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.
Table of Contents (12 chapters)

Implementing a Big Data Application

In this chapter, we will focus on the hands-on implementation of big data applications using AWS services. More specifically, we will implement typical use cases for ETL, serverless computing, streaming data, and machine learning using AWS services such as Kinesis, EMR, Apache Spark, SageMaker, and Glue.

In this chapter, we will cover the following:

  • Setting up an Amazon Kinesis Stream
  • Creating an AWS Lambda function
  • Using Amazon Kinesis Firehose
  • Using AWS Glue and Amazon Athena
  • Using Amazon SageMaker