Docker and Kubernetes have taken the software world by storm. DevOps, containers, and container management are at the center of most conversations about what’s relevant to technology. Tooling and services that ease running software in containers, therefore, occupy the minds of developers. Great tools and platforms create options and possibilities. They also create challenges in understanding available choices, though.
If you have difficulty in staying up to date regarding modern tooling and infrastructure, you’re not alone. It’s hard to know what’s available and which to use.
Docker, Docker Swarm, and Kubernetes are tools that make life easier for technology professionals. To make use of these amazing resources, you need to understand their relative strengths and capabilities. Read further to find out differences and similarities between Docker Swarm and Kubernetes, as well as situations where you’d choose one over the other.
The Docker Engine makes it straightforward to build images that contain all the runtime dependencies your application needs. It then makes it easy to run the processes that build your system into a cohesive whole. This enables a positive shift in the way team members relate to one another.
By writing a Dockerfile that scripts the building of a runtime environment for an application, developers package everything needed to run a given process. This means programmers include not only the code they write, but also everything a process needs to execute. The resulting image is a unit that’s easy to deploy and run as a container.
When deployments are easy and repeatable, the operations job gets easier. Team members can perform any role. There doesn’t need to be a distinction between development and operations. This contrasts with tiresome processes of operations teams trying to build suitable environments from written documents. Developers better test the runtime environment for the application. This means fewer surprises and better relationships among team members.
Docker effectively ends the “works on my machine” phenomenon.
Containers thus render team members better able to understand each other’s perspectives. They do this by improving and simplifying application delivery. Scripts replace documents for delivery. Teams now apply the development mindset to operations challenges and the operations mindset to development challenges. This is the true spirit of DevOps.
Docker solves the problem of making sure everything is in place for a process to run, but it doesn’t have much to say about how a container fits into a full system. It also doesn’t address questions about load balancing, container lifecycles, health, or readiness. And it’s silent about how to surface a scalable, fault-tolerant, and reliable service. Docker can run a workload in a container, but all it knows about the lifecycle of a container is that it starts and ends with a given process.
Building and running containers are foundational to modern software infrastructure, development, testing, and deployment, but it’s not the end of the story.
If you think about containers as the infantry in an army intent on serving a system, you quickly realize you need a way to manage coordination and command of those troops. Containers generally do one thing well. An orchestrator brings together the containers enlisted in the effort into a cohesive whole system. Orchestration is the mastermind, focused on the bigger picture.
Technical teams have many concerns. Among them are availability, fault tolerance, scale, networking, discovery, and cost. Over time, teams have addressed these problems in ways that have become standard. For instance, load balancing addresses scale, fault tolerance, and partition tolerance. Then we have instrumentation, which deals with visibility and health monitoring. Finally, virtualization solves problems with resource utility and flexibility.
Orchestration of workloads in containers is an umbrella for managing all of these concerns and remedies in an automated way.
Operations specialists have traditionally dealt with creating environments to handle these concerns and run application workloads. In modern environments, teams may not have purely operational specialists. Further, the number of components making up a system may be beyond the capacity of management without automation. Finally, increasing emphasis on continuous deployment makes critical the need for tooling for managing provisioning, deployment, monitoring, and resource balancing.
Container orchestration provides exactly this. This type of infrastructure shines in managing complex deployments. It enables handling many moving parts and keeping the operation up, healthy, and thriving. Orchestrators like Docker Swarm and Kubernetes solve the real needs of real teams for turning their desired state into reality. After reaching the desired state, they monitor for disruption to that state and restore it when there’s a deviation.
Because of this, orchestration engines provide valuable services. These services compare favorably to what would be provided by the ideal operations team. Such a team would be constantly vigilant, doing exactly what’s needed for making the applications work. And they’d do this with reliable, perfect, and well-understood communication.
Using orchestration gives you something of the sort via software instead of via an operations team.
Kubernetes is the gold standard for managing containerized workloads. Google engineers designed Kubernetes to automate deployment, scaling, and operations of application containers across multiple hosts. Its core philosophy is team-focused: teams can define the desired state of their deployment, and Kubernetes will bring the specified infrastructure into being. It will also maintain the desired state.
Kubernetes has an enormous community of support from people in organizations of many shapes and sizes, with numerous contributors. The largest providers of cloud infrastructure have dedicated Kubernetes offerings, making it straightforward and cost-effective to run Kubernetes.
Kubernetes was serving Google prior to becoming the open-source project it is today. It successfully handles legions of use cases and workloads for numerous organizations. And it’s a great choice if you’re looking for a mature and proven project and architecture.
Kubernetes is currently the most popular container orchestration platform. This popularity has been earned with success running in demanding conditions.
Some of the largest and most well-resourced companies are using and supporting Kubernetes. They’re committed to doing so for the foreseeable future and have made large bets on its future.
Docker Swarm is an alternative to Kubernetes. Like Kubernetes, it manages containers and turns the desired state into reality. It also fixes any future deviations from the desired state.
The Docker team has built it and consider it a “mode” of running Docker. Running in swarm mode means making the Docker Engine aware that it works in concert with other instances of the Docker Engine. This capability is included in the installation of Docker. The Docker command line interface enables, initializes, and manages Docker Swarm. For these reasons, you can use Docker Swarm if you have Docker installed with only a few Docker commands. It’s extremely appealing because of this simplicity.
The Docker Engine can join and leave swarms via commands at the Docker command line interface.
Both Kubernetes and Docker Swarm enable teams to specify the desired state of a system running multiple containerized workloads. Given this desired state, they turn it into reality by managing container lifecycles and monitoring their readiness and health of containers and services.
Both use multiple hosts to form a cluster on which the load can be distributed. Both use containers as the units of work, although Kubernetes has a concept of “pods” that are composed of one or more containers as a fundamental, atomic unit.
You tell the orchestrator the needs of your system, and it works to keep the system running as desired. It does so in a balanced, fault-tolerant way. This is an appealing way to work that takes much of the load off the shoulders of your team.
Like Kubernetes, Docker Swarm can run anywhere. Neither will lock you into a single vendor or cloud platform. You’re free to run them in the cloud or on-premise as you desire. You can even use them on your workstation for development and testing. The Docker Engine installation includes swarm mode on any platform. Docker Desktop now includes Kubernetes as well. It’s straightforward to use either or both on a workstation in a single-node cluster for development and testing.
With both, it’s easy to list and tail logs in your containers, and tools exist to aggregate logs and make this even easier. Further, for monitoring and improving application performance and quality, Stackify created Retrace. Check out the instructions here for setting up your Kubernetes cluster and pods to use Retrace.
The differences between Kubernetes and Docker Swarm are best summarized as a comparison between simplicity vs. complexity and completeness.
Kubernetes has been around longer and applied in many more use cases and conditions. For this reason, it has expanded to meet the needs of many organizations. As such, Kubernetes is more complete in its feature set than Docker Swarm.
With Kubernetes’ completeness of functionality and its flexibility to handle any situation comes complexity. It’s harder to learn Kubernetes than Docker Swarm. Discoverability can also be a problem. Kubernetes does so much that it’s hard to know what it can do and how to approach it. It takes time to get comfortable with Kubernetes and what it has to offer.
Swarm mode, on the other hand, is simple to set up and run. You can be off and running with creating services in moments. To manage a swarm, you use the same Docker command line interface as you use to build images and run containers on your workstation. This makes for a greater degree of approachability for Docker users.
Kubernetes uses a different command line interface. It has many similarities to the Docker interface, but it’s a separate executable with more commands to know. Kubernetes also has a vast array of configuration and authentication options. This gives much greater flexibility—but at the cost of having much more you need to know.
Therefore, consider Kubernetes a more fully-featured platform for handling any use case. Likewise, consider Docker Swarm a shorter path to productivity for more limited use cases.
Kubernetes is able to run your system in containers in the way you need it to run. It’s flexible to the point that you’re going to be able to make it do what you want, whatever that may be. However, it takes some time and learning to get comfortable and able to specify Kubernetes manifests. When you do, though, you’ll be able to tell Kubernetes the desired state of your containerized system. It will get you to that state and fix it if your system doesn’t stay in that state.
With popularity comes many perks. The incredible community around Kubernetes means you’ll be able to find the information and support you need.
The complexity of setting up Kubernetes is generally not a problem in cloud deployment scenarios because the major providers have offerings that take away significant portions of the setup required. They also have default configurations that are good for most needs, plus straightforward configuration options for customization. Further, the cloud provider offerings ease the need for setting up, for example, ingress, in Kubernetes. That’s because services can be specified with load balancer types that make use of capabilities of the various platforms.
Kubernetes does what you want to do—and does it well.
Docker Swarm builds on Docker and coordinates multiple instances of the Docker Engine. A swarm requires only a little more setup than installing Docker on more than one node. For these reasons, it doesn’t take much time or effort to get up and running with an orchestrator when using Docker in swarm mode.
Further, having an instance of Docker Engine participate in a swarm doesn’t render it useless as a standalone engine. For instance, if you join your workstation to a swarm, you can still use it to build images and run containers not subject to the swarm.
There’s never been a better time to be a developer. With great tools, like Docker, Docker Compose, Docker Swarm, and Kubernetes, you have an incredible array of capabilities and workflows at your fingertips, both for doing your own job in your own way and for working with your team.
Use of Swarm or Kubernetes doesn’t have to be mutually exclusive. In fact, Docker Enterprise sets up clustered nodes as both parts of a Kubernetes cluster and parts of a swarm by default. You benefit from the flexibility to create environments in different ways with varying degrees of complexity and management required.
If your production deployment is ultimately going to be on Kubernetes, you usually want to test on Kubernetes. Nonetheless, for proof-of-concept and ad-hoc environments, there are cases where the simplicity of a swarm is beneficial, even if you’re using Kubernetes for your main environments.
The ubiquity of Kubernetes and the commitment of the major cloud providers to creating and maintaining first-class offerings mean it’s a safe choice to stake your production infrastructure on Kubernetes. Additionally, Kubernetes is a complete management system with role-based authorization and namespaces for confining portions of a system into bounded contexts.
For a large deployment with complex needs, especially with multiple teams, arguing against Kubernetes is harder than arguing for it. It’s flexible and able to handle what you need admirably. Kubernetes is a great choice for all but the smallest and simplest of workloads.
Kubernetes also handles controlling authorization, volumes, and cloud service integration better than Docker Swarm. And it provides flexible ways to configure probes to check that your containers are alive, ready, and healthy.
Docker Swarm does not have the done-for-you cluster setup offerings that make Kubernetes shine, but it’s easy to set up for yourself and straightforward to run in your environment. When you want to prove concepts regarding application communications and dynamics, Docker Swarm is a great way to approach that. And if you want to test out infrastructure ideas, it’s a good choice as well.
Running the Docker Engine in swarm mode has proven success with production workloads. Plus, it has the advantage of being generally easier to set up and configure than Kubernetes. For smaller organizations that don’t need the flexibility of Kubernetes, Docker Swarm can be a great choice. If you find yourself thinking Kubernetes is overkill, consider a swarm.
Additionally, Docker in swarm mode is useful for development and proof-of-concept work. It works for getting a minimum viable feature set out the door and evaluated with real users. With Docker, you’ll find it a short path to a real deployment with real scalability. Kubernetes can work in these situations as well, but Swarm is simpler and can be a quicker path to realization.
Docker Compose is popular on developer workstations for quickly spinning up environments with multiple containers. Swarm mode supports using Compose files to deploy stacks, which makes for nice reuse of a definition of developer environments to deploy in other places.
For most situations and deployments, given that container orchestration is a boon to operation, choosing Kubernetes makes sense. If it’s not the right choice, it’s at least a right choice. There are situations where it may be better to use Docker Swarm (or a simpler container service like Amazon’s Elastic Container Service). Even in such cases, Kubernetes is only inferior because it’s a bit more complex than the situation warrants, rather than being a bad choice.
Choosing Kubernetes will set you up better for handling the unknown. Therefore, if you don’t know everything that will be thrown your way in the future, using Kubernetes will put you in a good position to adjust.
Given workloads that run in containers and use cases that fit orchestration, you should usually choose Kubernetes for your production and non-production canonical deployments. This is especially true in cases of large and/or multiple teams, diverse sets of needs for different system parts, needs for fine-grained control of authorization, and the presence of uncertainty of infrastructure needs. When your use cases are relatively simple, known, and homogeneous, you should consider the simplicity of Docker Swarm for running your production and non-production canonical deployments.
For proof-of-concept and other ad-hoc environment needs, using an existing Kubernetes cluster or something of the sort may fit the needs of your team. It might also work better for testing in a more production-like environment. But you can quickly and easily create swarms using Docker Engine installations, which serves these use cases well—often better than Kubernetes.
As always, you need to carefully consider your situation and decide, for yourself, what is best for you.