This project Setup is on a Continuous Integration/Continuous delivery pipeline for a Python-based machine learning application using the Flask web framework.
- login to azure portal at https://portal.azure.com/ and open the cloud shell
ssh-keygen -t rsa
NOTE: use cat ~/.ssh/id_rsa.pub
if you have generated it before
git clone [email protected]:AnimogM/Building-CI-CD-Pipelines.git
cd Building-CI-CD-Pipelines
python3 -m venv venv
source venv/bin/activate
make all
az webapp up --sku F1 -n maryam-ml-app
- Go to https://dev.azure.com and sign in.
- Create a new private project.
- Under Project Settings create a new service connection and select Azure Resource Manager.
- Create a Python-specific pipeline to deploy to App Service, and linked it to your GitHub repo.
az webapp log tail
- set the app name inside make_predict_azure_app.sh file
It an be improvedon by having multiple environments (Dev, Staging and Production) and have a pipeline for each environment.