1. Docker-CE with swarm mode enabled
2. Connect the required list of nodes to the Docker Swarm cluster
3. Credentials for your private Docker Registry to pull Metric Insights docker images
   • You can also pull from Metric Insights' official docker registry (contact [email protected] for credentials)
4. NFS Share mounted to all nodes to store the Metric Insights file system
   • This ensures continuous operations where critical application and data files survive and containers across the cluster continue to run should any nodes go down.
5. Ensure the following ports are open in the load balancer:

MI v7.0.1a:

• 80, 443 - HTTP and HTTPS ports for the Web UI Service (default redirection to 443)
• 32550 - TCP port for the Data Processor cluster
• 3306 - MySQL port for external access
• 8080, 8443 - HTTP and HTTPS ports for the REST API Data Processor Service
• 8081 - TCP port for Console Tool

MI v6.4.5:

• 80, 443 - HTTP and HTTPS ports for the Web UI Service (default redirection to 443)
• 2550 - TCP port for the Data Processor cluster
• 2551 - TCP port for the Seed Node Service
• 3306 - MySQL port for external access
• 8080, 8443 - HTTP and HTTPS ports for the REST API Data Processor Service
• 8081 - TCP port for Monitoring Tool

1. Install all required packages to both application nodes to support Docker
2. Provision a remote MySQL server database to store the application database
   • MySQL 8+
     • 8.0.37 for MI v7.0.1a
     • 8.0.32 for MI v6.4.5
   • MySQL root user required for the deployment
3. Provision an NFS share to mount to all nodes to store the MI filesystem (default path is /opt/mi)
4. Identify and label the nodes as master and slave:
   • For master node, enter the following docker command to label it as master:
     docker node update --label-add type=master node_master
   • For slave node, enter the following docker command to label it as slave:
     docker node update --label-add type=worker node_slave
5. Download the Metric Insights installer then unpack to the master node (contact [email protected] for the installer tarball). This will create an installer directory from where we can run the installer to generate a Deployment Manifest for Docker Swarm
   • tar xf MetricInsights-Installer-vX.X.X-Full.tar.gz
   • cd MetricInsights-Installer-vX.X.X-Full
6. Prepare Docker Secret files for each MI service
   • In the installer directory, you can find the template files to generate the secrets in ../utils/orchestration/swarm/secrets
   • Copy the *.env.example files there to your local directory and rename to *.env
   • Each template file represents a different MI service:
     • MI v7.0.1a:
       • web.env
       • console.env
       • dataprocessor.env
       • data-analyzer.env
       • image-generator.env
       • redis.env

• MI v6.4.5:
  • web.env
  • seed.env
  • dataprocessor.env
  • data-analyzer.env
  • monitoring.env
  • redis.env

• Edit each template file and update each parameter. Make sure the passwords you generate are consistent throughout the files

1. Generate the deployment manifest to use with Docker Swarm by running the following from the installer directory:
   • If the remote DB server has the same timezone as MI app: ./installer.py swarm --timezone <MI app timezone> -o <manifest filename>.yml
   • If the remote DB server has a different timezone than MI app: ./installer.py swarm --timezone <MI app timezone> --mysql-timezone <remote database server timezone> -o <manifest filename>.yml
   • If the Metric Insights Docker images will be pulled from a private Docker registry, use the --registry option along with the Docker registry URL as in ./installer.py swarm... --registry docker.metricinsights.com. When providing a registry URL, be sure to not include “https://.” The supported values are <hostname> or <hostname>:<port> without any protocol.

8. Finally, update the NFS share address in the deployment manifest file:
   • Look for this section and change the address nfs-server.metricinsights.com to the appropriate NFS share:

data:
    driver_opts:
      type: "nfs"
      o: "addr=nfs-server.metricinsights.com,nolock,soft,rw"
      device: ":/opt/mi/data/data"

To deploy docker swarm using the deployment manifest, use the docker stack deploy command:

$ docker stack deploy -c mi-swarm.yml --with-registry-auth mi
Creating network mi_metricinsights_net 
Creating secret mi_dataprocessor 
Creating secret mi_data-analyzer 
Creating secret mi_console 
Creating secret mi_redis 
Creating secret mi_image-generator 
Creating secret mi_web 

Creating service mi_dataprocessor 
Creating service mi_data-analyzer 
Creating service mi_console 
Creating service mi_redis 
Creating service mi_image-generator 
Creating service mi_web-master 
Creating service mi_web-slave

• Note, the docker stack deploy command will create the docker secrets required for each service based on the *.env files. There is no need to create the secrets yourself.
• Please see Docker Commands Cheat Sheet for a list of docker commands to use to manage the deployment.

To upgrade the deployment to a newer version of Metric Insights, simply generate a new config file using the installer for the new release, then redeploy using docker stack deploy.

Basic console commands can be checked by running ./installer.py swarm --help.