Book Image

Learning AWS - Second Edition

By : Aurobindo Sarkar, Amit Shah
Book Image

Learning AWS - Second Edition

By: Aurobindo Sarkar, Amit Shah

Overview of this book

Amazon Web Services (AWS) is the most popular and widely-used cloud platform. Administering and deploying application on AWS makes the applications resilient and robust. The main focus of the book is to cover the basic concepts of cloud-based development followed by running solutions in AWS Cloud, which will help the solutions run at scale. This book not only guides you through the trade-offs and ideas behind efficient cloud applications, but is a comprehensive guide to getting the most out of AWS. In the first section, you will begin by looking at the key concepts of AWS, setting up your AWS account, and operating it. This guide also covers cloud service models, which will help you build highly scalable and secure applications on the AWS platform. We will then dive deep into concepts of cloud computing with S3 storage, RDS and EC2. Next, this book will walk you through VPC, building real-time serverless environments, and deploying serverless APIs with microservices. Finally, this book will teach you to monitor your applications, automate your infrastructure, and deploy with CloudFormation. By the end of this book, you will be well-versed with the various services that AWS provides and will be able to leverage AWS infrastructure to accelerate the development process.

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Table of Contents (12 chapters)
Preface
Preface
Who this book is for
What this book covers
To get the most out of this book
Get in touch
Free Chapter
1
Cloud 101 – Understanding the Basics
Cloud 101 – Understanding the Basics
Defining cloud computing
Introducing public, private, and hybrid clouds
Introducing cloud service models – IaaS, PaaS, and SaaS
Introducing multi-tenancy models
Understanding cloud-based workloads
Setting up your AWS account
Summary
2
Designing Cloud Applications
Designing Cloud Applications
Introducing cloud-based multitier architecture
Designing for multi-tenancy
Understanding cloud applications design principles
Understanding emerging cloud-based application architectures
Estimating your cloud computing costs
A typical e-commerce web application
Summary
3
Introducing AWS Components
Introducing AWS Components
AWS components
Managing costs on AWS cloud
Application development environments
Setting up the AWS infrastructure
Summary
4
Designing for and Implementing Scalability
Designing for and Implementing Scalability
Defining scalability objectives
Designing scalable application architectures
Leveraging AWS infrastructure services for scalability
Evolving architecture against increasing loads
Event handling at scale
Setting up Auto Scaling
Summary
5
Designing for and Implementing High Availability
Designing for and Implementing High Availability
Defining availability objectives
Nature of failures
Setting up high availability
Summary
6
Designing for and Implementing Security
Designing for and Implementing Security
Defining security objectives
Understanding the security responsibilities
Best practices in implementing AWS security
Setting up security
Summary
7
Deploying to Production and Going Live
Deploying to Production and Going Live
Managing infrastructure, deployments, and support at scale
Creating and managing AWS environments using CloudFormation
Using CloudWatch for monitoring
Using AWS solutions for backup and archiving
Planning for production go-live activities
Setting up for production
Summary
8
Designing a Big Data Application
Designing a Big Data Application
Introducing big data applications
Analyzing streaming data with Amazon Kinesis
Best practices for serverless big data applications
Best practices for using Amazon EMR
Best practices for distributed machine learning and predictive analytics
Security overview for big data applications
Configuring and using EMR-Spark clusters
Summary
9
Implementing a Big Data Application
Implementing a Big Data Application
Setting up an Amazon Kinesis Stream
Creating an AWS Lambda function
Using Amazon Kinesis Firehose
Using AWS Glue and Amazon Athena
Using Amazon SageMaker
Summary
10
Deploying a Big Data System
Deploying a Big Data System
Using CloudFormation templates
Authoring and deploying serverless applications
Using AWS Serverless Application Repository
Summary
11
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Best practices for using Amazon EMR

Amazon has made working with Hadoop a lot easier. You can launch an EMR cluster in minutes for big data processing, machine learning, and real-time stream processing with the Apache Hadoop ecosystem. You can use the Management Console or the command line to start a few nodes or a thousand nodes with ease.

Like EC2, EMR pricing is now changed from pay per hour to pay per second. If you stop your cluster—you stop paying immediately. This results in lower costs and you don’t have to worry about the hourly boundary, anymore.

EMR makes a whole bunch of the latest versions of open source software available to you. There are 19 open source projects, presently. New releases are made every 4 to 6 weeks so latest versions of the open source projects are available. This is very useful especially for rapidly evolving open source projects such...

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