MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + .srt | Duration: 11 lectures (50m) | Size: 507.5 MB
Learn to Build & Push a Python Web Application using Docker, Cloud Build & Cloud Run on the Google Cloud Platform
What you'll learn:
Deploying a Serverless Python Web Application
Setting up Google Cloud SDK on their System
Basic Docker Usage (Dockerfile)
Web Application Deployment to Google Cloud
What a Serverless application is
Cloud Build on Google Cloud Platform
Python (like 30 Days of Python)
Web Application Development (Like our Try Django series)
Build a Serverless Python Application by using a Docker Container and Google Cloud Run.
Serverless allows us to focus on our code and deploy more. What's better, our serverless applications only cost us money when they're used.
Docker Containers make it easy to create our own isolated environment on the operating system level. This is exactly what we need in so many applications.
In this series, we'll be deploying a Serverless Container Application on Google Cloud. In our case, we'll be using Python and FastAPI to deploy a REST API service. Using Containers give us the control we need to setup our environment and distribute to nearly any service that can run a Docker container.
Serverless web applications don't mean no servers, they just mean that the server is handled for you so your app can scale as large as it needs to meet incredible demand or scale to 0 if there's no demand. Container-based serverless apps are made possible by open-source technologies Kubernetes and Knative and managed for us by Google Cloud. Google developed Kubernetes to manage (orchestrate) containers. Luckily for us, we don't have to worry about Kubernetes at all, we just have to worry about our application's code and google handles the rest.
Serverless apps using containers on Google Cloud is seriously amazing. Let's see why.
Who this course is for
Students with some Python Experience
Beginner web app developers with interest in Serverless applications
AWS Lambda users looking for a better way