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In this lesson, you will learn how to monitor your Docker Swarm cluster and manage its services through a visual interface. While the command-line tools docker service ls and docker service ps are effective for checking which services are running on which nodes, they can become cumbersome as your cluster scales.
For clusters with multiple nodes and services, consider using Docker Visualizer to simplify monitoring and management.

Introducing Docker Visualizer

Docker Visualizer is a user-friendly tool available on Docker Hub under Docker Samples. Look for the image named “visualizer” when browsing Docker Samples. The help section on its Docker Hub page provides all necessary instructions for running the tool.

Deploying Docker Visualizer on Your Docker Swarm Cluster

To deploy Docker Visualizer, execute the following commands on your Docker master node. This first command creates a Docker service for the visualizer:
If you’re using an ARM-based system, build the image with the ARM-specific Dockerfile using:
Alternatively, you can run the visualizer as a standalone interactive container. This command binds the host’s Docker socket and maps port 8080:
Once the container launches, Docker will download the image if it is not already available locally. Open your web browser and navigate to: http://<your-docker-master>:8080 This interface displays your Docker Swarm cluster topology, including the master node, worker nodes, and the details of individual services and containers.

Example: Deploying a Docker Stack

Below is an example of deploying a Docker stack for an application. The output shows the creation of various services and provides a snapshot of the current state of your Docker services:
The Docker Visualizer interface presents a clear and dynamic view of your Docker Swarm topology, showcasing nodes, running containers, and resource usage details. This visual approach enhances your ability to manage and troubleshoot cluster deployments.
The image shows a Docker container visualizer interface displaying three nodes with running containers, including details like RAM usage and container states.
Thank you very much for your time, and happy learning!

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