Kubernetes vs Docker

In this kubernetes vs docker tutorial we will briefly look into an overview of Kubernetes vs Docker Swarm before distinguishing  these two containerization platforms. After distinguishing docker swarm vs kubernetes, we will go through the pros and cons of docker vs kubernetes by the end of this tutorial.

Now, let go through the concepts of kubernetes and docker.

Overview of Kubernetes

Kubernetes is an open-source platform developed by Google for container deployment operations, scaling up and down, and automation across the clusters of hosts. Kubernetes is utilized by any architecture deployment  as the platform is modular with features of production-ready, enterprise-grade, self-healing functionalities like auto-scaling, auto-replication, auto-restart, auto-placement. Kubernates also assists in distributing the load among the containers. The goal is to relieve the tools and components from the problem faced due to running applications in private and public clouds by placing the containers into groups and naming them as logical units. The power of kubernetes lies in easy scaling, environment agnostic portability, and flexible growth.

The architecture of kubernetes was designed by keeping the orchestration in mind. It is based on the primary/replica model, in which a master node distributes the instructions to the worker nodes. Worker nodes are the machines which run the microservices. This configuration allows each node to host all of the containers that are running within a container run-time i.e., Docker. Nodes also contain Kubelets that take the instructions from the API, which is in the master node, and then process them. Kubelets also manage pods, including creating new ones if a pod goes down. A pod is an abstraction which groups the containers. By grouping containers into a pod, those containers can share resources. These resources include processing power, memory, and storage. The main features of Kubernetes’ comprises Automation, Deployment and Scaling.

Architecture of Kubernetes

There are two fundamental concepts in a Kubernetes cluster which are node and pod. A node is a common term for VMs and/or bare-metal servers that Kubernetes manages and a pod is a fundamental unit of deployment in Kubernetes. A pod is a collection of related Docker containers that need to coexist. For instance, a web server may need to be deployed with a redis caching server so you can encapsulate both of them into a single pod. Kubernetes deploys both of them side by side. If it makes matters easier for you, you can totally picture a pod consisting of a single container and that would be fine. There are two types of nodes, the master node and the worker node. The master node is the heart of Kubernetes that is installed. It controls the scheduling of pods across various worker nodes, where your application actually runs. The job of this master node is to make sure that the expected state of the cluster is maintained.

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Here’s a brief summary of the Kubernetes’s diagram that is illustrated below.
On Kubernetes Master we have:

1. kube-controller-manager: This is responsible for taking into account the current state of the cluster (for instance, X number of running pods) and making decisions to achieve the expected state (for instance, having Y number of active pods instead). It listens on “kube-apiserver” for information about the state of the cluster
   
2. kube-apiserver: This api server exposes the gears and levers of Kubernetes. It is used by WebUI dashboards and command-line utilities like “kubectl”. These utilities are in turn used by human operators to interact with the Kubernetes cluster.
   
3. kube-scheduler: This will decide how events and jobs would be scheduled across the cluster depending on the availability of resources, policy set by operators, etc. It also listens on “kube-apiserver” for information about the state of the cluster.
   
4. etcd: This is the “storage stack” for the Kubernetes master nodes. It uses key-value pairs and is used to save policies, definitions, secrets, state of the system, etc.

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We can have multiple master nodes so that Kubernetes can survive even the failure of a master node.
On a worker node we have:

1. kubelet: This relays the information about the health of the node back to the master as well as execute instructions given to it by the master node.
   
2. kube-proxy: This network proxy allows various microservices of your application to communicate with each other, within the cluster, as well as expose your application to the rest of the world. Each pod can communicate to every other pod through this proxy, in principle.
   
3. Docker: This is the last unit where each node has a docker engine to manage the containers.

Overview of Docker Swarm

Docker platform has revolutionized the software into packaging. Docker Swarm is an open-source container orchestration platform and is the native clustering engine for and by Docker. Any software, services, or tools that run with Docker containers run equally well in Swarm. Also, Swarm utilizes the same command line from Docker. Swarm turns a pool of Docker hosts into a virtual, single host. Docker swarm essentially benefits the people who are trying to get a pleasant orchestrated environment or who would like clinging to a simple deployment technique but also have more than just one cloud environment or one particular platform to run this on.

Docker swarm uses the standard Docker API and networking which makes it easy to drop into an environment where you’re already working with the Docker containers. There are four key principles on which the Docker Swarm is designed to work around.

1. Simple yet powerful with a “just works” user experience.
2. Resilient zero single-point-of-failure architecture.
3. Secure by default with automatically generated certificates.
4. Backward compatibility with existing components.

Likewise to Kubernetes, Docker Swarm also deploys across nodes and manages the nodes availability. Docker Swarm calls the manager node i.e., it’s main node. Within the Swarm, the manager nodes communicate with the worker nodes. Docker Swarm also offers load balancing.

Architecture of Docker

Traditionally, cloud service providers use the virtual machines to separate running applications from one another. A hypervisor, or host operating system, provides virtual CPU, memory and other resources to many guest operating systems. Each guest OS works as if it is running on an actual physical hardware and it is, ideally, unaware of other guests running on the same physical server.

Nevertheless, there are several issues with virtualization. Primary issue is that provisioning of resources takes time. Each virtual disk image is large and bulky and getting a VM ready for use can take up to a minute. Second crucial issue is that system resources are used inefficiently. OS kernels are control freaks that would like to manage everything that’s supposedly available to them. For instance, if a guest OS thinks 2GB of memory is available to it, it takes control of that memory even if the applications running on that OS consumes only half of it.

On the contrary, when you run containerized applications, you will virtualize the operating system having standard libraries, packages, etc. but not the hardware. Now, instead of providing virtual hardware to a VM, you provide a virtual OS to your application. You can run multiple applications and impose limitations on their resource utilization if you want, and each application will run obliviously to the hundreds of other containers it is running alongside.

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Comparing Kubernetes and Docker Swarm

Although both these orchestration tools offer much of the same functionalities, there are common differences among them in which they operate.

Comparing Applications definitions among Kubernetes vs Docker

In kubernetes an application is deployed by utilizing amalgamation of services or microservices, deployments, and pods. 

In Docker Swarm, the applications can be deployed as micro-services or services in a swarm cluster. YAML files are utilized to identify multi-container. Additionally, Docker compose can install the application.

Comparing Network among kubernetes vs Docker swarm 

The networking model in kubernetes is a flat network which allows all pods to interact with each other. The policies of the network specify pods interaction among each other. The flat network is implemented typically as an overlay. The model needs two CIDRs: one for the services and the other from which pods acquire an IP address.

In Docker Swarm, the node joining a swarm cluster generates an overlay network for services that span every host in the docker swarm and a host-only docker bridge network for containers. The docker swarm allows the users to choose to encrypt container data traffic while creating an overlay network on their own.

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Comparing Scalability among docker vs kubernetes 

Kubernetes framework provides all features at one place for distributed systems. It is a complex system which gives strong guarantees about the cluster state and a unified set of APIs. The container scaling and deployment is slowed down because of this reason.

While comparing Docker Swarm with Kubernetes, the docker can deploy containers much faster and reaction times are fast to scale on demand.

Comparing high availability among docker swarm vs kubernetes 

Kubernetes offers high availability by tolerating the application failure as all the pods in kubernetes are distributed among nodes. Load balancing services in kubernetes detect unhealthy pods and get rid of them which ensures high availability.

In Docker Swarm, as the services are replicated in Swarm nodes, it also offers high availability. The Swarm manager nodes in docker swarm deal with the entire cluster and handle the resources of worker nodes’.

Comparing Container setup among kubernetes vs docker

Kubernetes utilizes its own YAML, API, and client definitions and each of these varies from that of standard docker equivalents.  This conveys that you cannot utilize Docker Compose nor Docker CLI to define containers. The switching platforms, YAML definitions and commands must be rewritten.

The Docker Swarm API will not enclose the whole Docker’s commands but offers much of the close functionality from Docker. It supports most of the tools that run with Docker. However, if Docker API is deficient of a particular operation, there doesn’t exist an easy way around it utilizing Swarm.

Comparing Load Balancing among docker vs kubernetes

In Kubernetes, the pods are exposed through service, which can be utilized as a load balancer within the cluster. Usually an ingress is utilized for load balancing.

Swarm mode consists of a DNS element that can be utilized for distributing incoming requests to a service name. Services are assigned automatically or can run on ports specified by the user.

Pros and Cons of Using Kubernetes

Advantages:

• Kubernetes is backed up by the Cloud Native Computing Foundation (CNCF).
• Kubernetes has a larger community among container orchestration tools which comprises over 50,000 commits and 1200 contributors.
• Kubernetes is an open-source and modular tool that works with any operating system.
• Kubernetes provides easy service organization with pods.

Disadvantages:

• The installation of Kubernetes is quite complex with a steep learning curve when you try to do it by yourself.
• Kubernetes still needs to have a separate set of tools for management, including kubectl CLI.
• Kubernetes has got the issues of compatibility with current Docker CLI and Compose tools.

Pros and Cons of Using Docker Swarm

Advantages:

• Installation of Docker Swarm is easy with a fast setup.
• Deployment is very simple and the Docker engine has the Swarm mode included in it.
• Docker Swarm has an easier learning curve.
• Docker integrates smoothly with Docker CLI and Docker Compose.

Disadvantages:

• Docker offers limited functionality.
• Docker has limited fault tolerance.
• Docker Swarm has a smaller community and project as compared to Kubernetes community.
• Services are scaled manually in Docker Swarm.

Similarities Between Kubernetes and Docker

Kubernetes and Docker share the following similar ideas:

• Both market leaders have implemented microservices-based architecture.
• Both Kubernetes and Docker have developed the open source community to work with the large open source projects.
• They are largely written in Go programming language, which allows them to be shipped as small lightweight binaries.
• They use human-readable YAML files to specify application stacks and their deployments.

In theory, you can learn about one without having a hint about the other. But practically, you will benefit a lot more when you start with the simple case of Docker running on a single machine, and then step by step you will comprehend how Kubernetes comes into play.

Conclusion:
It is understandable that these two market leaders in container management have got their own unique abilities which cannot be judged as one is good and other as bad. Both of them are designed and developed from different perspectives for different types of organization’s management and their related issues. Hence, users can choose either kubernetes or docker from their choice of preferences.