52 Weeks of Cloud

### Episode 5:  AWS CP Part 3

* Writing a AWS S3 Bucket Lister application in Visual Studio 2022

* AWS CP Part 3:  Network and Content Delivery, Compute Storage

If you enjoyed this video, here are additional resources to look at:

Coursera + Duke Specialization: Building Cloud Computing Solutions at Scale Specialization: https://www.coursera.org/specializations/building-cloud-computing-solutions-at-scale

Python, Bash, and SQL Essentials for Data Engineering Specialization: https://www.coursera.org/specializations/python-bash-sql-data-engineering-duke

O'Reilly Book: Practical MLOps: https://www.amazon.com/Practical-MLOps-Operationalizing-Machine-Learning/dp/1098103017

O'Reilly Book: Python for DevOps: https://www.amazon.com/gp/product/B082P97LDW/

Pragmatic AI: An Introduction to Cloud-based Machine Learning: https://www.amazon.com/gp/product/B07FB8F8QP/

Pragmatic AI Labs Book: Python Command-Line Tools: https://www.amazon.com/gp/product/B0855FSFYZ

Pragmatic AI Labs Book: Cloud Computing for Data Analysis: https://www.amazon.com/gp/product/B0992BN7W8

Pragmatic AI Book: Minimal Python: https://www.amazon.com/gp/product/B0855NSRR7

Pragmatic AI Book: Testing in Python: https://www.amazon.com/gp/product/B0855NSRR7

Subscribe to Pragmatic AI Labs YouTube Channel: https://www.youtube.com/channel/UCNDfiL0D1LUeKWAkRE1xO5Q

View content on noahgift.com: https://noahgift.com/

View content on Pragmatic AI Labs Website: https://paiml.com/

• 🤖 Master GenAI Engineering - Build Production AI Systems
• 🦀 Learn Professional Rust - Industry-Grade Development
• 📊 AWS AI & Analytics - Scale Your ML in Cloud
• ⚡ Production GenAI on AWS - Deploy at Enterprise Scale
• 🛠️ Rust DevOps Mastery - Automate Everything

• 💼 Production ML Program - Complete MLOps & Cloud Mastery
• 🎯 Start Learning Now - Fast-Track Your ML Career
• 🏢 Trusted by Fortune 500 Teams

Learn end-to-end ML engineering from industry veterans at PAIML.COM

• Benchmarking: https://github.com/noahgift/benchmarking-aws
• History of AWS (AWS Shareholder Letter 2020): https://www.aboutamazon.com/news/company-news/2020-letter-to-shareholders
• Visual Studio AWS Tool
• Github Codespaces vscode tutorial: https://github.com/noahgift/DotNet-AWS/blob/main/chapters/appendix/AppendixB-CSharp-Tutorial.md
• AWS CP Part 2

If you enjoyed this video, here are additional resources to look at:

Coursera + Duke Specialization: Building Cloud Computing Solutions at Scale Specialization: https://www.coursera.org/specializations/building-cloud-computing-solutions-at-scale

Python, Bash, and SQL Essentials for Data Engineering Specialization: https://www.coursera.org/specializations/python-bash-sql-data-engineering-duke

O'Reilly Book: Practical MLOps: https://www.amazon.com/Practical-MLOps-Operationalizing-Machine-Learning/dp/1098103017

O'Reilly Book: Python for DevOps: https://www.amazon.com/gp/product/B082P97LDW/

Pragmatic AI: An Introduction to Cloud-based Machine Learning: https://www.amazon.com/gp/product/B07FB8F8QP/

Pragmatic AI Labs Book: Python Command-Line Tools: https://www.amazon.com/gp/product/B0855FSFYZ

Pragmatic AI Labs Book: Cloud Computing for Data Analysis: https://www.amazon.com/gp/product/B0992BN7W8

Pragmatic AI Book: Minimal Python: https://www.amazon.com/gp/product/B0855NSRR7

Pragmatic AI Book: Testing in Python: https://www.amazon.com/gp/product/B0855NSRR7

Subscribe to Pragmatic AI Labs YouTube Channel: https://www.youtube.com/channel/UCNDfiL0D1LUeKWAkRE1xO5Q

View content on noahgift.com: https://noahgift.com/

View content on Pragmatic AI Labs Website: https://paiml.com/

• 🤖 Master GenAI Engineering - Build Production AI Systems
• 🦀 Learn Professional Rust - Industry-Grade Development
• 📊 AWS AI & Analytics - Scale Your ML in Cloud
• ⚡ Production GenAI on AWS - Deploy at Enterprise Scale
• 🛠️ Rust DevOps Mastery - Automate Everything

• 💼 Production ML Program - Complete MLOps & Cloud Mastery
• 🎯 Start Learning Now - Fast-Track Your ML Career
• 🏢 Trusted by Fortune 500 Teams

Learn end-to-end ML engineering from industry veterans at PAIML.COM

If you enjoyed this video, here are additional resources to look at:

Coursera + Duke Specialization: Building Cloud Computing Solutions at Scale Specialization: https://www.coursera.org/specializations/building-cloud-computing-solutions-at-scale

Python, Bash, and SQL Essentials for Data Engineering Specialization: https://www.coursera.org/specializations/python-bash-sql-data-engineering-duke

O'Reilly Book: Practical MLOps: https://www.amazon.com/Practical-MLOps-Operationalizing-Machine-Learning/dp/1098103017

O'Reilly Book: Python for DevOps: https://www.amazon.com/gp/product/B082P97LDW/

Pragmatic AI: An Introduction to Cloud-based Machine Learning: https://www.amazon.com/gp/product/B07FB8F8QP/

Pragmatic AI Labs Book: Python Command-Line Tools: https://www.amazon.com/gp/product/B0855FSFYZ

Pragmatic AI Labs Book: Cloud Computing for Data Analysis: https://www.amazon.com/gp/product/B0992BN7W8

Pragmatic AI Book: Minimal Python: https://www.amazon.com/gp/product/B0855NSRR7

Pragmatic AI Book: Testing in Python: https://www.amazon.com/gp/product/B0855NSRR7

Subscribe to Pragmatic AI Labs YouTube Channel: https://www.youtube.com/channel/UCNDfiL0D1LUeKWAkRE1xO5Q

View content on noahgift.com: https://noahgift.com/

View content on Pragmatic AI Labs Website: https://paiml.com/

• 🤖 Master GenAI Engineering - Build Production AI Systems
• 🦀 Learn Professional Rust - Industry-Grade Development
• 📊 AWS AI & Analytics - Scale Your ML in Cloud
• ⚡ Production GenAI on AWS - Deploy at Enterprise Scale
• 🛠️ Rust DevOps Mastery - Automate Everything

• 💼 Production ML Program - Complete MLOps & Cloud Mastery
• 🎯 Start Learning Now - Fast-Track Your ML Career
• 🏢 Trusted by Fortune 500 Teams

Learn end-to-end ML engineering from industry veterans at PAIML.COM

• Part 1: Cover Reinvent 2021 announcements
• Part2: Talk about getting started:
  • AWS Free Tier
  • AWS Academy (for students)
  • AWS Sagemaker Studio Lab
• Part 3: Cloud development environments
  • AWS Cloudshell Can run Bash, ZSH or Powershell
  • AWS Cloud9 Supports many languages including Python and C#
• Notes on Episode 2

If you enjoyed this video, here are additional resources to look at:

Coursera + Duke Specialization: Building Cloud Computing Solutions at Scale Specialization: https://www.coursera.org/specializations/building-cloud-computing-solutions-at-scale

Python, Bash, and SQL Essentials for Data Engineering Specialization: https://www.coursera.org/specializations/python-bash-sql-data-engineering-duke

O'Reilly Book: Practical MLOps: https://www.amazon.com/Practical-MLOps-Operationalizing-Machine-Learning/dp/1098103017

O'Reilly Book: Python for DevOps: https://www.amazon.com/gp/product/B082P97LDW/

Pragmatic AI: An Introduction to Cloud-based Machine Learning: https://www.amazon.com/gp/product/B07FB8F8QP/

Pragmatic AI Labs Book: Python Command-Line Tools: https://www.amazon.com/gp/product/B0855FSFYZ

Pragmatic AI Labs Book: Cloud Computing for Data Analysis: https://www.amazon.com/gp/product/B0992BN7W8

Pragmatic AI Book: Minimal Python: https://www.amazon.com/gp/product/B0855NSRR7

Pragmatic AI Book: Testing in Python: https://www.amazon.com/gp/product/B0855NSRR7

Subscribe to Pragmatic AI Labs YouTube Channel: https://www.youtube.com/channel/UCNDfiL0D1LUeKWAkRE1xO5Q

View content on noahgift.com: https://noahgift.com/

View content on Pragmatic AI Labs Website: https://paiml.com/

• 🤖 Master GenAI Engineering - Build Production AI Systems
• 🦀 Learn Professional Rust - Industry-Grade Development
• 📊 AWS AI & Analytics - Scale Your ML in Cloud
• ⚡ Production GenAI on AWS - Deploy at Enterprise Scale
• 🛠️ Rust DevOps Mastery - Automate Everything

• 💼 Production ML Program - Complete MLOps & Cloud Mastery
• 🎯 Start Learning Now - Fast-Track Your ML Career
• 🏢 Trusted by Fortune 500 Teams

Learn end-to-end ML engineering from industry veterans at PAIML.COM

Outline

**Key Book Facts:**

* (8 chapters: 30 pages/chapter & 240-250 total length)

* Each chapter has one more more independent code examples in Github

* Chapter 1:  Getting started with .NET on AWS

   * What is Cloud Computing

       * Types of Cloud Computing:  

           * IaaS

           * PaaS, FaaS and Serverless

           * SaaS

           * MaaS

       * Key Cloud Computing Concepts

           * Elastic Infrastructure

           * Overview of Core Services

   * High-level overview of AWS

       * History of AWS

       * Global Infrastructure

   * Using AWS

       * Setting up an account

       * Using AWS Console

       * Setting up and Using IAM

       * Setting up and Developing AWS C# SDK with:

           * Quickstart of cross-platform C# app

           * AWS Cloudshell

           * AWS Cloud9

           * Visual Studio

           * Visual Studio Code and Visual Studio Codespaces on Github

* Chapter 2:  AWS Core Services

   * AWS Storage

       * Overview of AWS Storage

       * Developing with S3 Storage

       * Developing with EBS Storage

       * Using EFS Storage

   * Using EC2 Compute

       * Overview of EC2

       * Using EC2

       * Using EC2 Instance Types

       * Using EC2 Purchase Options

   * Security Best Practices for AWS

       * Encryption at REST and Transit

       * PLP (Principle of Least Privilege

   * Developing NoSQL Solutions with DynamoDB

       * What is DynamoDB

       * Key DynamoDB Concepts

       * Build a Sample C# DynamoDB Console App

* Chapter 3:  Migrating a legacy .NET application to AWS

   * Choosing a migration path

       * Rehosting

       * Replatforming

       * Repurchasing

       * Refactoring

       * Retire

       * Retain

   * Rehosting .NET Framework

       * App2Container

   * Rehosting .NET Core / 5

       * .NET Core Elastic Beanstalk

   * Replatforming: Migrating .NET Framework

       * Considerations for moving to .NET 5

       * Microsoft .NET Upgrade Assistant

       * AWS Porting Assistant for .NET

   * Migrating Build and Deploy to AWS

       * Teamcity to AWS Code Build

       * Selecting Deploy Compute Target Environment

* Chapter 4:  Modernizing .NET applications to Serverless

   * What is “Serverless” Computing?

   * Choosing the correct Serverless components for .NET on AWS

       * Developing with AWS Lambda and C#

       * Developing with AWS Step Functions

       * Developing with services with SQS and SNS

       * Developing Event Driven via AWS Triggers

   * Developing Serverless .NET Microservices on AWS

       * What is a Microservice according to AWS?

       * Overview of AWS Microservice options

       * Develop RESTful API with AWS App Runner

       * Developing RESTful API with AWS Lambda, API Gateway and SAM

* Chapter 5:  Containerization of .NET

   * Developing with Containers on AWS

       * Introduction to Containers

   * Comparing Containers to Hardware Virtualization

       * Advantages of Containers

   * Building Microservices with Containers

   * Introduction to Kubernetes

       * What is Kubernetes?

       * Understanding Kubernetes on AWS

   * Developing with AWS Container Compatible Services

       * Amazon ECR

       * Amazon ECS and Fargate

       * Amazon EKS

       * AWS App Runner

       * AWS Lambda

* Chapter 6:  DevOps

   * Getting started with DevOps on AWS?

       * What is DevOps?

       * What are AWS DevOps best practices

   * Developing with CI/CD

       * AWS Code Build

       * AWS Code Pipeline

       * Integrating 3rd party build servers

           * Jenkins

           * Teamcity

           * Github Actions

   * Developing with IAC

       * What is IAC?

       * Developing with Amazon CDK for IAC

           * What is CDK?

           * Working with CDK in C#

   * Developing with Terraform for IAC

* Chapter 7:  Monitoring, Instrumentation and Auditing and Testing for .NET

   * Using AWS Cloudwatch

       * Alarms, Logs, Metrics

   * Application monitoring

       * ServiceLens

       * Traces, Resource Health and Synthetic Canaries

   * Enabling SDK Metrics and Additional Tools

   * Using AWS Cloudtrail for Security Auditing

   * Continuous Delivery Key Concepts for .NET on SDK

* Chapter 8: Developing with AWS C# SDK

   * Using AWS Toolkit for Visual Studio in Depth

       * Configuring Visual Studio for AWS Toolkit

       * Special Features of Visual Studio for AWS Toolkit

   * Key SDK Features

       * Async APIs

       * Retries and Timeouts

       * Paginators

   * Working with High-level AWS Services

       * Using AWS Rekognition

       * Using AWS Comprehend

       * Using AWS Sagemaker

If you enjoyed this video, here are additional resources to look at:

Coursera + Duke Specialization: Building Cloud Computing Solutions at Scale Specialization: https://www.coursera.org/specializations/building-cloud-computing-solutions-at-scale

Python, Bash, and SQL Essentials for Data Engineering Specialization: https://www.coursera.org/specializations/python-bash-sql-data-engineering-duke

O'Reilly Book: Practical MLOps: https://www.amazon.com/Practical-MLOps-Operationalizing-Machine-Learning/dp/1098103017

O'Reilly Book: Python for DevOps: https://www.amazon.com/gp/product/B082P97LDW/

Pragmatic AI: An Introduction to Cloud-based Machine Learning: https://www.amazon.com/gp/product/B07FB8F8QP/

Pragmatic AI Labs Book: Python Command-Line Tools: https://www.amazon.com/gp/product/B0855FSFYZ

Pragmatic AI Labs Book: Cloud Computing for Data Analysis: https://www.amazon.com/gp/product/B0992BN7W8

Pragmatic AI Book: Minimal Python: https://www.amazon.com/gp/product/B0855NSRR7

Pragmatic AI Book: Testing in Python: https://www.amazon.com/gp/product/B0855NSRR7

Subscribe to Pragmatic AI Labs YouTube Channel: https://www.youtube.com/channel/UCNDfiL0D1LUeKWAkRE1xO5Q

View content on noahgift.com: https://noahgift.com/

View content on Pragmatic AI Labs Website: https://paiml.com/

• 🤖 Master GenAI Engineering - Build Production AI Systems
• 🦀 Learn Professional Rust - Industry-Grade Development
• 📊 AWS AI & Analytics - Scale Your ML in Cloud
• ⚡ Production GenAI on AWS - Deploy at Enterprise Scale
• 🛠️ Rust DevOps Mastery - Automate Everything

• 💼 Production ML Program - Complete MLOps & Cloud Mastery
• 🎯 Start Learning Now - Fast-Track Your ML Career
• 🏢 Trusted by Fortune 500 Teams

Learn end-to-end ML engineering from industry veterans at PAIML.COM