Container orchestration is one of the important topics in DevOps, and the market in this is getting bigger daily. Let us look into Docker swarm and Kubernetes in detail, their differences, and most importantly when to use them. In this article, you will learn what containers are and then move on to what Kubernetes is and why we need them. This article will also explore Docker swarm and take you through the similarities and differences between Docker swarm and Kubernetes and, finally, which container orchestration needs to be used and when. If you are preparing for DevOps certification, do checkout Docker Kubernetes certification.
What are containers?
Containers can be managed in a standardized way, which allows for standard solutions during a containerized software’s lifecycle:
- Common build chain
- Common image storage
- Common way to deploy and scale-up
- Common hosting of running containers
- Common control and monitoring of running containers
- Common ways to update running containers to a new version
The most important part is that whatever the software inside the container is, it can be handled in a standardized way. Each container has its own specific IP, but it is available at localhost or 127.0.0.1. A TCP port must be exposed to communicate with the application it runs, e.g., port 80 or 443 for an HTTP or HTTPS web servers.
For more than one container, the exposed ports should be different. For example, the HTTP server and WordPress have 80 as the default port. If you are using both together, only one can be exposed to 80, and the other has to be exposed to some other port, so bind exceptions of ports can be avoided. Docker also allows you to access the container shell to enter terminal commands and expose further ports to attach debuggers and investigate problems. Data written to the container’s file system is lost when it shuts down.
Any number of containers can be launched from the same base image. This makes scaling easy because every container instance is identical and disposable. This may change how you approach application development if you want to use Docker on production servers. Presume your application has a variable that counts the number of logged-in users. If it runs in two containers, either could handle a login, so each would have a different user count.
Dockerized web applications should avoid retaining state data in variables and local files. Your application can store data in a database such as Redis, MySQL, or MongoDB, so the state persists between container instances. If you want to improve your knowledge of DevOps, check out the DevOps courses on KnowledgeHut.
Kubernetes vs Docker Swarm: Head-to-head Comparison
Point of comparison
No GUI, needs third party
All-in-one scaling based on traffic
Values scaling quickly (approx. 5x faster than K8s) over scaling automatically
No, needs third party
No built-in internal auto load balancing
Internal load balancing
Supports multiple security features
Supports multiple security features
Needs a separate CLI
CLI is out of the box
Docker Swarm vs Kubernetes: Detailed Comparison
What is Kubernetes?
Kubernetes’ job is to take a group of machines and expose them as if it was a single thing. It is similar to running an application locally; you don’t care which CPU core is executing it or the memory addresses the application is using. We just run the application, and let the operating system take care of the rest. Kubernetes does that at the data center level. It doesn’t matter if we have one or one thousand machines available. The way we interact with Kubernetes is the same; we tell it what we want, and it will do its best to make that happen.
Kubernetes API allows us to declare what we want without having to know exactly how that is going to happen, and this is very powerful.
We will not say: “run one copy of this application in machine A and another in machine B.” Actually, we don’t even need to know what machines are running behind as people continue using Kubernetes. We will just say, “I need 2 copies of this application, and it needs 2 cores and 5 GB of memory,” and Kubernetes will find a way to run it.
If the application crashes, Kubernetes can restart it. If one application starts using more resources than you defined as its limit, Kubernetes will make sure this application will not impact other applications running in the same machine. Kubernetes helps us run all our applications smoothly, fixes things when they go wrong and uses the available resources in the best way possible.
In addition, Kubernetes provides several features that make our lives easier. If we have dozens of replicas of an application running, Kubernetes can load and balance the traffic between these replicas. Kubernetes can also help if we need an application to be accessible from outside the cluster. What if we need to provide configurations and secrets to our applications, run one-off tasks, or run tasks on a schedule? Kubernetes can do it all.
In summary, Kubernetes is a platform that makes it easier to run complex systems’ reliably. Think of it this way:
While Kubernetes can orchestrate other workload types, including virtual machines and server less functions, it is most commonly used to orchestrate containerized apps.
A case has just been made for a long and bright future for Kubernetes with all the major technology companies backing it. In fact, it grew so rapidly and became so important that even Amazon embraced it. Even the mighty Amazon and AWS could not ignore Kubernetes.
Another reason the user community needs and loves Kubernetes goes back to the idea that Kubernetes is the OS of the cloud.
It has already been stated that Kubernetes can abstract lower-level on-premises and cloud infrastructure, allowing you to write your applications to run on Kubernetes without even knowing which cloud is behind it. Well, this has a few side benefits including:
- Deploy to one cloud today and switch to another tomorrow.
- You can run multi-cloud.
- Can ramp onto a cloud and then ramp off back to on-prem more easily.
Basically, applications written for Kubernetes will run anywhere that has Kubernetes. It is a lot like writing applications for Linux, you write your applications on Linux, it does not matter even if Linux is running on Supermicro servers in your garage, or AWS cloud instances on the other side of the planet.
What is Docker Swarm?
Docker swarm is a container orchestration tool that allows a user to manage multiple containers deployed across multiple host machines. Docker swarm has different components which help it to manage the swarm effectively. Let us have a look at the architecture to understand how it works:
Docker Swarm Architecture
A worker node is something on which tasks are created by the manager. It will have services running on it to maintain the state defined in the YAML file.
In this architecture, there is only one YAML file and this is the power of YAML file. A stack of services is created and deployed on each worker node using the YAML file.
A node is a machine. It can act as a manager, worker, or both. We can also have multiple manager nodes but there will always be a primary node to manage the swarm cluster.
Characteristics of Manager Node
Building Blocks of Docker Swarm
A swarm cluster can have the following components:
- Node: The node is the host machine. A machine can act as a worker, manager, or both. We can have a swarm with one node as well. In that case, the respective machine acts as both a worker and manager node. For example, in a cluster of 5 computers, each computer will be a node. And there will be a master computer which is responsible for the communication of the Cluster.
- Stack: A set of services combined is called a stack. Stack and Compose work somewhat similarly, except, there are some commands which will be ignored by Docker-compose in a non-swarm mode such as For example, when we want to deploy our whole project which is a collection of services (like web server, database, and maybe a task queue) in a single command; we declare all the services in a YAML file, and that YAML file is now a stack of services for the swarm manager. The swarm manager will deploy the stack and maintain the desired states of services defined in the YAML file.
- Service: A service is the definition of the tasks to execute on the manager or worker nodes. It is the central structure of the swarm system and the primary root of user interaction with the swarm. When you create a service, you specify which container image to use and which commands to execute inside running containers. For example, the flask app we created earlier is a service. Why? Because we are using flask_app:2.0 Docker image which will be running in a container with the command to run the WSGI server.
- Task: Task is responsible for maintaining the desired replica set of the service. To deploy a service on a worker node, the swarm manager creates a task and starts a container in
Swarm as an Orchestrator
On the orchestration front, Swarm exposes a rich API that allows you to deploy and manage complex microservices apps with ease. You can define your apps in declarative manifest files and deploy them to the Swarm with native Docker commands. You can even perform rolling updates, rollbacks, and scaling operations with simple commands.
Differences Between Docker Swarm and Kubernetes (Based on Tech Stack)
Kubernetes and Docker Swarm are both effective solutions for:
- Massive scale application deployment
The Core Differences
The main difference is that Kubernetes is a container orchestration system that manages multiple containers. Docker Swarm does not manage any containers but instead is a cluster manager for Docker containers. Kubernetes also has built-in support for stateful applications, whereas Docker Swarm does not.
- Kubernetes is designed to work with any programming language and framework, while Docker Swarm only works with the Docker Engine API.
- Kubernetes runs on top of Linux Containers while Swarm runs inside Docker Containers.
- Kubernetes uses a master-slave architecture where one master instance controls multiple worker instances; Kubernetes uses an active/passive model where each worker instance is controlled by its own master instance.
Kubernetes and Docker Swarm are the most popular container orchestration tools available today. These tools can be used to deploy and manage containers on your own infrastructure, but they also provide a way to run your own container services in the cloud.
Kubernetes is an open-source container orchestrator and scheduler built by Google to manage containerized applications and services. It was designed to be easy to use, fast, reliable and secure from the ground up.
Docker Swarm is also an open-source project that aims to provide a simple, yet powerful cluster manager to run your containers at scale. It offers you a lot of features like load balancing, service discovery, high availability etc.
It can be said that Docker Swarm is easier to pick up than Kubernetes. Even teams with less technical skill can pick up Kubernetes and work on it. But the thing with Kubernetes is it offers faster and more secure clusters than Docker Swarm. One thing to understand is Kubernetes cannot be learned before learning Docker. The technology involved in Docker is used to build containers to deploy inside the Kubernetes cluster. You can take Docker and Kubernetes certification training on KnowledgeHut.
Frequently Asked Questions FAQs
1. Does Kubernetes use Docker Swarm?
No, Kubernetes and Docker swarm are two different tech stacks, and both are used for container orchestration. Kubernetes has a more complex architecture compared to Docker swarm
2. Do I need to learn swarm before Kubernetes?
Not required. Both are container orchestration tools.
3. Is Docker and Docker swarm the same?
No, Docker and Docker Swarm are different, Docker is a container, and Docker swarm is a container orchestration tool.