September 7, 2022
Majority of the time when people refer to Kubernetes vs Docker they most probably are referring to a similar but different term. In this article, we have covered the major difference between the two and how they help in solving problems.
If you are one of those who utilize container technologies, you must have come across Kubernetes and Docker. And you might be wondering which one to choose, what features they have. Keep reading to discover how these distinct technologies relate to each other and integrate effectively to develop, deliver, and scale containerized apps.
Table of Contents
To compare Docker vs. Kubernetes, you need to know what Container is.
Containers provide a crucial solution in the process of developing an application. Developers work in their own local development environment when writing code. Problems start to appear when they are ready to put that code into production. In reality, code that runs flawlessly on their machine doesn’t function in real time. There are many potential causes for this, including various operating systems, dependencies, and libraries.
Containers allowed you to decouple code from the underlying infrastructure it is operating on, which was a significant portability problem. The whole set of binaries and libraries a program needs to function properly could be packaged by developers into a compact Container image. Any computer with a containerization platform can run that Container in production. It helps greatly in scalability and portability.
Containers have a remarkably little footprint. The application and a list of all the bins and libraries it needs to execute are all that the Container takes to get started. Container isolation is performed on the kernel level without the requirement for a guest operating system, in contrast to virtual machines (VMs), which each include a full replica of a guest operating system. Libraries can also be distributed between containers, removing the need for 10 copies of the same library on a server and saving even more space. If we have three apps that are all using node and express, we don’t need to run three separate instances of those programs; instead, those programs can access bins and libraries. This allows applications to become embedded in self-contained environments, deployments can be made faster, development environments can have more parity, and unlimited scalability can be achieved.
Docker is a commercial containerization platform. It’s a toolkit that makes building, deploying, and managing containers for developers simpler, safer, and faster.
Even though Docker was initially an open-source project, it now also refers to Docker, Inc., the business that creates the paid Docker product. Whether developers use Windows, Linux, or macOS, it is now the most well-liked tool for constructing containers.
Before the 2013 launch of Docker, container technologies had been around for decades. Linux Containers, also known as LXC, were the most popular in the beginning. Although Docker was originally based on LXC, it swiftly overtook LXC to become the most widely used containerization platform thanks to its specialized technology.
One of Docker’s most important features is portability. Any desktop, data center, or cloud environment can run Docker containers. An application can continue to function while one of its components is getting updated or getting fixed since only one process can execute in each Container.
The following are some of the vocabulary and utilities frequently used with Docker:
The runtime environment known as Docker Engine enables programmers to create and operate containers.
A straightforward text file that specifies each step of creating a Docker container image, including the OS network requirements and file locations. In essence, it is a set of instructions that Docker Engine will follow to put the image together.
A tool for creating and operating multi-container applications is Docker Compose. It creates a YAML file to list the services that are included in the application and uses the Docker CLI to deploy and execute containers with only one command.
A platform for scheduling and automating the deployment, management, and scaling of containerized applications is called Kubernetes. A “cluster” is the name for the multiple container architecture in which containers function. There is a container in a Kubernetes cluster acting as a control plane that schedules workloads for the remaining containers-or worker nodes.
The master node selects how to assemble apps (or Docker containers), where to host them, and how to orchestrate them. By organizing the containers that constitute an application into clusters, Kubernetes helps with service discovery. In addition, it allows administrators to manage large quantities of containers at any point in their lifecycle.
In 2014, Google released Kubernetes as an open-source project. As of now, it’s managed by the Cloud Native Computing Foundation (CNCF). Kubernetes is popular for container orchestration in production environments due to its extensive capabilities, thriving open-source community with thousands of participants, and portability across multiple public cloud providers (including IBM Cloud, Google Cloud, Azure, and Amazon Web Services).
Kubernetes | Docker |
Open-source: You can use it on-premises, in a public cloud, or in a hybrid cloud, depending on what you want. | The convenience of configuration: Docker makes it easy to deploy your code in a wide range of environments in less time and effort. Infrastructure specifications are no longer tied to the application environment, simplifying and speeding up the configuration process. |
Interaction: Kubernetes can manage multiple clusters simultaneously. Scaling is possible both horizontally and vertically. | Use Swarm: It’s a tool for clustering and scheduling Docker containers. Docker APIs are implemented by Swarm as a frontend. It also allows us to control clusters of Docker hosts as a single virtual host, enabling us to access various tools for the controller. Pluggable backends are enabled by this self-organizing group of engines. |
Self-monitoring: It allows you to self-monitor since it continually checks the adequacy of the nodes and the container. When a container or a node dies, Kubernetes will restart, replace, or reschedule it, and it will kill containers that do not respond to user-defined health checks. | Ensures security: Docker allows us to store secrets within the swarm itself. Afterward, select which secrets should be accessible to services. A few crucial commands are included in it, such as secret inspections and secret creations. |
Features automated scalability: Adapts to heavy loads by automatically starting new containers based on CPU consumption, memory levels, or custom measurements. | Service: A service defines the state of a container within a cluster by defining a list of tasks. Swap schedules each task according to the number of containers it should run. |
Dynamic Volume provisioning Facilitates the creation of storage volumes without requiring cluster administrators to contact their storage providers or construct objects. | Increase in Productivity: By facilitating configuration & efficient deployment of applications, Docker has enabled applications to run in an isolated environment, thus reducing resources. |
Orchestration of storage: Installs persistent storage systems in the cloud or on-premises to minimize lag and enhance user experience. | It is Lightweight and Portable: Containerized applications are lightweight and portable, and they run regardless of operating system (where Docker is available). Multiple containers can be managed seamlessly and concurrently using Docker containers. |
Automation of rollouts and rollbacks: Applications are updated and monitored for issues, and changes are rolled back if something is wrong. | Agile app development: CI/CD processes, agile methodologies, and DevOps can be implemented more easily with containerization. As business needs change rapidly, containerized apps can be tested in one environment and deployed in another. |
The majority of the time, when people use the phrase “Kubernetes vs. Docker” they mean “Kubernetes vs. Docker Swarm” The latter, which uses its API and is strongly integrated into the Docker ecosystem, is Docker’s native clustering solution for Docker containers. Similar to most schedulers, Docker Swarm offers a mechanism to manage several containers dispersed across server clusters. Its filtering and scheduling system makes it possible to choose the best cluster nodes for container deployment.
Kubernetes vs. Docker. From what we have shared till now, we hope you have gotten a clearer picture that it is not an either/or question.
Kubernetes has the opportunity to coordinate and manage all of your container resources from a single control plane, even though containers promise to allow you to write code once and execute it anywhere. All of the Kubernetes nodes that run your containers benefit from its assistance with networking, load-balancing, security, and scaling. Additionally, Kubernetes offers built-in isolation mechanisms like namespaces that let you organize container resources based on things like access permissions and staging environments. Without having to mock up the entire application in their development environment, these constructs make it simpler for IT to give developers self-service resource access and for developers to collaborate on even the most sophisticated microservices architecture. Cloud-native applications can be deployed more quickly and more scalable by combining DevOps practices with Kubernetes and containers.
At the end of the day, it’s up to your team to determine what type of tools it needs to accomplish its goals. Make sure to do a complete thorough analysis of different technologies’ features and how compatible they can be if used collectively. This can turn out well than you imagine.
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