Unlock the power of AWS to create resilient cloud architectures on AWS and operate your business efficiently using best practices Key Features Transform chaos into reliability with real-world case studies and cutting-edge methods to design robust AWS architectures Minimize downtime and protect business revenue through battle-tested architectural strategies Implement scalable architecture solutions on AWS using proven patterns and best practices <l

Serverless Architecture with AWS begins with an introduction to the serverless model and helps you get started with AWS and Lambda. You&apos;ll also get to grips with other capabilities of the AWS Serverless Platform and see how AWS supports enterprise-grade serverless applications with and without Lambda.This book will guide you in deploying your first serverless project and exploring the capabilities of serverless Amazon Athena, an interactive query service that makes it easy to analyze data in Amazon Simple Storage Service (S3 Amazon) using standard SQL. You’ll also learn about AWS Glue, a fully managed ETL service that makes categorizing data easy and cost-effective. You&apos;ll study how Amazon Kinesis makes it possible to unleash the potential of real-time data insights and analytics with capabilities such as video streams, data streams, data firehose, and data analytics. Last but not least, you’ll be equipped to combine Amazon Kinesis capabilities with AWS Lambda to create lightweight serverless architectures.By the end of the book, you will be ready to create and run your first serverless application that takes advantage of the high availability, security, performance, and scalability of AWS.

When we wrote the first edition of Building Evolutionary Architectures in 2017, the idea of evolving software architecture was still somewhat radical. During one of her first presentations about the subject, Rebecca was approached afterward by someone accusing her of being professionally irresponsible for suggesting that software architecture can evolve over time—after all, the...(展开全部)

This book is for all IT professionals, system administrators, security analysts, solution architects, and chief information security officers who are responsible for securing workloads in AWS for their organizations.

Green roofs, artificial mountains and geological forms; buildings you walk on or over; networks of ramps and warped surfaces; buildings that carve into the ground or landscapes lifted high into the air: all these are commonplace in architecture today. New technologies, new design techniques and a demand for enhanced environmental performance have provoked a re-thinking of archi...(展开全部)

The software development ecosystem is constantly changing, providing a constant stream of new tools, frameworks, techniques, and paradigms. Over the past few years, incremental developments in core engineering practices for software development have created the foundations for rethinking how architecture changes over time, along with ways to protect important architectural char...(展开全部)

The software development ecosystem is constantly changing, providing a constant stream of new tools, frameworks, techniques, and paradigms. Over the past few years, incremental developments in core engineering practices for software development have created the foundations for rethinking how architecture changes over time, along with ways to protect important architectural char...(展开全部)

Companies today are moving rapidly to integrate generative AI into their products and services. But there's a great deal of hype (and misunderstanding) about the impact and promise of this technology. With this book, Chris Fregly, Antje Barth, and Shelbee Eigenbrode from AWS help CTOs, ML practitioners, application developers, business analysts, data engineers, and data scienti...(展开全部)

AWS is constantly driving new innovations that empower data scientists to explore a variety of machine learning (ML) cloud services. This book is your comprehensive reference for learning and implementing advanced ML algorithms in AWS cloud.As you go through the chapters, you’ll gain insights into how these algorithms can be trained, tuned and deployed in AWS using Apache Spark on Elastic Map Reduce (EMR), SageMaker, and TensorFlow. While you focus on algorithms such as XGBoost, linear models, factorization machines, and deep nets, the book will also provide you with an overview of AWS as well as detailed practical applications that will help you solve real-world problems. Every practical application includes a series of companion notebooks with all the necessary code to run on AWS. In the next few chapters, you will learn to use SageMaker and EMR Notebooks to perform a range of tasks, right from smart analytics, and predictive modeling, through to sentiment analysis. By the end of this book, you will be equipped with the skills you need to effectively handle machine learning projects and implement and evaluate algorithms on AWS.

If you are an I.T. professional or a system architect who wants to improve infrastructure using AWS, then this book is for you. It is also for programmers who are new to AWS and want to build highly efficient, scalable applications.