Overview of container orchestration systems
Modern cloud infrastructures rely heavily on container orchestration systems. So, what exactly are they? In this article, we are going to explore this compelling concept as well as examine two of the biggest brand names in the container orchestration world: Kubernetes vs Docker. While not exactly rivals, both solutions offer their comprehensive set of pros and cons that provide a combination of attributes that signify their essence and relevance in the industry.
Container systems exist as a solution to package software. Container systems are remarkable because they are predictable, repeatable, and permanent. As a user, you don’t want to experience unexpected errors when transferring software from one machine to another, or between environments. Thus, container orchestration systems have become a must-have to serve as the building block and improve a cloud architecture.
Software packages, labeled as “containers” are isolated segments of an application that can communicate with each other via well-defined channels. All containers run in a single operating system kernel and are considered more lightweight than virtual machines.
In an industry where microservices have become the norm for numerous architectures, there’s a noteworthy spot for containers to enable quick elasticity and separation. All of an application’s code, libraries, and dependencies are nicely wrapped up in a single container that is a fixed item. Next, we are going to explore the importance and rise of container orchestration systems in the current technology environment.
The importance and the rise of container orchestration systems
While the concept of containers has been around for over more than a decade, its popularity is relatively recent. While multiple operating systems that are based in Unix held built-in support of containers, it was Docker that revolutionized the container game, making containers manageable and accessible to development teams and IT operations teams.
The industry has associated the “containerization” concept as an equivalent concept of operating-system-level virtualization. Containers are efficient, lightweight, effective, and swift. Therefore, it is no wonder that they’ve experienced a popularity rise over traditional virtualization solutions in recent years.
Containers enable applications to be enclosed in self-contained environments which, as we’ve mentioned before, results in quick deployments, scalability, and tight-knit management between development environments.
Containerized applications are easily transferred and can run anywhere without the need for a full-fledged virtual machine or other dependencies. Container orchestration systems come into play when there are multiple containers involved. Container orchestration is the process of deploying multiple containers to implement an application through automation.
As previously mentioned, containers are being used more frequently than ever before to package code and other dependencies, but are also being significantly leveraged by DevOps processes, making them an integral and all-around solution for automation and continuous integration/deployment channels.
With the rise in interest and usage of container systems, the Open Container Initiative was formed to create open industry standards around container image formats and runtime. This initiative was originally created by Docker and other industry leaders in the market.
The importance of container systems is significant enough that it has influenced traditional Platform as a Service (PaaS) architectures due to its open and efficient model to package, deploy, isolate, discover, scale and roll-out. As of late, most PaaS solutions embrace containers or are built on top of container orchestration, which has played a key role in almost every aspect of modern software development and deployment.
What is Kubernetes?
Kubernetes is an open-source system used to automate deployment, scale, and manage container applications. Overall, the purpose of Kubernetes is to group the containers that constitute an application into logical units for easy management and discovery. Kubernetes has over 15 years of experience t running production workloads at Google and pairs that experience with high-class ideas and practices for the community.
Kubernetes was designed by Google but it now has its home in the Cloud Native Computing Foundation. Since it was initially released, Kubernetes works with an array of container tools such as Docker to provide a comprehensive platform that orchestrates container activities across clusters of hosts. It is geared to run enterprise-class IT workloads that are also cloud-enabled and web-scalable.
By grouping containers into logical units, Kubernetes aims to provide mechanisms that collectively provide for the deployment, maintenance, and scaling of applications. The fundamental scheduling unit in Kubernetes is called the pod. The pod is made of one or more containers that can share resources within the same host machine. Each pod is assigned an IP address within a cluster to enable applications to use ports seamlessly.
Kubernetes is geared to drive the adoption of containers in both enterprises and emerging startups. The Kubernetes architecture is crucial in this adoption by making the process flexible and efficient.
Kubernetes is an advocate of the master-slave architecture. A Kubernetes cluster is comprised of at least one master and several compute nodes. The master exposes the API, schedules deployments and manages the cluster. Each compute node runs a container runtime alongside an agent that is in constant communication with the master. In essence, nodes in Kubernetes are the manpower of the cluster by exposing compute, networking and storage resources to applications.
The Kubernetes fundamental unit of management is called a pod. A pod is a collection of one or more containers that acts as the boundary for containers that share identical context and resources. The mechanism behind the grouping of pods is what differentiates between containerization and virtualization. This mechanism makes it possible to run several processes simultaneously. Pods are scaled by creating replica sets that are meant to secure the deployment of a specified number of pods.
Kubernetes objects such as pods, replica sets, and services are submitted to the master so they can schedule a specific pod on a specific node. Thus, the node can extract images from the container image registry and coordinate the runtime to launch the container.
This Kubernetes architecture is what makes the system modular and scalable, creating a cohesive environment for applications and the underlying infrastructure.
What is Docker?
Many industry experts consider Docker as the most popular solution in terms of container platforms. Docker is an open-source container platform program that helps build, manage, and secure all applications, leading them from traditional applications to cutting-edge microservices, deploying them virtually anywhere they are needed.
Docker enables users to start with legacy or new applications by using operational models or any available operating system across infrastructures, whether on-prem or in the cloud. It unifies processes and aligns to existing IT operations to get applications to the market faster.
Since its release in 2013, Docker has been used to run containers of software packages and it was primarily designed for Linux. Docker is written in Go and leverages multiple features of the Linux kernel to deliver functionality.
Docker is known for providing the right tools and a platform to manage the full lifecycle of containers by:
- Developing an application and its supporting components by using containers.
- Using containers as the key unit to distribute and test an application.
- Deploying an application into a production environment, as a container or orchestrated service.
Based on a client-server model, which we will detail in the architecture section, Docker engine has these major components:
- REST API
- Command line interface (CLI) client
With these elements in place, Docker is powerful enough to streamline effectively the development lifecycle of applications, by enabling developers to work in environments with local containers. Containers are particularly relevant and important in the continuous integration and continuous delivery workflows.
Many consider Docker a computer within a computer. Docker is designed to develop, ship, and run applications by separating applications from the infrastructure and delivering the software swiftly. By leveraging Docker’s methodologies for shipping, testing, and deploying code quickly, users reduce delay times between writing code and running it in production.
To achieve this, the Docker architecture is devised in a client-server model. In essence, the client communicates with the Docker daemon (a computer program that runs as a background service), which is in charge of the building, running, and distributing of Docker containers. The client and the daemon communicate using REST API via UNIX sockets or a network interface.
Docker’s architecture is comprised of these key components:
- Docker daemon: Docker’s daemon (a computer program that runs in the background) is named dockerd. It is a persistent process that manages Docker containers and operates container objects. It listens to requests sent via the Docker Engine API and it provides a command-line interface that enables users to interact with dockerd. The daemon listens to Docker API requests and manages objects (images, containers, networks, and volumes) and it also communicates with other daemons to manage Docker services.
- Objects: Docker objects are entities that are used to assemble an application. The main Docker objects are images, containers, and services.
- Images: Read-only template used to build containers and store and ship applications.
- Containers: An encapsulated and runnable environment or instance of an image that runs applications and is managed by Docker API or CLI.
- Services: It allows containers to scale across multiple dockerds, that when working collectively are known as a swarm and is basically a collection of cooperating dockerds that communicate via the Docker API, with multiple managers and workers.
- Registries: Repository of Docker images where clients connect to download images for use or upload. Registries can be public or private – the most well-known public registries are Docker Hub and Docker Cloud. Docker Hub is a public registry and is of great use as Docker is configured by default to search for images on Docker Hub.
- Docker client: The client is the primary method for users to interact with Docker. The client sends commands for execution by using the Docker API. The client is capable of communicating with more than one daemon.
Docker Swarm is Docker’s native clustering solution for Docker containers that turns a group of Docker engines into a single virtual Docker engine. Docker Swarm leverages its own API and enables users to create discovery tokens, list nodes in a cluster, and run Swarm containers.
Comparing Container Orchestration Systems: Kubernetes vs Docker
As we mentioned before, in the concept of Kubernetes vs Docker, there is no real rivalry. If any, the real rivalry occurs in Docker Swarm vs Kubernetes, which are both container management and orchestration engines that help users deploy containers, automate updates, monitor performance, and perform failover procedures.
As previously stated, in the realm of Kubernetes vs Docker, these two players are fundamentally different technologies that, rather than compete, rely on each other on the road to success. Docker is a platform and tool that enables users to build, distribute, and run Docker containers. On the other hand, Kubernetes is a system that can be used for Docker containers.
Comparing Docker Swarm vs Kubernetes, Kubernetes is a more comprehensive solution than Docker Swarm, making it easy for users to build on top of Kubernetes clusters. By itself, Kubernetes is not a robust solution but it works pretty well with Docker to facilitate the management and deployment of containers in distributed architectures.
Next, we are going to explore both the pros and cons of Kubernetes and Docker to get a better understanding of what each solution entails.
Pros and cons of Kubernetes
- Logging and monitoring: Kubernetes offers support of multiple versions of logging and monitoring when services are deployed within the cluster.
- Speed: Kubernetes is the premium choice to continuously deploy features without any downtime. It is capable of updating applications with constant uptime.
- Declarative configuration: The system communicates the state it is in to inform users where it should be to avoid errors.
- Scale: Due to the immutable and declarative nature of Kubernetes, it is easy for the system to scale through these following methods:
- Horizontal infrastructure scaling: Operations performed at the individual server level for horizontal scaling.
- Auto-scaling: Users can modify the number of running containers based on CPU usage or other metrics.
- Manual scaling: Users scale running containers via a command or in the interface.
- Replication controller: It ensures the cluster has equivalent pods in a running condition and removes any extra pods or adds them as necessary.
- Storage: Kubernetes shares data across containers, storing data remotely to keep it intact until the user decides to delete it.
- Setup: Kubernetes users different setup processes for each operating system, which adds complexity to the process. While users can leverage online resources, it is still rather challenging to build custom environments.
- Migration: If an application is clustered or stateless, it will cause extra pods to not be properly configured, which results in rework of the configuration.
- Compatibility: Kubernetes is not compatible with any existing Docker CLI and Compose tools.
Pros and cons of Docker Swarm
- Installation: Docker Swarm uses the CLI to run all aspects of its programs, making it easy for users since they only have to learn one set of tools to build environments and configurations. Additionally, since Docker Swarm runs on top of Docker, it requires very little configuration and setup.
- Familiarity: Since Docker Swarm runs on top of Docker, it is easy for users to feel at home while using Docker Swarm to work with other Docker tools. By using Docker Swarm, users operate with the same Docker CLI, which provides an easy-to-use command structure.
- Speed: Docker Swarm provides a quick-paced environment that boots up a virtual machine and lets an app run in a virtual environment quickly.
- Strong documentation: Docker stands out in a crowd thanks to its comprehensive documentation efforts. It continuously updates its documentation to stay relevant and accurate to the latest information available.
- Version control: Users can track container versions with ease to examine discrepancies between prior versions.
- Platform-dependency: Docker Swarm supports multiple operating systems but it is a Linux platform that requires the use of virtual machines to run in non-Linux platforms.
- Storage: Docker Swarm is not the easiest solution to use to connect containers to storage.
- Monitoring: Docker Swarm is not capable of offering advanced monitoring and while there are external tools available to help with this task, it is not feasible to collect more data in real-time by using Docker.
How they fare against each other
While both solutions work on different levels, they are great allies to each other. Both Kubernetes and Docker have seen an explosion in their popularity and it is only bound to grow with the impending transformation of the technology market. When used together, both tools bring out the best in each other to develop cutting-edge cloud architectures.
In the list of differences between Docker and Kubernetes, Kubernetes fares best if users want a mature deployment, fast and reliable response times, efficient development of complex applications with high resource computing, and the use of big clusters. On the Docker side, it is better to leverage this solution if users want to start a process without investing much time on configuration and installation, develop basic and standard applications, test and run the same application on different operating systems, and want docker API experience and compatibility.
To sum things up, use Kubernetes for complex apps and Docker Swarm for small-scale apps.
Future trends of Docker and Kubernetes
In their particular niches, both Kubernetes and Docker are considered top-class solutions. We emphasize this point because, in terms of future trends, both Kubernetes and Docker have a lot to look forward to and they must rely on their strengths to evolve with the industry.
These are the future trends to keep an eye on:
- Microservices: This trend is a top contributor to the rise in container usage. As we know, Microservices break down applications into small, lightweight, and independent services. With this definition in mind, containers are a great fit to support these types of applications in a production environment. Thus, it will be no surprise to see more and more applications based on microservices that use Docker and Kubernetes.
- Multi-cloud environments: Single-cloud solutions are steadily becoming a thing of the past. Nowadays, organizations look for multi-cloud environments where they can leverage more options and decrease their dependency on a single vendor. Thus, users can run Docker and Kubernetes in multi-cloud environments.
- Support: With loyal communities that rally behind each one, both Kubernetes and Docker are experiencing a surge in an active user base that frequently updates information. With this supportive community, it is no wonder that these solutions are on the road to becoming more common in both large and small business organizations.
- App modernization: Containers are a superb option to help with cloud migration and app modernization of native apps and legacy apps.
Svitla Systems has in its ranks teams of talented professionals who are not only extremely knowledgeable about Kubernetes and Docker, but also cloud environments.
With expert teams that are familiar with these solutions, Svitla Systems is always looking for ways to help clients with new capabilities and emerging platforms, delivering talented software teams that can utilize the potential Kubernetes and Docker offer.
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