While Docker and Kubernetes are integral to container-based applications, they serve different purposes. Docker is a containerisation platform, whereas Kubernetes is an orchestration system designed to manage containers across multiple environments. In this guide, we'll explore the differences and help you understand when to use Docker and Kubernetes together.
Kubernetes (K8s) is an open-source platform designed to orchestrate containerised applications. Developed by Google and open-sourced in 2014, Kubernetes was inspired by Google's internal Borg system. It was designed to manage and orchestrate containers at scale, facilitating automated deployment, scaling and management of containerised applications
At Hyperstack, we make it easy to get started with Kubernetes. Our platform provides on-demand provisioning for managed Kubernetes clusters, allowing you to quickly deploy and manage containerised applications. You can customise your Kubernetes version and node types, and Hyperstack handles the rest, offering a seamless experience. Visit our API Guide for step-by-step instructions on creating a Kubernetes cluster on Hyperstack.
Docker is a containerisation platform that allows developers to package applications and their dependencies into lightweight, portable containers. Originating from dotCloud (later renamed Docker Inc.), Docker was introduced in 2013 to simplify application deployment through containerization. It revolutionised software development by allowing developers to package applications and their dependencies into portable containers.
On Hyperstack, Docker’s integration is taken a step further. Our pre-baked Docker image is optimised for GPU workloads and simplifies deployment for machine learning and AI. Unlike standard Docker setups, where you might need to configure everything manually, Hyperstack’s Docker image comes with everything you need to get started with GPU support right out of the box. Explore more in our Docker Support Guide here.
Hyperstack Kubernetes clusters are built on a high-performance architecture optimised for scalability, security and reliability, making them ideal for AI, machine learning, and high-performance computing (HPC) workloads.
Docker follows a client-server architecture that simplifies the process of building, shipping, and running applications in containers. At its core is the Docker Engine, which consists of three key components:
Docker Daemon (dockerd): The background service that manages Docker containers, handles image creation, and interacts with the host operating system.
Docker Client (docker): A command-line tool that users interact with. It communicates with the Docker Daemon via REST API or UNIX socket to issue commands.
Docker Registry: A repository where Docker images are stored and shared. Docker Hub is the default registry, but private registries can also be used.
Docker containers are built from images, which are lightweight, standalone packages including the application code, runtime, libraries and system tools. Images are defined using a Dockerfile, which specifies the steps needed to assemble the image.
When an image is executed, Docker creates a container, a lightweight and isolated process with its own filesystem and networking, yet sharing the host kernel. This container-based architecture allows applications to run consistently across different environments, making it ideal for modern CI/CD pipelines and microservices architectures.
Check out the major differences between Kubernetes and Docker below:
Purpose: Docker packages and runs individual containers, while Kubernetes manages and orchestrates those containers across multiple nodes and clusters.
Container Management: Docker handles isolated environments for each application. Kubernetes takes it further by managing entire pods (groups of containers), ensuring scalability and availability across a cluster.
Scalability: Docker’s scalability is limited to single nodes, whereas Kubernetes allows seamless scaling across multiple nodes, making it ideal for cloud-native applications.
Networking: Docker’s networking is simple and sufficient for single-node setups, while Kubernetes provides advanced networking features such as service discovery, load balancing, and multi-cluster communication.
Complexity: Docker is simple to deploy and use, while Kubernetes has a steeper learning curve, best suited for large, distributed applications.
Choosing between Docker and Kubernetes for your specific workloads can be hard, so we’ve made it easier for you to decide. See below:
Docker is ideal for smaller applications or single-host environments. It offers all the tools necessary for developers to package, distribute, and run containers without complex orchestration, making it especially useful for development testing. With our Docker images optimised for ML, you can easily build your ML projects locally before scaling up. Read our guide to Run a Docker Container on Hyperstack for AI Applications.
For organisations and larger development teams with advanced CI/CD workflows, Kubernetes is often the preferred choice. Its orchestration capabilities enable efficient resource management across clusters, automating scaling and load balancing for high-demand applications. Our managed Kubernetes clusters are designed to simplify complex AI/ML deployments, enabling you to focus on development rather than infrastructure.
In many cases, Docker and Kubernetes are used together to capitalise on each tool’s strengths. Docker simplifies the creation and deployment of containers, while Kubernetes manages these containers across clusters, handling the complexities of scaling, self-healing, and load balancing. With Hyperstack, you can leverage Docker’s containerisation alongside Kubernetes’ orchestration for a streamlined and powerful approach to deploying and managing AI applications.
For those looking to deploy containerised applications, Docker is an excellent choice for its simplicity and portability. For large-scale, distributed applications that require automated scaling and management, Kubernetes is the King. We make it easy to take advantage of both technologies with one-click Docker image deployment, pre-configured for GPU workloads. With Hyperstack, you can skip the setup complexities and focus on what matters- building high-performance applications faster. Get started with Hyperstack’s Kubernetes Beta API Guide and bring scalable AI solutions to life.
Docker is a containerisation platform that allows developers to package applications and their dependencies into portable containers.
Kubernetes is an orchestration system designed to manage and automate the deployment and scaling of containerised applications across multiple hosts.
Yes, Docker is often used for container creation, while Kubernetes orchestrates those containers at scale.
No, Kubernetes has a steeper learning curve and is more complex to set up compared to Docker, which is simpler for individual projects.
Docker is ideal for small applications and development environments that do not require complex orchestration or multi-host setups.