RangRang - Server

Steps to Replicate the Server Deployment

1. Open the Google Cloud Platform
2. To grant an IAM role as Editor VM on a project, do the following:
   • In the Cloud Console, go to the IAM page
   • Go to the IAM page
   • Click Add
   • Enter an email e.g example@gmail.com,
   • Choose the Roles under the Compute Engine Role and Select 'Compute Engine Admin'
   • Click Save
3. Go into the Cloud Console
4. To Provision a New Compute Instance for the Back-End Server, Run the Following Commands

   gcloud beta compute --project=<YOUR PROJECT ID> instances create rangrang-backend --zone=asia-southeast2-b --machine-type=n1-standard-2 --subnet=default --address=34.101.140.95 --network-tier=PREMIUM --maintenance-policy=TERMINATE --service-account=1083353886178-compute@developer.gserviceaccount.com --scopes=https://www.googleapis.com/auth/cloud-platform --tags=http-server,https-server --image=ubuntu-2004-focal-v20210603 --image-project=ubuntu-os-cloud --boot-disk-size=10GB --boot-disk-type=pd-ssd --boot-disk-device-name=rangrang-backend --no-shielded-secure-boot --shielded-vtpm --shielded-integrity-monitoring --reservation-affinity=any
   
   gcloud compute --project=<YOUR PROJECT ID> firewall-rules create default-allow-http --direction=INGRESS --priority=1000 --network=default --action=ALLOW --rules=tcp:80 --source-ranges=0.0.0.0/0 --target-tags=http-server
   
   gcloud compute --project=<YOUR PROJECT ID> firewall-rules create default-allow-https --direction=INGRESS --priority=1000 --network=default --action=ALLOW --rules=tcp:443 --source-ranges=0.0.0.0/0 --target-tags=https-server
   

5. SSH into the Server either by GUI, or through the Command Line Interface
6. Update Packages on the Ubuntu VM by Running the Following Commands

   sudo apt update && sudo apt upgrade -y

7. Setup Machine Learning Dependencies with the Following Commands
   • Clone models repository from tensorflow

     git clone https://github.com/tensorflow/models.git

   • Install tensorflow object detection API

     cd models/research
     protoc object_detection/protos/*.proto --python_out=.
     cp object_detection/packages/tf2/setup.py .
     sudo pip3 install --use-feature=2020-resolver .

8. Clone This Repository by Running the Following Command

   git clone https://github.com/Hyuto/rangrang-server.git
   cd rangrang-server

9. Install Django, djangorestframework and whitenoise

   sudo pip3 install django djangorestframework whitenoise

10. Setup django application
    • Setup main directory

      mkdir static files

    • Migrate db

      python3 manage.py migrate

    • Collectstatic

      python3 manage.py collectstatic

11. Exit the SSH Session by Running:

    exit

12. Turn off the VM Instance for the Back End Server by

• Clicking on the Checkbox of the VM that is Going to be Turned Off
• On the Top Panel, Click Stop

12. Click on the Back End Server VM then Click on the Edit Button.
13. Navigate to the Custom metadata Section, and add the Following:
    Key: startup-script
    Value:

    #! /bin/bash
    sudo service apache2 stop
    cd /home/rangrang-server
    sudo nohup python3 manage.py runserver 0.0.0.0:80 >> log.log 2>&1 | tee &

14. Save the Changes
15. Turn on the VM Instance to Start the Back End Server Service
16. Navigate to the External IP Address to Check Its Availability by Going to these Paths:

    http://<EXTERNAL-IP-ADDRESS>/cd-api/video/
    http://<EXTERNAL-IP-ADDRESS>/cd-api/picture/
    http://<EXTERNAL-IP-ADDRESS>/od-api/video/
    http://<EXTERNAL-IP-ADDRESS>/od-api/picture/
    

Once all the Paths are Working, the Server is Considered Fully Functioning and Ready to Use

Navigation

	Repository
Android	grrrracia/RangRang-MobileApp
Cloud Computing	Hyuto/rangrang-server
Machine Learning	Hyuto/rangrang-ML