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Docker Compose vs Kubernetes: What are the differences?
Introduction
Both Docker Compose and Kubernetes are popular tools used for container orchestration and management. While they serve the same purpose, they have some key differences in terms of their architecture, scalability, setup, and features.
Architecture: Docker Compose is a tool that allows you to define and run multi-container Docker applications. It uses a single machine to manage and distribute containers. On the other hand, Kubernetes is an open-source container orchestration platform that automates the deployment, scaling, and management of containerized applications across multiple machines or nodes. It is a distributed system, designed to handle large-scale containerized applications.
Scalability: Docker Compose is suitable for small-scale applications where scalability is not a major concern. It is designed for single host deployments and does not have built-in features for scaling across multiple machines. On the contrary, Kubernetes is highly scalable and can manage large-scale deployments efficiently. It can automatically scale applications based on resource utilization and can distribute the workload across multiple nodes for better performance.
Setup Complexity: Docker Compose has a relatively simple setup process. It requires Docker to be installed on the host machine, and then the application can be defined using a YAML file and started using a single command. On the other hand, Kubernetes has a more complex setup process as it involves setting up a cluster of nodes, configuring networking, and defining various resources like pods, services, and deployments using Kubernetes manifests. It requires more expertise and effort to set up a Kubernetes cluster compared to Docker Compose.
Built-in Features: Docker Compose provides a limited set of features for container orchestration, such as defining networks, volumes, and dependencies between containers. It focuses on running multiple containers as a single application stack. Kubernetes, on the other hand, offers a wide range of built-in features for container orchestration, including load balancing, service discovery, automatic scaling, and rolling updates. It provides more advanced capabilities for managing containerized applications in production environments.
Community Support: Docker Compose has a large and active community with a vast number of pre-built Docker images and stacks available for various applications. It is widely adopted and has extensive documentation and community support. Kubernetes also has a strong community support with a vast ecosystem of tools and resources. It is backed by major tech companies like Google, Microsoft, and Red Hat, which contributes to its rapid development and adoption.
Use Cases: Docker Compose is suitable for developers or small teams working on local development environments or small-scale applications. It provides an easy way to define and manage multi-container applications for development and testing purposes. Kubernetes, on the other hand, is designed for large-scale deployments in production environments where scalability, high availability, and operational efficiency are crucial. It is widely used in cloud-native application development and microservices architectures.
In summary, Docker Compose is a simple tool for running multiple containers as a single application stack on a single machine, while Kubernetes is a powerful container orchestration platform designed for managing large-scale deployments across multiple machines or nodes.
Hello, we have a bunch of local hosts (Linux and Windows) where Docker containers are running with bamboo agents on them. Currently, each container is installed as a system service. Each host is set up manually. I want to improve the system by adding some sort of orchestration software that should install, update and check for consistency in my docker containers. I don't need any clouds, all hosts are local. I'd prefer simple solutions. What orchestration system should I choose?
If you just want the basic orchestration between a set of defined hosts, go with Docker Swarm. If you want more advanced orchestration + flexibility in terms of resource management and load balancing go with Kubernetes. In both cases, you can make it even more complex while making the whole architecture more understandable and replicable by using Terraform.
We develop rapidly with docker-compose orchestrated services, however, for production - we utilise the very best ideas that Kubernetes has to offer: SCALE! We can scale when needed, setting a maximum and minimum level of nodes for each application layer - scaling only when the load balancer needs it. This allowed us to reduce our devops costs by 40% whilst also maintaining an SLA of 99.87%.
Our whole DevOps stack consists of the following tools:
- GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
- Respectively Git as revision control system
- SourceTree as Git GUI
- Visual Studio Code as IDE
- CircleCI for continuous integration (automatize development process)
- Prettier / TSLint / ESLint as code linter
- SonarQube as quality gate
- Docker as container management (incl. Docker Compose for multi-container application management)
- VirtualBox for operating system simulation tests
- Kubernetes as cluster management for docker containers
- Heroku for deploying in test environments
- nginx as web server (preferably used as facade server in production environment)
- SSLMate (using OpenSSL) for certificate management
- Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
- PostgreSQL as preferred database system
- Redis as preferred in-memory database/store (great for caching)
The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:
- Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
- Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
- Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
- Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
- Scalability: All-in-one framework for distributed systems.
- Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
Pros of Docker Compose
- Multi-container descriptor123
- Fast development environment setup110
- Easy linking of containers79
- Simple yaml configuration68
- Easy setup60
- Yml or yaml format16
- Use Standard Docker API12
- Open source8
- Go from template to application in minutes5
- Can choose Discovery Backend5
- Scalable4
- Easy configuration4
- Kubernetes integration4
- Quick and easy3
Pros of Kubernetes
- Leading docker container management solution166
- Simple and powerful129
- Open source107
- Backed by google76
- The right abstractions58
- Scale services25
- Replication controller20
- Permission managment11
- Supports autoscaling9
- Simple8
- Cheap8
- Self-healing6
- Open, powerful, stable5
- Reliable5
- No cloud platform lock-in5
- Promotes modern/good infrascture practice5
- Scalable4
- Quick cloud setup4
- Custom and extensibility3
- Captain of Container Ship3
- Cloud Agnostic3
- Backed by Red Hat3
- Runs on azure3
- A self healing environment with rich metadata3
- Everything of CaaS2
- Gke2
- Golang2
- Easy setup2
- Expandable2
- Sfg2
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Cons of Docker Compose
- Tied to single machine9
- Still very volatile, changing syntax often5
Cons of Kubernetes
- Steep learning curve16
- Poor workflow for development15
- Orchestrates only infrastructure8
- High resource requirements for on-prem clusters4
- Too heavy for simple systems2
- Additional vendor lock-in (Docker)1
- More moving parts to secure1
- Additional Technology Overhead1