Pragmatic Ai – Deploying Containers to Azure

Pragmatic Ai – Deploying Containers to Azure-iLLiTERATE
English | Tutorial | Size: 989.65 MB


Deploy a containerized web app to Azure

There are many services out there that allow you to deploy a container to the cloud. Although a straightforward operation, it is critical to understand how to create a robust automation deployment system. This course will create a Python Flask application from scratch, will containerize it, set the automation for it and then deploy it to Azure.

This course lays out the foundations for creating more powerful containerized applications beyond the simple examples. You can add a Machine Learning model into the container and the end result would be the same: a robust deployment system that can get changes quickly onto Azure with any changes to the main branch.

The continuous deployment system is a game changer as a skill set, making you a far more valuable engineer.

In this video you will learn:

Create a Python Flask application for containerization
Use a Dockerfile to create the Flask container
Use GitHub Actions to automatically deploy the container after a pull request or changes to the main branch
Push your container to the GitHub container registry from the GitHub repository
Create the web app on the Azure portal and connect it to GitHub Actions
Host the containerized Python Flask application on Azure
Debugging techniques for broken containers and other common errors like incorrect ports
GitHub repository with sample code
Free Azure Certification for Students
Try Azure for Free
AZ-900 Azure Fundamentals reference guide
Azure SAMBA file share
Azure Remote Compute for VSCode
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