Container Solutions: Kubernetes vs. Docker

Alex Tray -
kubernetes vs docker
Illustration: © IoT For All

Containerization has existed for decades but has seen increasing adoption in recent years for application development and modernization. We will discuss two specific container solutions and their uses: Docker vs. Kubernetes. First, we will discuss exactly what containerization is and then we will dive into the benefits of each solution.

What is Containerization?

Containerization is a form of virtualization at the application level. It aims to package an application with all its dependencies, runtimes, libraries, and configuration files in an isolated executable package called a container. The operating system (OS) is not included in the container, which makes it different from virtual machines (VMs), which are virtualized at the hardware level and include the OS. 

While the concept behind virtualization is the sharing of physical resources between several virtual machines, containers share the kernel of one OS between several containers. Unlike virtual machines, containers are lightweight precisely because they don’t contain the OS. This is why containers take seconds to boot. In addition, containers can easily be deployed on different operating systems (Windows, Linux, macOS) and in different environments (cloud, VM, physical server) without requiring any changes.

In 2013, Docker Inc. introduced Docker in an attempt to standardize containers to be used widely and on different platforms. A year later, Google introduced Kubernetes as a solution to manage a cluster of container hosts. The definitions of the two solutions will highlight their differences.

Container Solution: Docker

Docker is an open-source platform for packaging and running applications in standard containers that can run across different platforms in the same behavior. With Docker, containerized applications are isolated from the host, which offers the flexibility of delivering applications to any platform running any OS. Furthermore, the Docker engine manages containers and allows them to run simultaneously on the same host.

Due to the client-server architecture, Docker consists of client- and server-side components (Docker client and Docker daemon). The client and the daemon (Dockerd) can run on the same system, or you can connect the client to a remote daemon. The daemon processes the API requests sent by the client in addition to managing the other Docker objects (containers, networks, volumes, images, etc.).

Docker Desktop is the installer of Docker client and daemon and includes other components like Docker Compose, Docker CLI (Command Line Interface), and more. It can be installed on different platforms: Windows, Linux, and macOS.

Developers can design an application to run on multiple containers on the same host, creating the need to manage multiple containers simultaneously. For this reason, Docker Inc. introduced Docker Compose. Docker vs. Docker Compose can be summarized as follows: Docker can manage a container, while Compose can manage multiple containers on one host.

#1: Docker Compose

Managing multi-containerized applications on the same host is a complicated and time-consuming task. Docker Compose, the orchestration tool for a single host, manages multi-containerized applications defined on one host using the Compose file format. 

Docker Compose allows running multiple containers at the same time by creating one YAML configuration file where you define all the containers. Compose allows you to split the application into several containers instead of building it in one container. You can split your application into sub-sub services called microservices and run each microservice in a container. Then you can start all the containers by running a single command through Compose.

#2: Docker Swarm

Developers can design an application to run on multiple containers on different hosts, which creates the need for an orchestration solution for a cluster of containers across different hosts. For this reason, Docker Inc. introduced Docker Swarm. Docker Swarm, or Docker in Swarm mode, is a cluster of Docker engines that can be enabled after installing Docker. Swarm allows for managing multiple containers on different hosts, unlike Compose, which only manages multiple containers on the same host.

Container Solution: Kubernetes

Kubernetes (K8s) is an orchestration tool that manages containers on one or more hosts. K8s cluster the hosts whether on-premises, in the cloud, or in hybrid environments and can integrate with Docker and other container platforms. Google initially developed and introduced Kubernetes to automate the deployment and management of containers. K8s provides several features to support resiliency, like container fault tolerance, load balancing across hosts, and automatic creation and removal of containers.

Kubernetes manages a cluster of one or more hosts, either master nodes or worker nodes. The master nodes contain the control panel components of Kubernetes, while the worker nodes contain non-control panel components (Kubelet and Kube-proxy). The recommendation is to have at least a cluster of four hosts: at least one master node and three worker nodes to run your tests. It is essential to back up your cluster periodically to keep your Kubernetes data safe in case of a disaster scenario. All the critical information is saved in a snapshot file.

Control Panel Components (Master Node)

The master node can span across multiple nodes but can run only on one computer. It is recommended that you avoid creating application containers on the master node. The master is responsible for managing the cluster. It responds to cluster events, makes cluster decisions, schedules operations with containers, starts a new Pod (a group of containers on the same host and the smallest unit in Kubernetes), runs control loops, and more. 

  • The API server is the control panel frontend, which exposes an API to other Kubernetes components. It handles the access and authentication of the other components. 
  • Etcd is a database that stores all cluster key/value data. Each master node should have a copy of etcd to ensure high availability.
  • Kube scheduler is responsible for assigning a node for the newly created Pods.
  • Kube control manager is a set of controller processes that run in a single process to reduce complexity. The controller process is a control loop that watches the shared state of the cluster through the API server. When the state of the cluster changes, it takes action to change it back to the desired state. The control manager monitors the state of nodes, jobs, service accounts, tokens, and more.
  • The cloud controller manager is an optional component that allows the cluster to communicate with the APIs of cloud providers. It separates the components that interact with the cloud from those that interact with the internal cluster.

Node Component (Working Nodes)

The working nodes are the non-master nodes. There are two node components: kubelet and kube-proxy. They should run on each working node in addition to a container runtime software like Docker.

  1. Kubelet is an agent that runs on the working node to ensure that each container runs in a Pod. It manages the containers that were created by Kubernetes to ensure they are running in a healthy state.
  2. Kube-proxy is a network proxy running on each working node and is part of the Kubernetes network service. It allows communication between Pods and the cluster or the external network.

Additional Components

  • Service is a logical set of Pods that work together at a given time. Unlike Pods, the IP address of a service is fixed. This fixes the issue created when a Pod is deleted so that other Pods or objects can communicate with the service instead. The set of Pods of one service is selected by assigning a policy to the service to filter Pods based on labels.
  • A label is a key/value pair of attributes that can be assigned to Pods, services, or other objects. Labels allow the selection to query objects based on common attributes and assign tasks. Each object can have one or more labels. A key can only be defined one time in an object.

Kubernetes vs. Docker: Which is Better?

Kubernetes and Docker are different scope solutions that can complete each other to make a powerful combination. Thus, Docker vs. Kubernetes is not a correct comparison. Docker allows developers to package applications in isolated containers. Developers can deploy those containers to other machines without worrying about compatibility with operating systems. 

Developers can use Docker Compose to manage containers on one host. But Docker Compose vs Kubernetes is not an accurate comparison since the solutions are for different scopes. The scope of Compose is limited to one host, while that of Kubernetes is for a cluster of hosts. When the number of containers and hosts becomes high, developers can use Docker Swarm or Kubernetes to orchestrate Docker containers and manage them in a cluster. Both Kubernetes and Docker Swarm are container orchestration solutions in a cluster setup. 

Kubernetes is more widely used than Swarm in large environments because it provides high availability, load balancing, scheduling, and monitoring to provide an always-on, reliable, and robust solution. The following points will highlight the differences that make K8s a more robust solution to consider.

#1: Installation

  • Swarm is included in the Docker engine already. Using certain Docker CLI (command-line interface) standard commands, Swarm can easily be enabled. 
  • Kubernetes deployment is more complex because you need to learn new non-standard commands to install and use it. In addition, you need to learn to use the specific deployment tools in Kubernetes. The cluster nodes should be configured manually in Kubernetes, like defining the master, controller, scheduler, etc.

Note: The complexity of Kubernetes installation can be overcome by using Kubernetes as a service (KaaS). Major cloud platforms offer Kaas, those include Google Kubernetes Engine (GKE), which is part of Google Cloud Platform (GCP), and Amazon Elastic Kubernetes Service (EKS).

#2: Scalability

Both solutions support scalability. However, it is easier to achieve scalability with Swarm, while Kubernetes is more flexible.

  • Swarm uses the simple Docker APIs to scale containers and services on demand in an easier and faster way.
  • Kubernetes, on the other hand, supports auto-scaling, which makes scalability more flexible. But due to the unified APIs that it uses, the scalability is more complex.

#3: Load Balancing

  • Swarm has a built-in load balancing feature and is performed automatically using the internal network. All the requests to the cluster are load-balanced across hosts. Swarm uses DNS to load-balance the request to service names. No need for manual configuration for this feature in Swarm. 
  • Kubernetes should be configured manually to support load balancing. You should define policies in Pods for load balancing. Thus Pods should be defined as services. Kubernetes uses Ingress for load balancing, an object that allows access to Kubernetes services from an external network.

#4: High Availability

Both solutions natively support high availability features. Still, there are slight differences in Kubernetes vs. Docker.

  • The Swarm manager monitors a cluster’s state and takes action to fix any change in the actual state to meet the desired state. Whenever a worker node crashes, the swarm manager recreates the containers on another running node.
  • Kubernetes also automatically detects faulty nodes and seamlessly fails over to new nodes.

#5: Monitoring

  • Swarm does not have built-in monitoring and logging tools. It requires third-party tools for this purpose, like Reimann or Elasticsearch, and Kibana (ELK).
  • Kubernetes has the ELK monitoring tool built in to monitor the cluster state natively. In addition, a number of monitoring tools are supported to monitor other objects like nodes, containers, Pods, etc.

The Final Verdict: Kubernetes vs. Docker

Docker is a containerization platform for building and deploying applications in containers independently from the operating system. It can be installed using Docker Desktop on Windows, Linux, or macOS and includes other solutions like Compose and Swarm. When multiple containers are created on the same host, managing them becomes more complicated. Docker Compose can be used in this case to easily manage multiple containers of one application on the same host. 

In large environments, a cluster of multiple nodes becomes necessary to ensure high availability and other advanced features. Here comes the need for a container orchestration solution like Docker Swarm and Kubernetes. The comparison between the features of these two platforms shows that both support scalability, high availability, and load balancing. However, when it comes to Kubernetes vs. Docker installation, Docker Swarm is easier to install and use, while Kubernetes supports auto-scaling and built-in monitoring tools. This explains why most large organizations use Kubernetes with Docker for applications that are largely distributed across hundreds of containers.

Alex Tray - Cybersecurity Consultant, NAKIVO

Guest Writer
Guest Writer
Guest writers are IoT experts and enthusiasts interested in sharing their insights with the IoT industry through IoT For All.
Guest writers are IoT experts and enthusiasts interested in sharing their insights with the IoT industry through IoT For All.