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Docker Swarm, what we’re looking at in this article, is a container orchestration tool native to Docker that enables applications to run seamlessly across multiple nodes that share the same containers. In essence, you use the Docker Swarm model to efficiently manage, deploy, and scale a cluster of nodes on Docker. On top of your daily Free Learning eBook, you can access over 30 premium titles that we've handpicked for quality across a diverse range of tech. These are yours to access online forever with a free account.

Thanks to the popularity and widespread use of Kubernetes, Cloud Native Computing Foundation (CNCF) and the Linux Foundation created two Kubernetes certifications to standardize the training and certifications for engineers who want to expand and illustrate their knowledge on the platform.

This article will explain the two Kubernetes certifications and exams, explore benefits to certification, and describe how to get certified.

(This article is part of our Kubernetes Guide. Use the right-hand menu to navigate.)

What are the Kubernetes certifications?

There are two Kubernetes certifications: the Certified Kubernetes Administrator (CKA) and the Certified Kubernetes Application Developer (CKAD).

Candidates are awarded the certification upon passing the exam. In order to pass these exams, a candidate must show their understanding of Kubernetes and how its components tie together. All the questions are practical, not multiple choice, so you cannot simply guess the answers.

Certified Kubernetes Administrator (CKA)

The CKA tests your ability to deploy and configure a Kubernetes cluster as well as your understanding of core concepts. Candidates have three hours to take the exam and must score 74% or higher to earn the certification.

The CKA exam tests the following areas:

• 8% – Application lifecycle management
• 12% – Installation, configuration & validation
• 19% – Core concepts
• 11% – Networking
• 5% – Scheduling
• 12% – Security
• 11% – Cluster maintenance
• 5% – Logging/monitoring
• 7% – Storage
• 10% – Troubleshooting

Certified Kubernetes Application Developer (CKAD)

The CKAD tests your ability to deploy and configure applications running on the Kubernetes cluster and your understanding of some core concepts. You’ll have two hours to complete the CKAD exam. Scoring a 66% or higher means you’ve passed.

For the CKAD exam, you will be tested in the following areas:

• 13% – Core concepts
• 18% – Configuration
• 10% – Multi-container pods
• 18% – Observability
• 20% – Pod design
• 13% – Services & networking
• 8% – State persistence

Benefits of Kubernetes certification

Why bother taking a Kubernetes certification exam? If it seems like a lot of work, you’re right. But that hard work is worth it for plenty of folks. Engineers with k8s certification reap plenty of benefits:

• Stand out from the pack. A Kubernetes certification makes your resume look good and stand out from the competition. As companies rely more and more on k8s, your expertise will be an immediate asset.
• Get a pay bump. A top certification like the CKA or the CKAD gives you mighty potential for a better salary. Passing these exams is not an easy task, so companies seeking k8s engineers are willing to pay more because the certifications show that you’re not only experienced, but you truly understand the platform.
• Achieve personal growth. Passing these exams is rewarding on a personal level: you sacrificed free time and fun to study and prepare, so passing the exam is rewarding in itself. Next, you may even move onto another skillset to focus on.
• Become a Kubernetes expert. After passing the exam, Kubernetes concepts become simple and almost second-nature. After the frustration you may experience as a k8s newcomer, the pleasure of understanding it is worthwhile and priceless.
• Diversify and expand your knowledge. The k8s architecture was built on 12 factor app principles, so by becoming k8s certified, you’ve got a good foundation in the 12 factor app principles, which goes supports a variety of SaaS applications. Talk about growing your skillset.

Preparing for Kubernetes certification exams

Like any exam, preparing is not easy but it isn’t rocket science. You’ll need plenty of time both to study and to practice—many successful engineers take about four months to prepare, studying for 2-3 hours daily. Remember that the CKA and the CKAD aren’t the same. The CKA covers a lot of cluster-related components, installation, and configurations. The CKAD, on the other hand, doesn’t go into cluster configurations, but does require full understanding of how clusters work.

Below, I have listed steps for preparing for the exams.

• Get familiar with Kubernetes and what makes up a cluster.
• Try installing a cluster from scratch. I used Kelsey Hightower’s Kubernetes the Hard Way, which is probably the best tutorial on how all the components come together.
• Understand the concepts and how to actually use the cluster; start with this page for plenty of documentation on k8s concepts.
• Follow the tasks provided by Kubernetes here and here. This step provides actual use cases and examples.
• Experiment with kubectl to parse results. This page has helpful commands for advanced parsing and Kubernetes also has related information.
• Watch this webinar series on concepts that apply to both exams.
• Practice, practice, practice. Without hands-on experience and practice working with and deploying to a cluster, the exams will be very difficult to pass. A good way to practice: use a test application and deploy that to your running cluster, then try to achieve certain goals using that application. There are test applications aplenty if you do not have a current one. Check out Minikube if you don’t have a running k8s cluster.

Making the decision

If you’re still debating whether to dive in on a k8s exam, remember that the CKA and the CKAD are both useful and highly sought-after certifications. They’ll boost your resume and improve your opportunities. Though the test is difficult, it’s for a good reason: the Kubernetes platform requires deep theoretical understanding as well as actual use in a production environment—passing the exam means you can be confident that you’ll apply that knowledge in a real-world scenario.

One last tip: when you register for the exam, you get one free retake. Failing the exam is possible, but the free retake means you can get familiar with the type of questions asked and better prepare for the second go-round. Good luck!

When deploying applications at scale, you need to plan and coordinate all your architecture components with current and future strategies in mind. Container orchestration tools help achieve this by automating the management of application microservices across multiple clusters. Two of the most popular container orchestration tools are Kubernetes and Docker Swarm.

Let’s explore the major features and differences between Kubernetes and Docker Swarm in this article, so you can choose the right one for your tech stack.

(This article is part of our Kubernetes Guide. Use the right-hand menu to navigate.)

Kubernetes overview

Kubernetes is an open-source, cloud-native infrastructure tool that automates scaling, deployment, and management of containerized applications—apps that are in containers.

Google originally developed Kubernetes, eventually handing it over to the Cloud Native Computing Foundation (CNCF) for enhancement and maintenance. Among the top choices for developers, Kubernetes is a feature-rich container orchestration platform that benefits from:

• Regular updates by CNCF
• Daily contributions from the global community

Docker Swarm overview

Docker Swarm is native to the Docker platform. Docker was developed to maintain application efficiency and availability in different runtime environments by deploying containerized application microservices across multiple clusters.
Docker Swarm, what we’re looking at in this article, is a container orchestration tool native to Docker that enables applications to run seamlessly across multiple nodes that share the same containers. In essence, you use the Docker Swarm model to efficiently manage, deploy, and scale a cluster of nodes on Docker.

Differences between Kubernetes and Docker Swarm

Kubernetes and Docker Swarm are both effective solutions for:

• Massive scale application deployment
• Implementation
• Management

Both models break applications into containers, allowing for efficient automation of application management and scaling. Here is a general summary of their differences:

• Kubernetes focuses on open-source and modular orchestration, offering an efficient container orchestration solution for high-demand applications with complex configuration.
• Docker Swarm emphasizes ease of use, making it most suitable for simple applications that are quick to deploy and easy to manage.

Now, let’s look at the fundamental differences in how these cloud orchestration technologies operate. In each section, we’ll look at K8s first, then Docker Swarm.

Installation

With multiple installation options, Kubernetes can easily be deployed on any platform, though it is recommended to have a basic understanding of the platform and cloud computing prior to the installation.

Installing Kubernetes requires downloading and installing kubectl, the Kubernetes Command Line Interface (CLI):

• On Linux, you can install kubectl using curl, native or other package management procedure as a snap application.
• On MacOS, kubectl can be installed using curl, Homebrew, or MacPorts.
• On Windows, you can install kubectl using multiple options, including curl , Powershell Gallery package manager, Chocolatey package manager, or Scoop command-line installer.

Detailed steps on kubectl installation can be found here.

Compared to Kubernetes, installing Docker Swarm is relatively simple. Once the Docker Engine is installed in a machine, deploying a Docker Swarm is as easy as:

• Assigning IP addresses to hosts
• Opening the protocols and ports between them

Before initializing Swarm, first assign a manager node and one or multiple worker nodes between the hosts.

Graphical user interface (GUI)

Kubernetes features an easy Web User Interface (dashboard) that helps you:

• Deploy containerized applications on a cluster
• Manage cluster resources
• View an error log and information on the state of cluster resources (including Deployments, Jobs, and DaemonSets) for efficient troubleshooting

Unlike Kubernetes, Docker Swarm does not come with a Web UI out-of-the-box to deploy applications and orchestrate containers. However, with its growing popularity, there are now several third-party tools that offer simple to feature-rich GUIs for Docker Swarm. Some prominent Docker Swarm UI tools are:

Application definition & deployment

A Kubernetes deployment involves describing declarative updates to application states while updating Kubernetes Pods and ReplicaSets. By describing a Pod’s desired state, a controller changes the current state to the desired one at a regulated rate. With Kubernetes deployments, you can define all aspects of an application’s lifecycle. These aspects include:

• The number of pods
• Images to use
• How pods should be updated

In Docker Swarm, you deploy and define applications using predefined Swarm files to declare the desired state for the application. To deploy the app, you just need to copy the YAML file at the root level. This file, also known as the Docker Compose File, allows you to leverage its multiple node machine capabilities, thereby allowing organizations to run containers and services on:

• Multiple machines
• Any number of networks

Availability

Kubernetes allows two topologies by default. These ensure high availability by creating clusters to eliminate single point of failures.

• You can use Stacked Control Plane nodes that ensure availability by co-locating etcd objects with all available nodes of a cluster during a failover.
• Or, you can use external etcd objects for load balancing, while controlling the control plane nodes separately.

Notably, both methods leverage using kubeadm and use a Multi-Master approach to maintain high availability, by maintaining etcd cluster nodes either externally or internally within a control plane.

External etcd topology (Image source)

To maintain high-availability, Docker uses service replication at the Swarm Nodes level. By doing so, a Swarm Manager deploys multiple instances of the same container, with replicas of services in each. By default, an Internal Distributed State Store:

• Controls the Swarm Manager nodes to manage an entire cluster
• Administers worker node resources to form highly available, load-balanced container instances

Scalability

Kubernetes supports autoscaling on both:

• The cluster level, through Cluster Autoscaling
• The pod level, with Horizontal Pod Autoscaler

At its core, Kubernetes acts as an all-inclusive network for distributed nodes and provides strong guarantees in terms of unified API sets and cluster states. Scaling in Kubernetes fundamentally involves creating new pods and scheduling it to nodes with available resources.

Docker Swarm deploys containers quicker. This gives the orchestration tool faster reaction times that allow for on-demand scaling. Scaling a Docker application to handle high traffic loads involves replicating the number of connections to the application. You can, therefore, easily scale your application up and down for even higher availability.

Networking

Kubernetes creates a flat, peer-to-peer connection between pods and node agents for efficient inter-cluster networking. This connection includes network policies that regulate communication between pods while assigning distinct IP addresses to each of them. To define subnet, the Kubernetes networking model requires two Classless Inter-Domain Routers (CIDRs):

• One for Node IP Addressing
• The other for services

Docker Swarm creates two types of networks for every node that joins a Swarm:

• One network type outlines an overlay of all services within the network.
• The other creates a host-only bridge for all containers.

With a multi-layered overlay network, a peer-to-peer distribution among all hosts is achieved that enables secure and encrypted communications.

Monitoring

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Kubernetes offers multiple native logging and monitoring solutions for deployed services within a cluster. These solutions monitor application performance by:

• Inspecting services, pods, and containers
• Observing the behavior of an entire cluster

Additionally, Kubernetes also supports third-party integration to help with event-based monitoring including:

Unlike Kubernetes, Docker Swarm does not offer a monitoring solution out-of-the-box. As a result, you have to rely on third-party applications to support monitoring of Docker Swarm. Typically, monitoring a Docker Swarm is considered to be more complex due to its sheer volume of cross-node objects and services, relative to a K8s cluster.

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These are a few open-source monitoring tools that collectively help achieve a scalable monitoring solution for Docker Swarm:

Closing thoughts

The greater purpose of Kubernetes and Docker Swarm do overlap each other. But, as we’ve outlined, there are fundamental differences between how these two operate. At the end of the day, both options solve advanced challenges to make your digital transformation realistic and efficient.

Additional resources

Docker Deep Dive Pdf Free Download Windows 10

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For related reading, explore these resources:

• Kubernetes Guide, a series of tutorials and articles