Introduction

Docker Swarm has evolved as a strong and user-friendly platform for managing Docker containers at scale in the ever-changing container orchestration landscape. Swarm facilitates the deployment, scaling, and maintenance of containerized applications with its user-friendly interface and seamless integration with Docker. This essay examines the capabilities of Docker Swarm through real-world use scenarios, showcasing its adaptability and efficiency in a variety of situations.

Use Case 1: High Availability Web Applications

One of Docker Swarm's primary advantages is its ability to offer high availability for web applications. Consider the case of a popular e-commerce business experiencing high traffic during a flash sale. Docker Swarm enables automatic load balancing across several containers, ensuring that the website stays responsive even in the face of high visitor traffic. The traffic is efficiently spread by installing the web application in a Swarm cluster, preventing any single server from getting overburdened.

Use Case 2: Continuous Deployment and Rolling Updates

Continuous deployment and rolling upgrades are crucial DevOps strategies. Docker Swarm allows for smooth updates without interfering with the user experience. Consider a microservices application in which each service is containerized. Developers can use Swarm to update individual services without disrupting the entire program. This method assures little downtime and a pleasant user experience, making it a great alternative for apps that require frequent updates and enhancements.

Use Case 3: IoT Edge Computing

The Internet of Things (IoT) has transformed industries ranging from healthcare to manufacturing. Docker Swarm is critical in IoT edge computing, where data processing takes place closer to the data source. Swarm facilitates the deployment of lightweight containers on edge devices in this setting, ensuring effective resource use and low latency. Docker Swarm, for example, may manage containers on edge devices in a smart factory, evaluating sensor data in real-time and making split-second decisions without relying on a centralized server.

Use Case 4: Hybrid and Multi-Cloud Deployments

Modern enterprises frequently operate in hybrid or multi-cloud setups, combining on-premises servers with cloud platforms. Docker Swarm offers a uniform orchestration layer that spans several infrastructures. Organizations may smoothly migrate workloads between environments by installing Swarm clusters both on-premises and in the cloud. This adaptability provides optimal resource use, scalability, and resilience, making it a perfect alternative for businesses with complicated infrastructure needs.

Use Case 5: Disaster Recovery and Fault Tolerance

It is critical to ensure business continuity in the face of calamities or hardware problems. Docker Swarm includes fault tolerance and disaster recovery features. The system may automatically recover from node failures by replicating services across different nodes inside a Swarm cluster. This capability is very useful for situations where downtime is not an option, such as financial or healthcare systems. The ability of Docker Swarm to sustain service availability even in difficult scenarios makes it a dependable choice for mission-critical applications.

Quick project on how this works

Pre-requisites

AWS account

Three EC2 instances (t2.micro would do)

Understanding of Linux commands like sudo, apt install, etc.

Process

Step 1: Log in to your AWS account

Step 2: Create 3 EC2 instances (I used Ubuntu as the base OS)

Step 3: While creating the EC2 instances, under the security group section you click edit > add security group rule to add a couple of ports under the incoming section. The ports would be:
Custom TCP — 2377 — Anywhere IPv4

Custom TCP — 8001 — Anywhere IPv4

Once done and the instances were created, I named them Docker Swarm Manager, Docker Swarm Worker 1 and Docker Swarm Worker 2 respectively.

Step 4: Perform ssh into each of the instances

Step 5: Update the instances using the sudo apt update command

Step 6: Once this is done, install docker on all the three machines:

Step 7: On the manager machine (which I renamed as Docker Swarm Manager), initiate docker swarm using the command docker sudo docker swarm init

Fantastic!! Now you have the join command for the worker nodes ready to join them to your docker swarm network.

What next? Head to your worker instances...

Step 8: On the Worker instances, run the docker swarm join command which appeared on the Manager machine when we ran the sudo docker swarm init command. This is to be done on both instances.

If you want to check if the workers have joined the Manager, on the Manager instance perform:

sudo docker node ls

the Great!! Now both the instances have joined the manager and are ready to serve our HA purposes. Let's deploy a docker image and check if this works flawlessly.

Step 9: Create a Docker service with the below command:

sudo docker service create --name <name of the application> --replicas <number of replicas you need> --publish <ports you want to access the service on> <docker image name>

Sample application that I wanted to check and what i used:

sudo docker service create --name django-app-service --replicas 3 --publish 8001:8001 trainwithshubham/react-django-app:latest

Worked like a charm!! Now that the service is up and ready, lets check it once using sudo docker service ls

That's created!

To check the container created, run sudo docker ps

Alright!!! Time for a reality check since deployment is completed...

Grab a public IP address from any of the three instances. I took one from my worker instance 1. Now suffix that with the port number 8001 and access it on the browser.

Since my worker instance had an IP 18.212.101.57, the access link for me was 18.212.101.57:8001... Pasted that on a new browser window and there it was!!

You can verify this with the other IPs too... I am sure this should work!

Disadvantages of using Docker swarm

While Docker swarm proved useful, it has its disadvantages!

Limited Scalability Compared to Other Orchestration Tools

Docker Swarm is built for simplicity and ease of use, making it an excellent solution for small to medium-sized applications. Other orchestration solutions, such as Kubernetes, may offer more advanced functionality and scalability choices for extremely large-scale installations.

Smaller Ecosystem and Community Support

Docker Swarm has a smaller ecosystem and community than Kubernetes. There are fewer third-party integrations, plugins, and community-contributed solutions accessible as a result. The large Kubernetes community frequently results in faster problem resolution and a plethora of information for consumers.

Complex Networking Requirements

Docker Swarm networking is more difficult to set up and configure, particularly in complex networking applications. While it comes with basic networking capabilities, more elaborate network configurations may necessitate additional effort and knowledge.

Limited Built-in Features

While Docker Swarm provides key container orchestration tools, it lacks some sophisticated functionality found in Kubernetes, such as advanced deployment methods, extensive pod lifecycle hooks, and fine-grained access control. Users who need these features may find Docker Swarm inadequate.

Limited Customization

Docker Swarm places an emphasis on simplicity, therefore it may not be the ideal choice if your organization requires highly customized or specialized orchestration configurations. Kubernetes, with its wide configuration possibilities, may be a better fit in these situations.

Dependency on Docker

Docker Swarm is strongly intertwined with Docker, therefore it may not be the best choice for enterprises seeking a container-runtime-agnostic solution. Kubernetes, for example, provides different container runtimes, allowing for greater flexibility in container selection.

Learning Curve for Complex Use Cases

The configuration and optimization of Docker Swarm for more complicated situations may require a steep learning curve, especially for users who are already familiar with Docker but are unfamiliar with container orchestration ideas. This is true even though setting up Docker Swarm for basic use cases is very simple.

Uncertain Future

Regarding the future development and support for particular tools, there is always some degree of uncertainty given the rapid evolution of container orchestration technology. The strategic choices made by Docker could have an impact on the long-term development and support of Docker Swarm.

Conclusion

The real-time use cases for Docker Swarm highlight its adaptability and dependability in the changing IT world of today. When it comes to container orchestration, Docker Swarm proves to be a potent tool for ensuring high availability for web applications, enabling continuous deployment, supporting IoT edge computing, easing hybrid cloud deployments, and offering reliable disaster recovery solutions. Docker Swarm is a beacon of efficiency, providing smooth management of containerized apps across diverse scenarios as businesses continue to develop and face new difficulties. Embracing Docker Swarm enables businesses to confidently and easily traverse the complexity of contemporary IT infrastructures. In conclusion, enterprises with sophisticated, large-scale, or highly specialized requirements may find other orchestration systems, like Kubernetes, to be more appropriate. Docker Swarm, however, offers simplicity and ease of use. Before selecting an orchestration solution, it's critical to carefully assess the unique requirements of your apps and infrastructure.

I would love to hear back for any updates that I can make to this article!

Happy Learning