It’s impossible to learn about containerization without hearing about Docker and Kubernetes. These two tools together dominate the world of containers, both being the de facto standard in what they each do. When you’re first getting started learning about containers, it can be quite a challenge to figure out the differences between these two tools.
Many developers believe that Docker and Kubernetes are alternative methods to run containers, and that the biggest difference is in how they approached the issue of spinning up containers. This is actually a core misunderstanding of these technologies – Docker and Kubernetes are not competing technologies, and in fact are more often than not complementary due to the very different ways in which they work.
In this article you’ll get to learn about these differences in form and function. You’ll get an understanding of what each tool can accomplish separately, as well as how they complement each other in a production scenario. In the end, you’ll also get a short introduction to some alternatives, giving you a comprehensive look into the space these two tools live in.
What is Docker?
Docker is a tool to package and distribute applications. Using a Dockerfile, you build an image from which you can spin up a container.
A container is, roughly put, a very lightweight Virtual Machine (VM). There are some key reasons why a container isn’t actually a VM in practice, one of which is the clever way that docker containers use the host OS kernel directly, whereas a traditional VM would spin up an entirely virtualized machine with its own kernel – for the purposes of the layperson, however, a VM is an ok way to think of docker containers. Docker containers only use the exact amount of resources they need, and they add very little overhead when running.
While Docker allows you to run images that are based on regular OS’s like Ubuntu, in effect allowing you to run a full Linux server (or a personal Linux installation) in a container, that is rarely how it’s used.
To be clear, there’s nothing stopping you from using a container as a full Linux server. It’s definitely possible, to an extent. You can spin up an Ubuntu container by executing docker run -it ubuntu bash, and after about a minute you’ll have a running shell on an Ubuntu system. You’ll find that it’s a very limited Ubuntu installation. However, you can just install all the tools you need for yourself. But it’s a limited Ubuntu installation for a reason.
Generally, Docker is used to run applications using as few resources as possible. The more applications you have, and the more instances of your applications you have, the more important it becomes to have small images, as they are faster to spin up new containers. This is an essential feature to have when you want to orchestrate your docker containers. Orchestration is the functionality you’re getting from using Kubernetes.
What is Kubernetes
Once you’ve got your applications containerized, you need to run them somewhere, and there are many ways of doing this. You can use a simple turnkey solution like Azure App Service or Google App Engine. These services allow you to spin up a service in a cloud provider based on a Docker image, which will quickly give you a running application in the cloud with its own IP.
This isn’t the perfect solution for everyone however. Usually, this approach is mainly preferred by small-scale companies like startups. These services lets you get started quickly and without the need for an abundance of technical knowledge, but it has its drawbacks. Once you get to the point of growth where you need to hire dedicated infrastructure or DevOps engineers, you need a more structured approach to running your applications. This is where orchestration comes into play.
Orchestration means to take care of running your applications in the most optimal way possible. Using a good orchestrator, you simply declare how you want your applications to be run, and the orchestrator will handle all the under-the-hood mechanics of getting the containers to run the way you want them to.
For example, imagine that you have a webshop. Using containers, it’s very uncommon that you would only have a single instance of your webshop frontend running. Perhaps your webshop has grown quite big, and you want to run ten or 100 instances of your application. In this case, you would just tell Kubernetes to spin up the number of services you want, and it will make sure to create that amount of healthy instances. If an application suddenly fails, Kubernetes will know and kill it, immediately spinning up a new instance, hoping it was an ephemeral error.
This is a very simple overview of how Kubernetes works. A detailed overview of Kubernetes would cover multiple articles, as it also has support for a ton of other features way more complex, like autoscaling, controlling ingress, and running jobs on an interval.
How is Kubernetes Different from Docker?
As mentioned in the introduction, these two tools aren’t meant to be substitutions of each other, as they don’t have the same functionality. Because of this, it’s difficult to compare the two tools as it’s like comparing apples and oranges. They look the same, many will even put them in the same category, however they serve distinct purposes. You wouldn’t use an orange in an apple pie after all.
It’s exactly the same with Docker and Kubernetes. To the uninformed, they look to be exactly the same. They’re definitely in the same category, so it’s easy to be confused. However, you don’t want to use Docker when you should’ve used Kubernetes, as well as the other way around.
7 Key Differences
Docker and Kubernetes are two solutions that are complimentary, and as such, it helps to understand in what ways they are difference.
1 – Building vs. Managing
Docker
Docker is best thought of as a method for building solutions. Through container images, the Docker engine allows for the creation of containers that can execute specific functions and purposes. Multiple containers may exist in a structure, and these containers are all built for a specific form and function. One or more containers might exist in isolation, but they might also leverage the same libraries – nevertheless, these resources are self-contained within each container, and Docker operates as if each container is an isolated and complete solution.
Kubernetes
Kubernetes, on the other hand, is best thought of as a method for managing solutions. Once a Docker build is specified and built, those containerized applications need an orchestration platform in order to function properly. Managing containerized applications is not a core part of Docker itself (which we will discuss briefly) – for this reason, the Docker platform needs to connect with a solution to oversee the deployment process, to properly scale containerized applications, and to manage the numerous container runtimes, compute resources, and other process inherent in Docker use.
2 – Scope of Management
Docker
Docker deals with single-node container management, focusing on a limited scope of management. Docker Engine runs and manages containers on a single machine but can be distributed in some specific use cases. Docker is much more concerned with creating the container and deploying it simply.
Kubernetes
Kubernetes operates at a multi-node, cluster level, managing containerized applications across a cluster of machines. It is more concerned with managing many containers rather than a handful and focuses on availability, scaling, reliability, and overall orchestration.
3 – Orchestration
Docker
Docker Swarm (an optional feature of Docker) provides basic orchestration capabilities, allowing you to manage many containers. When distributing containerized applications, this is often good enough for more basic deployments using lightweight containers or simple flows, but when you need something a bit more advanced, Docker quickly runs out of headroom in terms of features.
Kubernetes
Since Kubernetes specializes in orchestration, it should not be surprising that it offers advanced features, including scheduling, service discovery, load balancing, self-healing, and much more. The core value offering here is that Kubernetes automates the management of a container collection from end to end – with this comes complexity, yes, but also incredible power.
4 – Networking
Docker
Docker handles its networking by providing bundled libraries and functionality within the containers themselves. More advanced container networking needs something like Docker Swarm, primarily on a single or connected cluster. Overall, the networking model of a Docker instance is less robust compared to Kubernetes, but in many cases, this is more than enough for light use cases and highly portable deployments.
Kubernetes
Kubernetes provides a more comprehensive and configurable networking model, supporting features like service discovery through DNS, pod-to-pod communication, and fine-grained networking policies. As a containerization platform, Kubernetes is less concerned with how you create containers and is much more concerned with how they communicate and are managed, so this is not surprising!
5 – Scalability
Docker
Docker is most suitable for smaller-scale applications or environments where extensive orchestration isn’t necessary. Docker streamlines the management of these containerized apps, but when you start looking at more complex containerized applications, you start running into barriers. That being said, Docker has highly efficient resource utilization in its basic deployment, and its highly portable containers make for easy scalability in the early stages.
Kubernetes
Once you get more complicated in your containerization, you need to start looking into orchestration for more efficient scalability. Kubernetes is designed for large-scale deployments with thousands of containers across clusters. It excels in scaling applications horizontally and ensuring high availability.
6 – State and Storage Management
Docker
Docker offers basic volume and storage management, mostly local to the host system. It lacks advanced persistence and stateful workload support, which makes more complex container instances a matter of trying to figure out how to do it within the limitations of Docker rather than taking advantage of the benefits of Docker.
This is especially true when dealing with multiple services and deployment scaling and management that has to take place over multiple clusters – while Docker Swarm does help with this, the inherent limitations of lacking advanced persistence can make this difficult.
Kubernetes
Kubernetes provides robust support for stateful applications, persistent storage, and dynamic provisioning through integration with various storage backends. This reduces the complexity of managing multiple servers and services, allowing you to deploy applications even in highly advanced or complicated production environments.
7 – Ecosystem and Extensibility
Docker
Docker is more focused on the containerization lifestyle than anything else, and most of its extensions and provisions, like Docker Compose, are focused on this. For that reason, there’s less of a focus on modularity in terms of extensibility – the idea is to simply add more containers. While this is easy to do, it can be costly and can result in Docker looking far more complicated than it actually is.
Kubernetes
Kubernetes is much more focused on providing a platform – as such, it is a rich, extensible ecosystem with support for plugins, custom controllers, and integrations with monitoring, logging, and CI/CD tools. Its declarative API and modular architecture make it highly adaptable to diverse use cases, allowing it to rapidly scale with less overhead than Docker at larger use case scales.
Kubernetes vs. Docker: Comparison Table
Based on the insights we discussed in the section above, here is a head-to-head comparison between the two technologies for easier comprehension:
| Key Difference | Docker | Kubernetes |
| 1. Building vs. Managing | A tool for building solutions through container images. Each container is self-contained and designed for specific functions. | A tool for managing solutions by orchestrating containerized applications. Handles deployment, scaling, and resource allocation for containers. |
| 2. Scope of Management | Manages containers on a single node, focusing on creating and deploying containers on individual machines. | Manages applications at a cluster level, handling containers across multiple nodes for scalability, reliability, and orchestration. |
| 3. Orchestration | Provides basic orchestration via Docker Swarm, suitable for lightweight containerized applications. | Offers advanced orchestration features such as scheduling, load balancing, self-healing, and service discovery. Automates management of container collections. |
| 4. Networking | Uses bundled libraries for container networking. Docker Swarm adds basic networking capabilities for connected clusters. | Supports robust networking features like pod-to-pod communication, service discovery via DNS, and detailed networking policies. |
| 5. Scalability | Ideal for small-scale applications with simpler setups. Portable and resource-efficient containers enable easy scalability in the early stages. | Designed for large-scale deployments, managing thousands of containers across clusters. Excels in horizontal scaling and maintaining high availability. |
| 6. State and Storage | Provides basic storage management limited to local volumes. Lacks advanced persistence and support for stateful workloads across clusters. | Offers advanced support for stateful applications, persistent storage, and dynamic provisioning through various storage backend integrations. Simplifies management of complex multi-service applications. |
| 7. Ecosystem and Extensibility | Focused on containerization, with extensions like Docker Compose. Limited modularity and extensibility, focusing on adding more containers, which can increase complexity. | A rich, extensible platform with support for plugins, custom controllers, and CI/CD integrations. Its modular architecture and declarative API make it highly adaptable and scalable for diverse use cases. |
A Brief History: Kubernetes and Docker
At this point, you may be wondering whether this means that you should use Kubernetes when you are containerizing applications. The simple answer is no. There are also other alternatives to using Kubernetes, like Docker Swarm. Docker Swarm is the container orchestration tool that was developed by the Docker company as a solution to orchestrate containers.
With Kubernetes coming out on June 7th 2014, and Docker Swarm being launched October 16th 2014, it was up to the community to decide which tool was the most appropriate to use for orchestration. It quickly became clear that the community much preferred working with Kubernetes, which is why you’re way more likely to hear about Kubernetes today than Docker Swarm.
It’s also important to understand that orchestration isn’t a new concept at all, and Kubernetes is just the tool for container orchestration. In the past, other tools have existed to help orchestrate non-containerized applications, like DC/OS.
However, in 2015, DC/OS saw the tendency in the industry and decided to sunset the platform in favor of becoming focused on providing a Kubernetes platform. This was a clear sign that Kubernetes was quickly becoming the preferred way of orchestrating workloads.
Which is Better: Kubernetes or Docker?
As you can see, these two tools serve very different use cases. Rather than trying to figure out which tool to use, it’s more important to figure out when one of these two tools should be used. You’ll often find that you should be implementing both, especially as your company scales.
Docker will be the tool you use in the beginning of your toolchain. It’s the tool you will use to define an image of your application, which can then later be run as a container. With Docker, you are preparing your application to be run in production.
Once your application is fully ready to be deployed, you’ll start using Kubernetes to run it. Handing it over to Kubernetes, the tool will then take care of running the application and handle any incoming requests to the application.
Does Kubernetes use Docker?
With all this talk about how Docker and Kubernetes work together, you’d imagine that Kubernetes uses Docker under the hood. The truth is that it doesn’t. With Kubernetes, you can choose what runtime you want to use, and at a point, it was indeed possible to use Docker as the container runtime. However, for a long time, this hasn’t been the default, with Kubernetes instead opting to use containerd as the runtime, which is an OCI-compliant runtime.
A while ago, Kubernetes decided to remove the dockershim, completely removing the possibility of using Docker as the runtime. There are a few reasons for this, with the main one being that Docker mostly works as a GUI for developers, not a runtime that is easy to use for computer systems like Kubernetes. Most likely, this isn’t going to be relevant for you when using Kubernetes, as it doesn’t have any effect on regular applications. However, it’s a good thing to know. For example, if you are thinking about running CI/CD pipelines in Kubernetes, this means you can’t use the popular principle of Docker-in-Docker.
Conclusion
Now you know more about what the purpose of both Docker and Kubernetes is. You know that Docker is the tool to use when you need to develop and prepare your applications to be run, and Kubernetes is the tool to use when you need to get your applications deployed. You also know that it’s possible to find alternatives to Docker to orchestrate your containers. Lastly, you know that Kubernetes doesn’t actually use Docker but instead uses an OCI-compliant runtime like containerd.
If you end up wanting to run your applications in Kubernetes, it’s important to know that your applications are running as expected, either by performing load testing or mocking services. In those cases, as well as during API debugging and contract testing, you can check out Speedscale.