Cloud Deployment Models

• Service models:

  • Infrastructure as a service (Iaas)

  • Platform as a service (Paas)

  • Software as a service (Saas)

• Fundamentals Overview

  • Storage

  • Networking and security

  • Compute

  • Virtualization and Containers

  • Managed services

  • Databases – Relational and NoSQL

AWS

• Amazon and AWS History & Region

• AWS Management Console

• AWS Command Line Interface

• Amazon S3

  • What is a Big Data Data-Lake S3

  • Amazon S3 Integration

  • Data Lake on S3 Use-Cases

• Amazon RDS

  • What is Amazon RDS

  • Supported Database Engines

  • Features and Advantages

  • Creation Method

  • Database Engine Type & Instance Sizes

  • Amazon RDS Storage Types

  • Setting the Availability

  • RDS Parameter Groups

  • Amazon Aurora

• Amazon Redshift

  • What is Amazon Redshift

  • Amazon Redshift and S3 Integration

  • Architecture

  • Performance Optimization

  • Managing and Query Methods

  • Amazon Redshift SQL Editor

  • Settings and Configuration

  • Amazon Redshift Lab

• Amazon Athena

  • Features andAdvantages

  • Athena SQL Engine

  • Data model for Athena & Partitioning

  • Athena Table Definitions and Schema

  • Cost Considerations

  • Amazon Athena AWS Services Integrations

  • Amazon Athena Real World Projects

• Amazon Glue

  • What is AWS Glue

  • Features and Advantages

    • Main Concepts:

    • Supported data Sources

    • Supported data Targets

  • Main Components

    • Data Catalog

    • Crawlers and Classifiers

    • ETL Operations

    • Streaming ETL

    • Tables

    • Connections

    • Glue Use-Cases

• Lambda & API Gateway

  • Lambda Features and Advantages

  • Lambda Code Editor

  • Function Creation Options

  • Lambda Considerations

  • Exposure Rest API and handle events

  • Integration with sources and targets Lab

• Message Queues

  • Introduction to message queues

  • Simple Queue Service (SQS)

  • Kinesis Services

  • Kinesis Data Streams Use-Cases

  • Amazon Kinesis Pricing Method