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Tarik Makota - Scalable Data Streaming with Amazon Kinesis: Design and secure highly available, cost-effective data streaming applications with Amazon Kinesis

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Tarik Makota Scalable Data Streaming with Amazon Kinesis: Design and secure highly available, cost-effective data streaming applications with Amazon Kinesis

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Amazon Kinesis is a collection of secure, serverless, durable, and highly available purpose-built data streaming services. This data streaming service provides APIs and client SDKs to enable you to produce and consume data at scale. This book begins with a quick overview of the core concepts of data streams along with the essentials of the AWS Kinesis landscape. Youll explore the requirements of the use case shown through the book to help you get started and cover the key pain points encountered in the data stream life cycle. As you advance, youll get to grips with the architectural components of Kinesis, understand how they are configured to build data pipelines, and delve into the applications that connect to them for consumption and processing. Youll also build a Kinesis data pipeline from scratch and learn how to implement and apply practical solutions. Youll then learn how to configure Kinesis on a cloud platform. Finally, youll learn how other AWS services can be integrated into Kinesis. These services include Redshift, Dynamo Database, AWS S3, Elastic Search, and third-party applications such as Splunk.

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Scalable Data Streaming with Amazon Kinesis Design and secure highly available - photo 1
Scalable Data Streaming with Amazon Kinesis

Design and secure highly available, cost-effective data streaming applications with Amazon Kinesis

Tarik Makota

Brian Maguire

Danny Gagne

Rajeev Chakrabarti

BIRMINGHAMMUMBAI Scalable Data Streaming with Amazon Kinesis Copyright 2021 - photo 2

BIRMINGHAMMUMBAI

Scalable Data Streaming with Amazon Kinesis

Copyright 2021 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author(s), nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

Group Product Manager: Kunal Parikh

Publishing Product Manager: Devika Battike

Senior Editor: Mohammed Yusuf Imaratwale

Content Development Editors: Sean Lobo and Tazeen Shaikh

Technical Editor: Devanshi Deepak Ayare

Copy Editor: Safis Editing

Project Coordinator: Aparna Ravikumar Nair

Proofreader: Safis Editing

Indexer: Tejal Daruwale Soni

Production Designer: Shankar Kalbhor

First published: March 2021

Production reference: 1300321

Published by Packt Publishing Ltd.

Livery Place

35 Livery Street

Birmingham

B3 2PB, UK.

ISBN 978-1-80056-540-1

www.packt.com

Contributors
About the authors

Tarik Makota hails from a small town in Bosnia. He is a principal solutions architect with AWS, a builder, a writer, and the self-proclaimed best fly fisherman at AWS. Never a perfect student, he managed to earn an MSc in software development and management from RIT. When he is not "doing the cloud" or writing, Tarik spends most of his time fly fishing to pursue slippery trout. He feeds his addiction by spending summers in Montana. Tarik lives in New Jersey with his family, Mersiha, Hana, and two exceptionally perfect dogs.

Brian Maguire is a solutions architect at AWS, where he is focused on helping customers build solutions in the cloud. He is a technologist, writer, teacher, and student who loves learning. Brian lives in New Hope, Pennsylvania, with his family, Lorna, Ciara, Chris, and several cats.

Danny Gagne is a solutions architect at AWS. He has extensive experience in the design and implementation of large-scale, high-performance analysis systems. He lives in New York City.

Rajeev Chakrabarti is a principal developer advocate with the Amazon Kinesis and the Amazon MSK team. He has worked for many years in the big data and data streaming space. Before joining the Amazon Kinesis team, he was a streaming specialist solutions architect helping customers build streaming pipelines. He lives in New Jersey with his family, Shaifalee and Anushka.

About the reviewers

Ritesh Gupta works as a software development manager with AWS, leading the control plane and data plane teams on the Kinesis Data Streams service. He has over 20 years of experience in leading and delivering geographically distributed web-scale applications and highly available distributed systems supporting millions of transactions per second; he has 10 years of experience in managing engineers and managers. Prior to Amazon, he worked at Microsoft, EA Games, Dell, and a few successful start-ups. His technical expertise cuts across building web-scale applications, enterprise software, and big data. I thank my wife, Jyothi, and daughter, Udita, for putting up with the late-night learning sessions that have allowed me to be where I am.

Randy Ridgley is an experienced technology generalist working with organizations in the media and entertainment, casino gaming, and public sector fields that are looking to adopt cloud technologies. He started his journey into software development at a young age, building BASIC programs on the Commodore 64. In his professional career, he started by building Windows applications, eventually graduating to Linux with multiple programming languages. Currently, you can find Randy spending most of his time building end-to-end real-time streaming solutions on AWS using serverless technologies and IoT.

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