SR Launcher CLI

SR Launcher supports Command Line Interface which is all equivalent to the GUI interface. You can use either one.

Installation with CLI

info

Installation of SENSR-I can be also done with CLI. You don't need to install SENSR-I using both. Regardless of the interface, once the SENSR-I is installed, you can launch SENSR-I using either one.

Pre-requisites are exactly same as the one for GUI installation.

caution

Make sure you have an active internet connection during the installation process.

1. Download sr-launcher-cli-[VERSION]-[ARCH].deb.

2. Install the downloaded file with command below.

   sudo apt install ./sr-launcher-cli-[VERSION]-[ARCH].deb

3. (Optional) Set version to use. Default version is latest.

   sr-launcher-cli set version
   # Available versions are shown. Select one. It requires internet connection.

4. Pre-install packages. It will download Kubernetes binary and Docker images of SENSR-I to the machine you are running SR Launcher CLI.

   sr-launcher-cli run pre-install
   # By default all images for both arm64 and amd64 will be downloaded. You can specify it like below.
   # sr-launcher-cli run pre-install -a amd64

5. Create cluster.json file with machine information that you want to install and use.

   • Case 1: Single machine installation, which Master node and Algo node will be in the same machine

     {
         "nodes": [
             {
                 "ip": "ip-of-the-machine",
                 "user_name": "user-name-of-the-machine",
                 "password": "password-of-the-machine",
                 "is_master": true,
                 "supported_worker_apps": ["algo"],
                 "name": "master"
             }
         ]
     }

   • Case 2: Machine A for Master node and Algo node, and Machine B only for Algo node

     {
         "nodes": [
             {
                 "ip": "node1_computer_ip_address",
                 "user_name": "node1_computer_user_name",
                 "password": "node1_computer_password",
                 "is_master": true,
                 "supported_worker_apps": ["algo"],
                 "name": "master"
             },
             {
                 "ip": "node2_computer_ip_address",
                 "user_name": "node2_computer_user_name",
                 "password": "node2_computer_password",
                 "is_master": false,
                 "supported_worker_apps": ["algo"],
                 "name": "algo_1"
             },
             ...
         ]
     }

   • IP address is a machine identifier of Kubernetes. Use the physical and static IP address (don't use localhost or 127.0.0.1) that changes as least as possible.

   • Don't add same machine many times to use many algo nodes in the machine. The node here is not corresponding to the number of algo nodes you can launch in a machine.

   • If you want to use the machine for Edge node, you can add "edge" to "supported_worker_apps".

6. Run installation with cluster.json file.

   sr-launcher-cli run install -f cluster.json

   This will install Docker and Nvidia-docker(if GPU is connected) on the machines, and load Docker images to the Master node machine.

Install License Server

1. Put the command as below.

   sr-launcher-cli run install license-server

2. Put the license file to the path /opt/seoulrobotics/licenses after activating the license following the steps here.
3. (Optional) Check license server is running fine by accessing http://<Master-Node-IP-Address>:9011 through web browser. You can see the page as below.

Launch SENSR-I with CLI

1. List the machines you will use in the json file. e.g. cluster.json

   {
       "nodes": [
           {
               "ip": "node1_computer_ip_address",
               "user_name": "node1_computer_user_name",
               "password": "node1_computer_password",
               "is_master": true,
               "supported_worker_apps": ["algo"],
               "name": "master"
           },
           {
               "ip": "node2_computer_ip_address",
               "user_name": "node2_computer_user_name",
               "password": "node2_computer_password",
               "is_master": false,
               "supported_worker_apps": ["algo"],
               "name": "algo_1"
           },
           ...
       ]
   }

   • Machines should be under the same network and be able to access to each other.
   • The machine that SR Launcher is running on should be included and set as the Master node machine as is_master: true. And the other machines should be set as the Algo node machines as is_master: false.
   • The name field is used to identify the machine. It can be anything, but it should be unique.

2. Create cluster using cluster.json file.

   sr-launcher-cli create cluster -f cluster.json <cluster_name>`

   • <cluster_name> will be used to identify the cluster. It can be anything, but is recommended to use site_name for easy identification, or use names such as c1 or c2 for easy use.

3. Run SENSR-I.

   sr-launcher-cli run sensr

   • To run SENSR-I with no-GUI mode, add --no-gui option. sr-launcher-cli run sensr --no-gui

Run Web FE server

1. Run command below. This should be done when SENSR-I is running.

   sr-launcher-cli run web-fe-server

2. Open web browser and go to http://<ip-of-the-machine>:5000 to access to the Web FE.

Terminate SENSR-I with CLI

1. Terminate SENSR-I. It will stop Web FE server if it's running.

   sr-launcher-cli stop sensr

2. Delete cluster. (Optional, but recommended to make clean up all services for SENSR-I and Kubernetes.)

   sr-launcher-cli delete cluster <cluster_name>

Update SENSR-I version

1. Set version that you want to update to.

   sr-launcher-cli set version
   # Available versions are shown. Select one. It requires internet connection.

2. Follow the installation steps above.