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Best AWS Books

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Best AWS Books

Here is the list of the Best AWS Books for Beginners and Advanced in 2022 to learn. Read this list of best AWS books for beginners and if you found any Best AWS Books for Beginners to advanced is missing please comment on the Best AWS books name so that we can add them and update the list.

7 Best AWS Books for Beginners and Advanced:

Best AWS Books for Beginners to advanced are listed for you, enjoy this list by reading.

AWS Cookbook: Recipes for Success on AWS

This practical guide provides over 70 self-contained recipes to help you creatively solve common AWS challenges you’ll encounter on your cloud journey. If you’re comfortable with rudimentary scripting and general cloud concepts, this cookbook provides what you need to address foundational tasks and create high-level capabilities.

Authors John Culkin and Mike Zazon share real-world examples that incorporate best practices. Each recipe includes a diagram to visualize the components. Code is provided so that you can safely execute in an AWS account to ensure solutions work as described.

From there, you can customize the code to help construct an application or fix an existing problem. Each recipe also includes a discussion to provide context, explain the approach, and challenge you to explore the possibilities further.

Go beyond theory and learn the details you need to successfully build on AWS. The recipes help you:

  • Redact personal identifiable information (PII) from text using Amazon Comprehend
  • Automate password rotation for Amazon RDS databases
  • Use VPC Reachability Analyzer to verify and troubleshoot network paths
  • Lock down Amazon Simple Storage Service (S3) buckets
  • Analyze AWS Identity and Access Management policies
  • Autoscale a containerized service

View this Book on Amazon

AWS for System Administrators: Build, automate, and manage your infrastructure on the most popular cloud platform – AWS

AWS for System Administrators will help you to learn several advanced cloud administration concepts for deploying, managing, and operating highly available systems on AWS.

Starting with the fundamentals of identity and access management (IAM) for securing your environment, this book will gradually take you through AWS networking and monitoring tools. As you make your way through the chapters, you’ll get to grips with VPC, EC2, load balancer, Auto Scaling, RDS database, and data management.

The book will also show you how to initiate AWS automated backups and store and keep track of log files. Later, you’ll work with AWS APIs and understand how to use them along with CloudFormation, Python Boto3 Script, and Terraform to automate infrastructure.

By the end of this AWS book, you’ll be ready to build your two-tier startup with all the necessary infrastructure, monitoring, and logging components in place.

What you will learn

  • Adopt a security-first approach by giving users minimum access using IAM policies
  • Build your first Amazon Elastic Compute Cloud (EC2) instance using the AWS CLI, Boto3, and Terraform
  • Set up your datacenter in AWS Cloud using VPC
  • Scale your application based on demand using Auto Scaling
  • Monitor services using CloudWatch and SNS
  • Work with centralized logs for analysis (CloudWatch Logs)
  • Back up your data using Amazon Simple Storage Service (Amazon S3), Data Lifecycle Manager, and AWS Backup

Who this book is for

This Amazon Web Services book is for system administrators and solution architects who want to build highly available and flexible AWS Cloud platforms for their applications. Software engineers and programmers looking to deploy their applications to AWS Cloud will also find this book useful. Basic knowledge of Linux and AWS is necessary to get started.

View this Book on Amazon

Data Science on AWS: Implementing End-to-End, Continuous AI and Machine Learning Pipelines

With this practical book, AI and machine learning practitioners will learn how to successfully build and deploy data science projects on Amazon Web Services. The Amazon AI and machine learning Books stack unifies data science, data engineering, and application development to help level up your skills.

This guide shows you how to build and run pipelines in the cloud, then integrate the results into applications in minutes instead of days. Throughout the book, authors Chris Fregly and Antje Barth demonstrate how to reduce cost and improve performance.

  • Apply the Amazon AI and ML stack to real-world use cases for natural language processing, computer vision, fraud detection, conversational devices, and more
  • Use automated machine learning to implement a specific subset of use cases with SageMaker Autopilot
  • Dive deep into the complete model development lifecycle for a BERT-based NLP use case including data ingestion, analysis, model training, and deployment
  • Tie everything together into a repeatable machine learning operations pipeline
  • Explore real-time ML, anomaly detection, and streaming analytics on data streams with Amazon Kinesis and Managed Streaming for Apache Kafka
  • Learn security best practices for data science projects and workflows including identity and access management, authentication, authorization, and more

View this Book on Amazon

Hands-On AWS Penetration Testing with Kali Linux: Set up a virtual lab and pentest major AWS services, including EC2, S3, Lambda, and CloudFormation

This book aims to help pentesters as well as seasoned system administrators with a hands-on approach to pentesting the various cloud services provided by Amazon through AWS using Kali Linux. To make things easier for novice pentesters, the book focuses on building a practice lab and refining penetration testing with Kali Linux on the cloud.

This is helpful not only for beginners but also for pentesters who want to set up a pentesting environment in their private cloud, using Kali Linux to perform a white-box assessment of their own cloud resources.

Besides this, there is a lot of in-depth coverage of the large variety of AWS services that are often overlooked during a pentest ― from serverless infrastructure to automated deployment pipelines.

By the end of this book, you will be able to identify possible vulnerable areas efficiently and secure your AWS cloud environment.

What you will learn

  • Familiarize yourself with and pentest the most common external-facing AWS services
  • Audit your own infrastructure and identify flaws, weaknesses, and loopholes
  • Demonstrate the process of lateral and vertical movement through a partially compromised AWS account
  • Maintain stealth and persistence within a compromised AWS account
  • Master a hands-on approach to pentesting
  • Discover a number of automated tools to ease the process of continuously assessing and improving the security stance of an AWS infrastructure

Who this book is for

If you are a security analyst or a penetration tester and are interested in exploiting Cloud environments to reveal vulnerable areas and secure them, then this book is for you.

A basic understanding of penetration testing, cloud computing, and its security concepts is mandatory.

View this Book on Amazon

AWS Lambda in Action: Event-driven serverless applications

AWS Lambda in Action is an example-driven tutorial that teaches you how to build applications that use an event-driven approach on the back-end. Starting with an overview of AWS Lambda, the book moves on to show you common examples and patterns that you can use to call Lambda functions from a web page or a mobile app.

The second part of the book puts these smaller examples together to build larger applications. By the end, you’ll be ready to create applications that take advantage of the high availability, security, performance, and scalability of AWS.

What’s Inside

  • Create a simple API
  • Create an event-driven media-sharing application
  • Secure access to your application in the cloud
  • Use functions from different clients like web pages or mobile apps
  • Connect your application with external services

View this Book on Amazon

Data Engineering with AWS: Learn how to design and build cloud-based data transformation pipelines using AWS

Written by a Senior Data Architect with over twenty-five years of experience in the business, Data Engineering for AWS is a book whose sole aim is to make you proficient in using the AWS ecosystem. Using a thorough and hands-on approach to data, this book will give aspiring and new data engineers a solid theoretical and practical foundation to succeed with AWS.

As you progress, you’ll be taken through the services and the skills you need to architect and implement data pipelines on AWS. You’ll begin by reviewing important data engineering concepts and some of the core AWS services that form a part of the data engineer’s toolkit.

You’ll then architect a data pipeline, review raw data sources, transform the data, and learn how the transformed data is used by various data consumers. You’ll also learn about populating data marts and data warehouses along with how a data lakehouse fits into the picture.

Later, you’ll be introduced to AWS tools for analyzing data, including those for ad-hoc SQL queries and creating visualizations. In the final chapters, you’ll understand how the power of machine learning and artificial intelligence can be used to draw new insights from data.

By the end of this AWS book, you’ll be able to carry out data engineering tasks and implement a data pipeline on AWS independently.

What you will learn

  • Understand data engineering concepts and emerging technologies
  • Ingest streaming data with Amazon Kinesis Data Firehose
  • Optimize, denormalize, and join datasets with AWS Glue Studio
  • Use Amazon S3 events to trigger a Lambda process to transform a file
  • Run complex SQL queries on data lake data using Amazon Athena
  • Load data into a Redshift data warehouse and run queries
  • Create a visualization of your data using Amazon QuickSight
  • Extract sentiment data from a dataset using Amazon Comprehend

Who this book is for

This book is for data engineers, data analysts, and data architects who are new to AWS and looking to extend their skills to the AWS cloud. Anyone new to data engineering who wants to learn about the foundational concepts while gaining practical experience with common data engineering services on AWS will also find this book useful.

A basic understanding of big data-related topics and Python coding will help you get the most out of this book but it’s not a prerequisite. Familiarity with the AWS console and core services will also help you follow along.

View this Book on Amazon

Conclusion:

Up to now, we have discussed the 9 Best AWS Books for Beginners, and also some best AWS Books for Beginners to Advanced Learners.

Still, if you find some of the Best AWS books for beginners to advanced are missing then please comment in the comment section. Thanks for reading the Best AWS books for beginners.

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