Containerization with DevOps processes has accelerated building, deploying, and scaling applications on cloud systems. Containers have also been a boon for microservices-based applications, where the overall application service may consist of two, three, or smaller applications. The intentional independence of those API-coupled little services means that each can be updated, scaled up or down, and even completely changed as the requirement changes. However, these systems’ speed, responsiveness, and flexibility also bring additional complexity that is infeasible when managed by following traditional manual IT processes.
Enter container orchestration engines (COEs) such as Kubernetes and Docker Swarm into the application management processes. Both are the leading container management automation tools renowned for handling the complexity of web-scale applications with ease.
What is Kubernetes?
Kubernetes (also known as K8s) is a COE initially developed by Google based on a system used to run containers at web-scale. Later, Google provided K8s to CNCF (Cloud Native Computing Foundation) as an open-source project for further development and improvements. It is written in the Go language. Kubernetes can be deployed on almost any type of infrastructure – anything from your laptop, local data center to the scale of a public cloud. It is even possible to have Kubernetes clusters spread across different infrastructures, such as on-premise, public cloud, and hybrid cloud.
Kubernetes comes with numerous container management “intelligence” built-in. Therefore, this COE allows placing containers on appropriate nodes based on resource requirements. It helps scale applications up and down in response to load, load balancing across applications, again facilitating restarting or replacing stalled and failed containers, and lots more functions and capabilities to developers.
What is Docker Swarm?
Docker Swarm or just Swarm is yet another popular open-source COE. The company that created the Docker container also created Docker Swarm as a Docker-native orchestration solution. One of the benefits for users of Docker containers is that it provides smooth integration. Swarm uses the same command-line interface (CLI) used for Docker containers. Developers using Docker can leverage backward compatibility with other Docker tools. Swarm is highly scalable, extremely simple to deploy, provides container management features such as load balancing and autoscaling.
Kubernetes vs. Docker Swarm
Although both Kubernetes and Swarm are open-source, run Docker containers, and provide similar functionality, several key differences exist in how these tools operate. Below, look at some notable differences and consider the pros and cons of the different approaches.
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Technical Comparison Between Kubernetes and Docker Swarm
Installation
Kubernetes: Installing Kubernetes requires some decisions, for example, which networking solution to implement, and the configuration, at least initially, must be manually defined. Information about infrastructure is also required ahead of time and includes roles, number of nodes, and node IP addresses. The most exciting thing is that most of the major cloud providers have hosted Kubernetes versions that take away most of the tough jobs involved in building your own system.
Docker Swarm: Installing Docker Swarm is as easy as installing any specific application with the package manager. To create a cluster, you only need to deploy one node and ask it to join the cluster. New nodes can be joined with worker or manager roles, which provides flexibility in node management.
Application Deployment
Kubernetes: Applications in Kubernetes are deployed as multi-container “pods”. A pod minimally includes an application and a network service container. Multi-container applications can be deployed simultaneously in a pod. Kubernetes deployment and Services provide the abstraction that helps to manage multiple Pod instances.
Docker Swarm: Multiples (replications) of single container applications are deployed and managed as “swarm” in Docker Swarm. Developers use YAML to define an application’s configuration file, and then Docker Compose installs multi-container applications.
Container Setup
Kubernetes: The goal of Kubernetes at the beginning of its development was to support all available container types, including Docker. This is the reason Kubernetes’ YAML, API, and client definitions differ from those used by Docker. As a result, it is possible to run CRI-O and Containers Runtime-compatible containers on Kubernetes alongside running Docker containers.
Docker Swarm: Docker Swarm was built as a “Docker Ecosystem” tool, supporting only Docker containers. Being native to Docker, it does not support other container runtimes.
Scalability & Autoscaling
Kubernetes: Kubernetes focuses on reliably maintaining cluster state, and the large, unified set of APIs makes container scaling and deployment slower than Swarm. Kubernetes comes with Cluster Autoscaling feature together with Horizontal Pod Autoscaler. It automatically scales up the cluster as soon as the system needs it and scales it back down to save money when the system doesn’t. That’s why Kubernetes is the best fit for projects to deal with predictable as well as unpredictable business growth.
Docker Swarm: Docker Swarm deploys containers much faster than Kubernetes, however; it doesn’t offer automatic and dynamic scaling. You need to use solutions like docker-machine to create machines on your infrastructure and link these to the existing Swarm cluster known as docker swarm join.
Networking
Kubernetes: Kubernetes is integrated with several networking technologies, with the open-source Calico and Flannel solutions being the most popular. With flannel, containers are connected via a flat virtual network, which allows all pods to interact with each other with restrictions set by the network policy. Developers can employ TLS security; however, they have to follow manual configuration to implement it.
Docker Swarm: Nodes are connected via a multi-host Ingress network overlay that links containers running on all cluster nodes. A node joining a Swarm cluster generates an overlay network for services across all Swarm hosts and a host-only Docker Bridge network for service containers. It is possible to configure the inter-container network further. Authentication (TLS) between nodes is configured automatically.
Load Balancing
Kubernetes: In Kubernetes, pods are exposed through a service, allowing them to be implemented as load balancers inside a cluster. It has single DNS name and container applications are accessed through IP addresses and HTTP route. Usually, Ingress is used for load balancing.
Docker Swarm: Swarm mode comes with a DNS element that can be used to distribute incoming requests on the name of the service. Thus services can be assigned automatically or can act on ports pre-specified by the user.
High Availability
Kubernetes: Kubernetes provides fairly high availability as it distributes all pods among nodes. This is achieved by absorbing the failure of an application. High availability in Kubernetes is achieved through a replication controller that also maintains pod health across nodes.
Docker Swarm: Docker also provides high availability architecture as all services can be cloned to Swarm nodes. Swarm Manager nodes manage worker node resources and the entire cluster.
So which COE should you choose – Kubernetes or Swarm?
There emerged many situations and deployment needs in a legacy application modernization where, using Kubernetes makes sense due to a number of features such as self-healing, horizontal scaling, batch execution, automatic bin packing, automated rollouts and rollbacks, and many others. Kubernetes is considered down only because it’s a bit more complex and its learning curve is steeper. Once you learn the ins and outs of the Kubernetes, it will help set up better for handling the unknown. Kubernetes will put you in a good position even in scenarios when you don’t know everything that will be thrown your way in the future during project development.
The simplicity of Docker Swarm makes it a good choice for running production and non-production canonical deployments. But for proof-of-concept and other ad-hoc environment needs, there is no better option available than the Kubernetes cluster.
