TABLE OF CONTENTS
Updated: 10 Dec 2024
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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 vs Docker
Feature |
Docker |
Kubernetes |
Purpose |
Containerisation platform |
Container orchestration and management |
Primary Use |
Packaging and running single containers |
Managing multiple containers across clusters |
Scalability |
Limited to single-host scaling |
Auto-scaling for applications across multi-node clusters. |
Networking |
Basic networking model |
Advanced networking and load balancing |
Setup Complexity |
Simple to install and configure |
More complex to set up and manage; designed for multi-host environments |
What is Kubernetes?
Kubernetes (K8s) is an open-source platform designed to orchestrate containerised applications. Developed by Google, Kubernetes simplifies the management of distributed systems at scale, optimising resource utilisation across clusters of containers. It can run independently of Docker and offers advanced features such as self-healing, scaling, and load balancing for complex 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 to create a Kubernetes cluster on Hyperstack.
What is Docker?
Docker is a containerisation platform that allows developers to package applications and their dependencies into lightweight, portable containers. Docker ensures that applications run consistently across different environments, providing an isolated environment for applications to function without conflicts.
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.
Docker Image on Hyperstack: One-Click Deployment
Setting up Docker with GPU support on a standard Ubuntu image requires following detailed instructions (see this guide or check the tutorial below), configuring drivers, and dependencies and ensuring compatibility with your system.
Instead of setting up Docker from scratch, you can deploy a pre-configured Docker image with GPU support on Hyperstack. This eliminates the need for complex setup or dependency management. Whether you're building AI models, working on microservices or optimising CI/CD pipelines, Hyperstack’s one-click Docker deployment offers:
- Instant Setup: Deploy containers with GPU support in minutes, bypassing the traditional manual installation and configuration.
- Optimised for AI/ML: The Docker image is designed to make GPU resources accessible immediately, ideal for machine learning workloads.
- Hassle-Free: With our docker image, you can save time, minimise setup errors and ensure smooth GPU access for demanding workloads on Hyperstack.
5 Key Differences Between Kubernetes and Docker
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.
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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.
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Scalability: Docker’s scalability is limited to single nodes, whereas Kubernetes allows seamless scaling across multiple nodes, making it ideal for cloud-native applications.
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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.
When to Choose: Docker vs Kubernetes on Hyperstack
Choosing between Docker and Kubernetes for your specific workloads can be hard, so we’ve made it easier for you to decide. See below:
For Small Applications, Single-Host Deployments and Development Testing
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 Multi-Team Environments, Complex CI/CD Pipelines and Cloud-Native 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.
Combining Docker and Kubernetes on Hyperstack
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.
Conclusion
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.
FAQs
What is the main purpose of Docker?
Docker is a containerisation platform that allows developers to package applications and their dependencies into portable containers.
How does Kubernetes differ from Docker?
Kubernetes is an orchestration system designed to manage and automate the deployment and scaling of containerised applications across multiple hosts.
Can Docker and Kubernetes be used together?
Yes, Docker is often used for container creation, while Kubernetes orchestrates those containers at scale.
Is Kubernetes easy to set up?
No, Kubernetes has a steeper learning curve and is more complex to set up compared to Docker, which is simpler for individual projects.
When should I use Docker?
Docker is ideal for small applications and development environments that do not require complex orchestration or multi-host setups.
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