VictorOps is now Splunk On-Call! Learn More.
Today, most organizations are rearchitecting their applications and moving them to the cloud. Use of microservices architecture and containers has completely transformed the way organizations develop and deploy new applications in the cloud. These technologies, alongside container orchestration tools like Kubernetes and Docker Swarm, allow organizations to develop small, independently deployable components of code that require minimal resources.
Using Docker and microservices architecture, it’s possible for organizations to provision their resources automatically and use them only when they’re needed. It can solve the under-provisioning and over-provisioning challenges once and for all. However, for this to happen, organizations need a solution that helps them manage complexity in the container ecosystem.
Orchestration, networking and service discovery pose huge challenges with containers and microservices running on hundreds or thousands of nodes. While Docker has become a natural choice for container packaging, runtime issues can still exist during the launch, upgrade, and monitoring of containers.
This is where container orchestration solutions like Docker Swarm and Kubernetes come into the picture.
Kubernetes or K8s is a powerful open-source container orchestration system originally developed and used by Google. Apart from Google Cloud, all major cloud services providers and OS vendors including Amazon Web Services (AWS), Microsoft and IBM offer native support for Kubernetes.
Docker Swarm is the native clustering engine and container orchestration system offered by Docker. Docker Swarm is also open-source and easy for developers to use since almost everything that works with Docker containers runs equally well in Swarm. You will find the same command line in both Swarm and Docker.
Both of these solutions can help you with:
In this article, we’ll compare Kubernetes and Docker Swarm. Before we begin, we’d like to clarify that while both Docker Swarm and Kubernetes can be used in production environments, Kubernetes seems to have a slight edge – it can scale up to approximately 5000 nodes as compared to 4700 nodes in Swarm. Further, Kubernetes has a wider adoption across DevOps and software development teams.
In Kubernetes, setting up a cluster isn’t simple. It can take up a lot of planning time and effort to get started with Kubernetes. There are different configurations for different operating systems – making the whole process complex and time-consuming.
Swarm’s installation is easier than K8s. You only need to know a couple of commands to set up clusters in Docker Swarm. Further, the setup across different operating systems is similar – making it easier for developers to get started no matter which OS they’re working with.
Kubernetes offers auto-scaling and can scale up to thousands of nodes with multiple containers in every node. Although Kubernetes is a proven all-inclusive framework offering a large set of APIs and stable cluster states, the complexity leads to slower speeds when deploying new containers.
Docker Swarm doesn’t support auto-scaling out-of-the-box. But, DevOps and IT teams can sometimes find workarounds for this issue. In 2016, the previous version of Docker Swarm wasfive times faster than K8s when it comes to starting a new container. Additionally, at the time, Swarm could be up to seven times faster when listing all running containers in production. But today, the difference in speed between Docker Swarm and Kubernetes is negligible.
TLS authentication for security requires manual configuration.
TLS authentication and container networking are automatically configured.
Docker Swarm and Kubernetes both offer different approaches to service discovery. In K8s you need to define containers as services manually. On the other hand, containers in Swarm can communicate via virtual private IP addresses and service names regardless of their underlying hosts.
Both Kubernetes and Docker Swarm use raft consensus for management failover. Both tools require 3-5 management nodes and allow healthchecks to auto-create containers if apps or nodes fail. All in all, the difference in fault tolerance between Kubernetes and Docker Swarm is minimal.
Both container orchestration solutions offer high availability and redundancy by deploying a container on multiple nodes. This ensures that when a host goes down, the services can self-heal.
It’s true that the learning curve is higher in K8s; Docker CLI or Docker Compose cannot be used to define containers and YAML definitions have to be rewritten. However, K8s offers more possibilities for customization.
While the Swarm API offers ease in leveraging Docker with similar functionality, it isn’t easy to perform operations that aren’t covered under the API.
Built-in logging and monitoring are available. But, you can also use 3rd-party monitoring tools such as Splunk, Prometheus or AppDynamics to keep track of logs and other important performance metrics.
Swarm provides some basic out-of-the-box tools like Docker Service Logs, Docker Events and Docker Top. But, in order to level-up your monitoring, you’ll still want to take advantage of other 3rd-party logging and monitoring tools like Splunk and Prometheus.
Rolling updates progressively updates the pods sequentially with HA. K8s offers automated rollbacks in case of a failure.
In Swarm, the scheduler is used for updates. Also, the facility for automated rollbacks is not available out-of-the-box. Howeever, you can get full auto-rollback support in every update by setting “–update-failure-action=rollback” in your services, including healthcheck based rollbacks.
Kubernetes leads the market in terms of adoption. Even Docker allows its customers to choose Kubernetes for orchestration.
A summary of benefits and drawbacks
Despite its complexity, Kubernetes has entered the mainstream market. It enjoys the support of a larger community and the big three cloud vendors also offer managed Kubernetes services (i.e. EKS (AWS), GKE (Google), and AKS (Azure)). However, Swarm isn’t dead and can be a better fit for many teams.
In a blog post, an insider from Docker makes a pretty good argument for Swarm’s utility:
“…Swarm orchestration is not going away. Swarm forms an integral cluster management component of the Docker EE platform; In addition, Swarm will operate side-by-side with Kubernetes in a Docker EE cluster, allowing customers to select, based on their needs, the most suitable orchestration tool at application deployment time.”
While Kubernetes and Swarm can help you orchestrate your containers with higher efficiency, application downtime and performance worries are far from gone. DevOps teams are often overworked managing applications in their distributed setup.
Monitoring containerized environments can be more difficult than traditional applications and services. As containers are stateless, the logs have to be archived before the container shuts down. This requires persistent log collection, analysis and archiving. Moreover, container environments have a multi-tier structure which makes log collection complicated.
Many organizations don’t have a ready setup to manage application logs in a complex containerized environment. Further, their traditional security and incident management solutions aren’t equipped to meet spikes in log volumes and can be painfully slow while searching through older logs.
It’s important to realize that logs can hold key insights and provide the only reliable avenue for tracing issues and solving performance bottlenecks. This is where tools like Splunk’s container monitoring can help you out. Splunk provides a smart approach to managing and analyzing container logs in a proactive manner. Unlike other open-source solutions which require complex configuration and integrations to monitor container environments, Splunk comes right out of the box, ready to go.
Learn why a centralized solution for monitoring and alerting leads to improved on-call incident management when using containers. Sign up for a 14-day free trial or request a personalized demo to see how DevOps and IT teams are making on-call suck less with VictorOps.