Kubernetes vs Docker: Why not Both?
In this article, we will discover the most widely used tools in the modern cloud-native container ecosystem: Docker and Kubernetes. Though Docker and Kubernetes are often used together, the most common question asked is Kubernetes or Docker. The answer is neither. Our comprehensive will give you a better understanding and help you to understand Docker and Kubernetes easily.
What is a container?
The applications are packaged together with all the necessary software libraries along with dependencies and configuration files required to run them as a single unit called containers.
Containers are immutable and share the same underlined operating system, which will save us time and money.
Containers share the same operating system kernel and isolate the application processes. Containers are immutable, so the whole application can be moved and run across different computing environments like development, testing, production, and so on.,
We can also run the containers on VMs, Bare Metal machines.
Containers are often used with container orchestration platforms such as Kubernetes.
The applications along with all the dependencies are called container images. So that it can run in any environment like a private data centre, public cloud , even on a developers personal laptop. We can take that image and create containers.
It is the most part of the container ecosystem. Generally they follow a layered approach using the Union File System approach to create containers.
What is Docker?
Docker is an open-source containerization platform that we can run on different operating systems, such as Linux, Windows, and Mac. It is used in building, shipping, running, and managing containers. Docker is one of the container runtimes used in orchestration, in which we can run and scale the containers without any downtime.
Docker and container-d are container runtimes. These runtimes use the features of the underlying OS, like namespaces and cgroups, to run the containers.
Let’s explore the architecture of Docker.
Docker uses a client-server architecture with three main components:
2.Docker Daemon or Docker Host
1. Docker client:
The Docker client interacts with the Docker daemon to build, manage and run containers. But before you can run a Docker container, its image must be built with a Dockerfile.
2. Docker Daemon or Docker Host:
Docker Host provides an environment to execute and run the containers or applications. It contains the docker daemon, images, containers, networks, and volumes.
3. Docker Registry:
Docker also has a service called DockerHub, a central repository of Docker images, where you can store and access many pre-built images and distribute them across different environments. The Docker registry can be a public or private registry.
Challenges With Docker:
Docker has become a popular tool for containerization and application deployment. There are some challenges and limitations that users should be aware of. Here are some of the potential problems with Docker:
- Portability and Compatibility: Docker images may not always be compatible with different host operating systems. Docker versions can cause issues with deployment and portability.
- Complexity: If users are unfamiliar with containerization concepts, additional tooling is required to manage container orchestration, monitoring, and networking.
- Resource consumption: When many containers are running on the same host, it can consume a significant amount of system resources. This can lead to issues with performance and scalability.
- Security: Containers in Docker share the same host operating system kernel, which means that if one container is compromised, it might be possible to bring down the other containers or even the host itself. So when we use Docker, we need to follow the security practices such as running containers with minimal privileges and restricting network access.
Containers are difficult to manage at volume in a real-world production environment. Containers at volume need an orchestration system.
Why do we move to Container Orchestration?
If the containers running on the single host OS and the host machine go down, it also brings down the running containers. Also, management gets difficult if many containers run on the same host OS. Scaling is difficult as the containers are running on a single host OS.
Let’s explore the architecture of Docker Swarm orchestrators.
Docker Swarm Architecture
Docker Swarm is a native clustering and orchestration solution for Docker. Docker Swarm is a container orchestration tool that allows users to deploy and manage a cluster of Docker nodes as a single system.
A minimum of three nodes must be available to build the Swarm. With these three nodes, Docker Swarm can manage failures of a single node.
The components of Docker Swarm
The Docker Swarm architecture consists of several components that work together to provide a scalable and fault-tolerant platform for running containerized applications.
To create a Docker Swarm, we need to initialize a Swarm Manager. The Swarm manager is the central point of control for the Swarm Cluster. It is responsible for managing the state of the cluster, scheduling tasks on worker nodes, and handling node failures. The Swarm manager schedules tasks to run on worker nodes to maintain the desired state.
Worker nodes are the computing resources that run Docker containers.
They receive tasks from the Swarm manager and execute them and report back the results to the manager.
Worker nodes are the computing resources that run Docker containers.
Features of using Docker Swarm
- It is suitable for large-scale deployments, such as load balancing, service discovery, scaling, and rolling updates.
- Provides a scalable and fault-tolerant platform for deploying and managing containerized applications.
- Docker Swarm supports Docker’s networking and storage plugins, which allow users to integrate with various network and storage solutions.
Docker Swarm is a powerful container orchestration tool. There are some disadvantages of using Docker Swarm, such as it is unsuitable for complex infrastructures, and the community is smaller than other platforms.
So, Let’s explore the Kubernetes architecture and its advantages and get to know Why Kubernetes is a popular orchestrator tool used by the larger community?
What is Kubernetes?
Kubernetes is an open-source container orchestration platform that helps to automate the deployment, management, and scaling of containerized applications. One can deploy Kubernetes everywhere on a laptop, on the edge, on a developer workstation, public or private cloud. Kubernetes is also very stable at the core; it is highly extensible and well suited for hybrid setups.
Kubernetes is also known as k8s. It was started by Google in 2014. Now owned and managed by cloud native computing foundation (https://www.cncf.io)
The three main components are,
1. The Control Plane
2. Worker nodes
1.The Control Plane
Control plane is also known as the Master Node. We can also configure a cluster with a multi-master for high availability and consistency of a cluster.
The control plane is responsible for scheduling, resource allocation, health monitoring, and networking.
The Control Plane Components are
Etcd or key/value store: To which only the control plane component (API server) communicates. It stores all the
cluster data and
configuration information of applications. It is also known as the
brain of the cluster.
API server: It is used to communicate with the control-plane components, to the worker nodes, and to the key/value store as well.
Scheduler: Schedule our applications on different worker nodes.
Controller manager: It is a process that runs as a single process in the cluster. It has different types of controllers, such as,
- Node Controller: To check and respond when the node goes down.
- Deployment Controller: To check at any point of time the deployment’s current state is equal to the desired state and respond accordingly.
Where the pods get scheduled. In which we can deploy our applications.
Worker Node Components are,
2. Kube – Proxy
Kubelet: API server and kubelet communicate to deploy the application on the given node. One can send
YAML/JSON manifests to kubelet through API Server, then kubelet can deploy our applications according to the PodSpecs.
Kube – Proxy: A network proxy runs on each node and helps manage network rules on nodes. It allows communication to pods from inside and outside of the cluster.
Container Runtime: To run the containers inside pods, we need to have container runtime. Container runtime can be anything (
container-d, CRI-O, Docker) supported by Kubernetes.
pod is a logical collection of one or more containers. Pod holds containers and it is the
basic deployment units of Kubernetes.
Advantages of using Kubernetes
- Kubernetes gives features like container provisioning, fault toleration, scaling, service discovery, deployment strategies, etc. With those features, we can run the applications without any downtime.
- Kubernetes provides support for high availability. With the Fault-Tolerance feature (both at the app level and node level) , all of the applications would eventually be in the running state.
- Kubernetes is highly scalable and can manage clusters to scale to thousands of nodes.
- Kubernetes is highly flexible and can run on any cloud provider, on-premises data center, or hybrid environment.
- Kubernetes provides powerful automation tools to manage and deploy containerized applications. With these features, we can save time and reduce the possibility of human error.
The article discusses and understands that Docker is a technology for creating and running containers and Kubernetes is a container orchestration framework and also both tools have their pros and cons, but Kubernetes and Docker together provide a complete solution for managing containerized applications at scale. I hope this article helped in better understanding of Kubernetes and Docker. Have a Happy Learning!.