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AWS for Solutions Architects

You're reading from AWS for Solutions Architects The definitive guide to AWS Solutions Architecture for migrating to, building, scaling, and succeeding in the cloud

Product type Paperback

Published in Apr 2023

Publisher Packt

ISBN-13 9781803238951

Length 692 pages

Edition 2nd Edition

Tools

AWS

Concepts

Cloud Computing

Authors (4):

Neelanjali Srivastav

Saurabh Shrivastava

Alberto Artasanchez

Imtiaz Sayed

View More author details

Table of Contents (19) Chapters

AWS for Solutions Architects, Second Edition: Design your cloud infrastructure by implementing DevOps, containers, and Amazon Web Services

1 Understanding AWS Principles and Key Characteristics FREE CHAPTER

2 Understanding AWS Well-Architected Framework and Getting Certified

3 Leveraging the Cloud for Digital Transformation

4 Networking in AWS

5 Storage in AWS – Choosing the Right Tool for the Job

6 Harnessing the Power of Cloud Computing

7 Selecting the Right Database Service

8 Best Practices for Application Security, Identity, and Compliance

9 Dive efficiency with Cloud Operation Automation and DevOps in AWS

10 Bigdata and streaming data processing in AWS

11 Datawarehouse, Data Query and Visualization in AWS

12 Machine Learning, IoT, and Blockchain in AWS

13 Containers in AWS

14 Microservice and Event-Driven Architectures

15 Domain-Driven Design

16 Data Lake Patterns – Integrating Your Data across the Enterprise

17 Availability, Reliability, and Scalability Patterns

18 AWS Hands-On Lab and Use Case

What is a data lake?

A data lake is a centralized data repository containing structured, semi-structured, and unstructured data at any scale. Data can be stored in its raw form without any transformations, or some preprocessing can be done before it is consumed. From this repository, data can be extracted and consumed to populate dashboards, perform analytics, and drive machine learning pipelines to derive insights and enhance decision-making.

Data lakes allow you to break down data silos and bring data into a single central repository. You can store various data formats at any scale and low cost. Data lakes provide you with a single source of truth and allow you access to the same data using a variety of analytics and machine-learning tools.

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Authors (4)

Saurabh Shrivastava

Saurabh Shrivastava

Saurabh Shrivastava is a technology leader, author, inventor, and public speaker with over 18 years of experience in the IT industry. He currently works at Amazon Web Services (AWS) as a Global Solutions Architect Leader and enables global consulting partners and enterprise customers on their journey to the cloud. Saurabh led the AWS global technical partnerships, set his team's vision and execution model, and nurtured multiple new strategic initiatives. Saurabh has authored various blogs and whitepapers across a diverse range of technologies, such as big data, IoT, machine learning, and cloud computing. He is passionate about the latest innovations and their impact on our society and daily life. He holds a patent in cloud platform automation. Before AWS, Saurabh worked as an enterprise solution architect, software architect, and software engineering manager in Fortune 50 enterprises, start-ups, and global product and consulting organizations.

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Imtiaz Sayed

Imtiaz Sayed

Imtiaz (Taz) Sayed leads the Worldwide Data Analytics Solutions Architecture community at AWS. He is a Principal Solutions Architect, and works with diverse customers engaging in thought leadership, strategic partnerships and specialized guidance on building modern data platforms on AWS. He is a technologist with over 20 years of experience across several domains including distributed architectures, data analytics, service mesh, databases, and DevOps.

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Alberto Artasanchez

Alberto Artasanchez

Alberto Artasanchez is a solutions architect with expertise in the cloud, data solutions, and machine learning, with a career spanning over 28 years in various industries. He is an AWS Ambassador and publishes frequently in a variety of cloud and data science publications. He is often tapped as a speaker on topics including data science, big data, and analytics. He has a strong and extensive track record of designing and building end-to-end machine learning platforms at scale. He also has a long track record of leading data engineering teams and mentoring, coaching, and motivating them. He has a great understanding of how technology drives business value and has a passion for creating elegant solutions to complicated problems.

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Neelanjali Srivastav

Neelanjali Srivastav

Neelanjali Srivastav is a technology leader, product manager, agile coach, and cloud practitioner with over 16 years of experience in the software industry. She currently works at Amazon Web Services (AWS) as a Senior Product Manager and enables global customers on their data journey to the cloud. Neelanjali evangelizes and enables AWS customer and partners in AWS database, analytics, and machine learning services. She sets the product vision and cultivates new products in incubation. Before AWS, Neelanjali led teams of software engineers, solutions architects, and systems analysts to modernize IT systems and develop innovative software solutions for large enterprises. Neelanjali has held multiple roles in the IT services industry and R&D, focusing on enterprise application management, cloud service management, and orchestration.

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