IT sector has attained an all-new level of awesomeness with the reference of time, and credit entirely goes to its cloud services. With the help of these, container orchestration and data management have become a piece of cake for managers. There are a lot of tools or services available in the market to handle these tasks.
However, the two most powerful IT cloud container management platforms are ‘Kubernetes’ & ‘Docker Swarm’. Both have unique specialties of their own, and they are being used across various industries around the world for different purposes. Let us understand these two platforms in a better way and explore the difference between them. The below one Kubernetes vs Docker swarm is the topic which we are going to deal with in this article.
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So, let us begin with the Kubernetes definition first, which I am going to talk about in the section below.
Kubernetes is basically a result of Google’s excellence in running production workloads. The gigantic IT firm has been working on this platform for the past 15 years. As per its official website, ‘Kubernetes is basically an open-source system that works for automating management, scaling & deployment of containerized applications. It works with a principle that allows it to scale & manage billions of containers without increasing the operations team. Furthermore, it is an open-source platform, by which, you can take all the advantages of hybrid, public, or on-premises cloud infrastructure. It also lets you effortlessly move workloads to where it really matters to you.
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Docker Swarm is basically a clustering and scheduling tool specifically for Docker containers. Working on the basic Docker API & networking, it allows users to drop the work anywhere they want. Docker Swarm works on the following principles that make it one of the best in the market.
Let us compare two of the most advanced, highly used, and gigantic platforms of cloud container management here, so that, it will help all the desired users to choose any one of them. Kindly take a glance at the below-given table to check your preferences.
|Application Definition||An application can be deployed using a combination of pods, deployments, and services in Kubernetes.||Applications can be deployed as services (or microservices) in a Docker Swarm. YAML files can be used to specify a multi-container. Furthermore, Docker Compose can deploy the application.|
|Installation & Set-up||It requires manual installation and serious planning to keep Kubernetes up and running. Installation instructions differ according to the operating systems and their service provider. Apart from this, you must also keep the cluster configuration in mind such as IP addresses of a node.||Installation is a bit easier in Docker Swarm as compared to the Kubernetes. Users will have to learn just a single set of tools in order to build upon the environment & configuration. Apart from this, Docker Swarm also offers the facility for a new node to join an existing cluster either as a manager or as a worker.|
|Storage||It automatically mounts the storage system of your choice, either from local storage, a public cloud provider (GCP or AWS), or a network storage system (NFS, iSCSI, Gluster, Flocker, Ceph, or Cinder).||Docker containers come with two options to store files in the host machine which allows the files to persist even after stopping the container: bind mounts & volumes. If you’re running Docker on Linux, you can also use a tmpfs mount.|
|Rolling Application Upgrades & Rollback||In Kubernetes, Rolling updates let deployments update to execute with zero downtime simply by updating the pods instances with new ones incrementally. Moreover, it also provides the facility to revert the Deployment update to the previous one.||In Docker Swarm, the user will need to update each and every micro application one by one. In case the operation gets crashed in the middle, it automatically stops and offers us time to manage things.|
|Working on two systems||It demands the knowledge of CLI (Command Line Interface) to run Kubernetes on top of Docker. Users must know Docker CLI to navigate within a structure and then supplement Kubernetes common language infrastructure to run for those programs.||As Docker Swarm is a tool of Docker itself, the same language is used to navigate within a structure. This offers variability and speed to this tool and gives Docker a significant usability edge.|
|Load balancing||Ingress is used as the most popular & most flexible method, which operates by means of a controller in a specialized Kubernetes pod. It comes with an Ingress resource—a bundle of traffic governing rules and a daemon that applies those rules at appropriate positions. The controller is blessed with built-in features for load balancing coupled with a few reasonably sophisticated capabilities.||This platform allows its load balancer to run on every available node. Moreover, it loads balance requests across every container on every host in the cluster|
|Auto-scaling for the application||The Horizontal Pod Autoscaling helps Kubernetes to scale the number of pods automatically in a replication controller, replica set, or deployment based on the CPU utilization.||There is no automatic scaling option available for Docker Swarm. However, users can use a code to do that auto-scaling task.|
|Scalability||Kubernetes is basically a complex yet all-in-one system as it offers a unified set of APIs and strongly guarantees regarding the cluster state that slows downscaling & container deployment.||Docker Swarm can simply deploy containers faster as compared to Kubernetes which allows fast reaction times to make growth on demand.|
|Health checks||Self-healing is one of the most admiring facilities in Kubernetes. It has a facility to restart the failed containers. Moreover, for a dead node, it also provides a facility of rescheduling and replacement of containers. Apart from this, it ends containers that do not respond.||Docker Swarm comes with native health check implementation after version 1.12. The HEALTHCHECK instruction declares the health check command that can be used to determine whether or not the service status of the container master process is normal.|
|High availability||All pods are simply distributed between the nodes that provide high availability by tolerating application failure. Its load-balancing services automatically detect unhealthy pods and remove them which supports high availability.||Docker Swarm also provides high availability as services can be replicated in Swarm nodes. Swarm manager nodes are responsible for the whole cluster and manage the resources of worker nodes in Docker Swarm.|
|Networking||Kubernetes network is flat, as it allows all pods to communicate with each other. Its model requires two CIDRs, in which, the first one requires pods to get an IP address, and the other is for services.||In Docker Swarm, an overlay network of services emerges from the combination of a node and a cluster. That overlay network spans each and every host in the Swarm. It then hosts only the Docker bridge network for containers. In this, users also get an option to encrypt container data traffic while making an overlay network.|
----- Related Article: Kubernetes Interview Questions and Answers -----
After comparing both the gigantic IT cloud container management weapons, let us take a look at the pros & cons of each one of them.
Let us take a look at the pros and cons of Docker Swarm below.
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After discussing so much about these two market leaders in container management, it is still a bit tough to say which one is good and which one is not. Both Kubernetes vs Docker Swarm platforms have their own uniqueness, which makes them a lot different from each other. Both of them have been developed for different kind of industries (i.e. their management type), hence, users must keep all the points in mind before choosing any one of them.
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Sandeep is working as a Senior Content Contributor for Mindmajix, one of the world’s leading online learning platforms. With over 5 years of experience in the technology industry, he holds expertise in writing articles on various technologies including AEM, Oracle SOA, Linux, Cybersecurity, and Kubernetes. Follow him on LinkedIn and Twitter.
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