to start them all at once with only one command.
To do so, you have to write your app setup in a simple YAML file. Docker reads that file and sets up all the containers as described.
Docker Engine REST API
The Docker Engine REST API lets other systems interact with Docker. It provides a standard way to send instructions over the web using JSON and HTTP.
This is quite helpful when you want to automate Docker tasks or connect Docker with other tools.
Docker Machine
Docker Machine was used to set up Docker on virtual machines, especially on cloud providers or across different operating systems.
It helped users create Docker-ready VMs without doing it manually. But today, most developers use other tools (like Docker Desktop or Kubernetes) instead.
Docker Advantages: Why It’s Worth Using
You now know Docker took a messy, inconsistent deployment process and made it fast. So, here’s a quick summary of its key advantages for developers:
Advantage
What it means
Portabaility
Run containers the same way across dev, test, and production.
Speed
Containers start fast and use fewer resources than VMs.
Isolation
One container crash won’t affect others.
Easy Tooling
Use simple commands to build, run, and share containers.
Built-in Security
Default safeguards help reduce system risk.
What Is Kubernetes?
Kubernetes is an open-source system that helps you run and manage containers across multiple machines.
It handles the hard parts automatically, such as deciding where each container should run, keeping them healthy, and restarting them if something goes wrong.
This process is called container orchestration.
Instead of starting containers manually or tracking which server has space, Kubernetes does it for you. It can also scale your app by running more containers when traffic increases and shutting them down when they’re no longer needed.
Kubernetes was originally created by Google.
Today, it’s the most widely used tool for running container-based applications in production whether you’re using cloud servers, your own data center, or both.
How Does Kubernetes Work?
When you deploy an app to Kubernetes, it chooses the best machine to run it on based on available resources. Then it monitors the container to make sure it stays healthy.
If a container crashes, Kubernetes restarts it automatically. If more traffic comes in, it can start more containers to handle the load. If traffic drops, it can scale things back down.
Kubernetes constantly compares what you want running (your “desired state”) with what’s actually running. If there’s a difference, it fixes it.
Now, Kubernetes doesn’t need the full Docker platform to manage containers. Instead, it uses container runtimes like containerd, which is also used by Docker. That means you can still run Docker-built containers, but Kubernetes manages them directly.
Think of Kubernetes as an autopilot for your container infrastructure. It keeps things running, balances the load, and corrects issues in real time so your team can focus on building instead of babysitting servers.
Kubernetes Architecture
Kubernetes has two main parts: the control plane and the worker nodes.
The control plane manages the system and decides what should run where. The worker nodes are the machines where your containers actually run. Together, these components make up a scalable, self-healing system for running containerized apps.
Control Plane (Central Brain)
The control plane is in charge of the entire cluster. It decides where to place containers, monitors their status, and makes changes if something isn’t working as expected.
It includes several parts:
API Server is how you interact with Kubernetes. When you send a command like creating a new container, it goes through the API server.
etcd is a key-value database that stores everything Kubernetes needs to remember: configurations, state, and cluster data. It acts as the system’s memory.
Scheduler decides which machine (or node) should run each new container. It looks at available resources and rules you’ve defined.
Controller Manager monitors for changes and takes action. If a container stops running, it restarts it. If you ask for three copies of something, it makes sure three are running.
Cloud Controller Manager(optional) connects Kubernetes with your cloud provider. It handles cloud-specific features such as load balancers or storage.
Worker Nodes (Where Containers Run)
Worker nodes run your actual apps inside containers.
Each node includes:
Kubelet is a local agent that interacts with the control plane. It checks that containers on its machine are running as expected.
Kube-proxy handles network traffic. It makes sure requests get to the right container whether it’s on the same machine or another one in the cluster.
Container Runtime is the tool that runs the containers. Kubernetes supports different runtimes, like containerd, CRI-O, and Docker (though Docker itself is no longer required).
Kubernetes Advantages: Why Choose Kubernetes for Container Management
Here’s a quick look at why teams rely on Kubernetes in production:
Advantage
What it means
Automated Scaling
Adds or removes containers based on real-time demand.
Self-Healing
Restarts or reschedules containers if something fails.
Consistent Deployments
Uses YAML configs to ensure reliable, repeatable releases.
Resource Efficiency
Schedules containers to optimize CPU and memory use.
Built-in Security
Supports isolation, secrets, and access control by default.
Multi-Cloud Flexibility
Run Kubernetes anywhere—cloud, hybrid, or on-prem—without changes.
Docker vs Kubernetes: Side-by-Side Comparison
Docker and Kubernetes often get lumped together, but they serve different purposes in the container lifecycle. Here’s how they compare:
Feature
Docker
Kubernetes
What it does
Builds and runs containers
Orchestrates and manages containers at scale
Primary use case
Local development and packaging
Deploying and scaling containerized apps in production
Uses containerd, CRI-O, or other CRI-compatible runtimes
Best for
Building, testing, and sharing containers
Managing production-grade workloads across environments
Choosing Docker, Kubernetes, or Both: What Works and Why
Not every project needs Kubernetes. And Docker alone doesn’t always scale. So how do you choose between them, or know when to use both? Let’s understand this:
Use Docker when you’re building and testing locally.
Docker is ideal for building, testing, and running containers on a single machine. If you’re working on a local environment, running automated tests, or packaging an app, Docker is lightweight, fast, and easy to use.
Use Kubernetes when you need to scale or manage production workloads.
Kubernetes is suitable for production. It helps when your app needs to run across many servers, stay online 24/7, and recover quickly if something fails. It handles the hard parts: orchestration, scaling, monitoring, and self-healing.
Use both when you’re moving from dev to prod.
Most teams use Docker and Kubernetes together. Here’s how you can too:
Use Docker to build your containers
Push them to a container registry
Use Kubernetes to deploy and manage them in staging or production
This workflow gives you consistency from local development to live environments.
Can I Use One Without the Other?
Yes, and depending on your team size, infrastructure, and goals, it might even make sense.
Docker Without Kubernetes (Swarm)
If Kubernetes feels like overkill, Docker Swarm is a simpler alternative for orchestrating containers. It’s built into the Docker CLI and works well for smaller teams or staging environments.
Why some teams still use Swarm:
Quick setup: You can form a basic cluster in minutes.
Familiar tooling: Uses the same Docker CLI and image format.
Good enough scaling: Supports service discovery, load balancing, and rolling updates.
However, Swarm lacks the flexibility, ecosystem, and multi-cloud support Kubernetes provides. That’s why it’s less common in production today.
Does Kubernetes Use Docker? Kubernetes Without Docker (containerd)
As of Kubernetes v1.20, Kubernetes no longer uses Docker as its default runtime. Instead, it uses container runtimes like containerd or CRI-O. These are lighter and more efficient.
Here’s what this means:
You can still build containers with Docker
Kubernetes just doesn’t need the Docker Engine to run them
Your Docker-built images still work the same way
Kubernetes and Docker now work side by side without Kubernetes depending on the full Docker platform.
Take Control of Your Container Stack
Docker and Kubernetes aren’t competitors. They solve different but complementary problems in the container lifecycle.
Docker helps you build containers quickly. Kubernetes helps you run them reliably at scale.
Knowing when to use each (or both) gives you the control and consistency your infrastructure needs. But building and scaling aren’t enough without visibility. Once containers are live, you need to spot issues early and resolve them fast.
That’s where LogicMonitor comes in. It unifies observability across your containerized environments so your team can stay focused on delivering reliable services.
