Serverless Data Architecture & Containers On Google Cloud

Learn to deploy and implement applications at scale including Machine learning models

What you'll learn

Cloud computing using serverless data components

Containerization of python based applications

Microservice and Event driven architecture

Deploying production level machine learning workflows on cloud

Requirements

Must have a fair idea of how cloud works and past experience in basic programming using python and sql

Description

Google Cloud platform is one of the fastest growing cloud providers right now . This course covers all the major serverless components on GCP including a detailed implementation of Machine learning pipelines using Vertex AI and lab sessions covering Serverless Pyspark using Dataproc .Are you interested in learning & deploying applications at scale using Google Cloud platform ?Do you lack the hands on exposure when it comes to deploying applications and seeing them in action?If you answered "yes" to the above questions,then this course is for you .You will also learn what are micro-service and event driven architectures are with real world use-case implementations .This course is for anyone who wants to get a hands-on exposure in using the below services :Cloud FunctionsCloud Run Google App Engine Vertex AI for custom model training and development Kubeflow for workflow orchestration Dataproc Serverless for Pyspark batch jobs This course expects and assumes the students to have :A tech background with basic fundamentals Basic exposure to programming languages like Python & Sql Fair idea of how cloud works Have the right attitude and patience for self-learning :-)You will learn how to design and deploy applications written in Python which is the scripting language used in this course  across a variety of different services .

Overview

Section 1: Course Introduction and pre-requisites

Lecture 1 Course Introduction and Section Walkthrough

Lecture 2 Course Pre-requisites

Lecture 3 Course Material Github Repo

Section 2: Modern Day Cloud Concepts

Lecture 4 Introduction

Lecture 5 Scalability - Horizontal vs Vertical Scaling

Lecture 6 Serverless Vs Servers and Containerization

Lecture 7 Microservice Architecture

Lecture 8 Event Driven Architecture

Section 3: Get Started with Google Cloud

Lecture 9 Setup GCP Trial Account

Lecture 10 Gcloud CLI Setup

Lecture 11 Get comfortable with basics of gcloud cli

Lecture 12 gsutil and bash command basics

Section 4: Cloud Run - Serverless and containerized applications

Lecture 13 Section Introduction

Lecture 14 Introduction to Dockers

Lecture 15 Lab - Install Docker Engine

Lecture 16 Lab - Run Docker locally

Lecture 17 Lab - Run and ship applications using the container registry

Lecture 18 Introduction to Cloud Run

Lecture 19 Lab-Deploy python application to Cloud run

Lecture 20 Cloud Run Application Scalability parameters

Lecture 21 Introduction to Cloud Build

Lecture 22 Lab- Python application deployment using cloud build

Lecture 23 Lab-Continuous Deployment using cloud build and github

Section 5: Google App Engine - For Serverless applications

Lecture 24 Introduction to App Engine

Lecture 25 App Engine - Different Environments

Lecture 26 Lab-Deploy Python application to App Engine - Part 1

Lecture 27 Lab-Deploy Python application to App Engine - Part 2

Lecture 28 Lab-Traffic splitting in App Engine

Lecture 29 Lab-Deploy python-bigquery application

Lecture 30 What is Caching and the use-cases ?

Lecture 31 Lab-Implement Caching mechanism in python application - Part 1

Lecture 32 Lab-Implement Caching mechanism in python application - Part 2

Lecture 33 Lab-Assignment Implement Caching

Lecture 34 Lab-Python App deployment in flexible environment

Lecture 35 Lab- Scalability and instance types in App Engine

Section 6: Cloud Functions - Serverless and event driven applications

Lecture 36 Introduction

Lecture 37 Lab-Deploy python application using cloud storage triggers

Lecture 38 Lab-Deploy python application using pub-sub triggers

Lecture 39 Lab-Deploy python application using http triggers

Lecture 40 Introduction to Cloud Datastore

Lecture 41 Overview Product wishlist use-case

Lecture 42 Lab-Use-case deployment part-1

Lecture 43 Lab-Use-case deployment part-2

Section 7: Data Science Models with Google App Engine

Lecture 44 Introduction to ML Model Lifecycle

Lecture 45 Overview - Problem Statement

Lecture 46 Lab-Deploy Training Code to App Engine

Lecture 47 Lab-Deploy Model Serving Code to App Engine

Lecture 48 Overview-New Use Case

Lecture 49 Lab-Data Validation using App Engine

Lecture 50 Lab-Workflow Template introduction

Lecture 51 Lab-Final Solution Deployment using workflow and app engine

Section 8: Dataproc Serverless Pyspark

Lecture 52 Introduction

Lecture 53 PySpark Serverless Autoscaling Properties

Lecture 54 Persistent History Cluster

Lecture 55 Lab - Develop and Submit Pyspark Job

Lecture 56 Lab-Monitoring and Spark UI

Lecture 57 Introduction to Airflow

Lecture 58 Lab- Airflow with Serverless pyspark

Lecture 59 Wrap Up

Section 9: Vertex AI - Machine Learning Framework

Lecture 60 Introduction

Lecture 61 Overview - VertexAI UI

Lecture 62 Lab-Custom Model training using Web Console

Lecture 63 Lab-Custom Model training using SDK and Model Registries

Lecture 64 Lab- Model Endpoint Deployment

Lecture 65 Lab- Model Training Flow using Python SDK

Lecture 66 Lab - Model Deployment Flow using Python SDK

Lecture 67 Lab-Model Serving using Endpoint with Python SDK

Lecture 68 Introduction to Kubeflow

Lecture 69 Lab-Code Walkthrough using Kubeflow and Python

Lecture 70 Lab-Pipeline Execution in Kubeflow

Lecture 71 Lab-Final Pipeline Visualization using Vertex UI and Walkthrough

Lecture 72 Lab-Add Model Evaluation Step in Kubeflow before deployment

Lecture 73 Lab- Reusing configuration files for pipeline execution and training

Lecture 74 Lab - Assignment Use-case - Fetch data from BigQuery

Lecture 75 Wrap Up

Section 10: Cloud Scheduler and Application Monitoring

Lecture 76 Introduction to Cloud Scheduler

Lecture 77 Lab-Cloud Scheduler in action

Lecture 78 Lab - Setup Alerting for Google App Engine Applications

Lecture 79 Lab - Setup Alerting for Cloud Run Applications

Lecture 80 Lab Assignment - Setup Alerting for Cloud Function Applications

Aspiring data scientists and machine learning engineers,Data engineers and architects,Anyone who has a decent exposure in IT and wants to start their cloud journey