Google Cloud Run Services lets you rapidly deploy containerized apps to the cloud. In this liveProject, you’ll harness Google Cloud Run to deploy a customer feedback workflow and integrate an automated machine learning solution. Your company handles thousands of feedback queries every minute, and this new system will ensure that important customers are quickly escalated and kept happy.
You’ve decided your workflow will receive customer feedback via HTTP POST service calls, then use automated machine learning to decide whether comments are positive or negative. Your challenges will include creating a Cloud Run instance, Google’s Managed KNative Kubernetes Cluster, accepting and storing feedback data with Google’s NoSQL firestore, and managing future rollouts with proper versioning.
This project is designed for learning purposes and is not a complete, production-ready application or solution.
This liveProject is for experienced Kubernetes engineers looking for the flexibility of a serverless architecture. To begin this liveProject you will need to be familiar with:
- Intermediate Kubernetes
- Basics of Docker
- Basics of terminal/command lines
you will learn
In this liveProject, you’ll get hands-on experience with Google Cloud Platform while setting up a Kubernetes Cluster from scratch using Knative to orchestrate serverless functions.
- Setting up a cloud environment
- Creating a Kubernetes cluster
- Accepting HTTP requests
- Using serverless with Kubernetes
- Using machine learning to classify user feedback
- Event-based server development