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Code Repository for Work with RDS and DynamoDB: AWS with Python and Boto3 Series, Published by Packt

Work with RDS and DynamoDB: AWS with Python and Boto3 Series

This is the code repository for Work with RDS and DynamoDB: AWS with Python and Boto3 Series, published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.

About the Video Course

In this course, we’ll start by looking at the tools and the environment that is needed to work with AWS resources. We’ll be using Python, 3 and as per the IDE, we recommend you to use PyCharm from Jetbrains. It has a free community edition. After setting up your environment on both MacOS and Windows, we’ll create our credentials for AWS as being the AWS Access Key and AWS Secret Access Key for programmatic access to AWS resources. You’ll learn how you can set your AWS credentials globally on your computers using AWS CLI. Before jumping into the implementation, for one last tip, we’ll show you how you can have auto-complete capabilities on your PyCharm IDE with PyBoto3! Once we’re ready with our environment setup, we’ll start implementing our solution on AWS! And remember, we’ll do everything with Python code. Nothing will be done manually. We’ll start off with RDS or Relational Database Service from AWS. I’ll teach you how to launch your own Amazon RDS Instances purely with your Python code! Then, we’ll learn how to take a snapshot or namely backup our complete database instance. Later, I’ll teach you how to restore that snapshot that you have created earlier so that you can recover your database from failures! Next up is DynamoDB! With this very-popular NoSQL service from AWS, I’ll teach you how to create your own DynamoDB Tables on AWS with Python! You’ll learn how to provide a key schema, attribute definitions, and apply throughout to your tables.

The codes and caption files for this course are available at:

What You Will Learn

  • Develop a fully scalable solution on Azure using PaaS services to easily manage your users' traffic peaks
  • Design your application's architecture as cloud-native and asynchronous in nature to allow better cost savings and higher profits.
  • Deploy your solution as a Web App, a container, or a fully managed Kubernetes cluster; forget about operating a website and focus more on business leads.
  • Deploy databases and caching solutions on Azure to save costs and be protected from DDoS and other attacks.
  • Develop customer-centric engagement and retention solutions using best-in-class AI and Machine Learning solutions on Azure, so that you can reach them quickly, even on vacations.
  • Secure your web application with Azure AD, an Identity-as-a-Service service, enabling you to authenticate your users and secure their data in the GDPR world.
  • Safely balance your traffic loads across several nodes on the cloud/or off the cloud, so that you can provide the best experience to your users, even during sales

Instructions and Navigation

Assumed Knowledge

To fully benefit from the coverage included in this course, you will need:
This course is designed for beginners on AWS,Cloud Architect Associate Exam Preppers who wants to practice their theories with real projects and for those Who wants to learn how to implement Infrastructure-as-a-Code or IaaS on AWS and how to develop infrastructures on AWS using Python.

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