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Learn how VMware has brought its enterprise-class software-defined Data Center software to the AWS Cloud. This book will show how to enable customers to run production applications across VMware vSphere®-based private, public, and hybrid cloud environments, with optimized access to AWS services. The book begins by introducing the value of VMware Cloud on AWS and talking about the different use cases that can be addressed by this SaaS solution and how it can accelerate cloud migration. In subsequent chapters, you’ll adopt a more pragmatic approach with practical examples of how to successfully plan, design and deploy VMware Cloud on AWS. VMware Cloud on AWS also covers technical requirements as well as the different options to prepare for a successful deployment and make the right decision to interconnect the solution to any existing environment through a dedicated link. In a dedicated chapter, it approaches the challenge of migrating workloads on the platform and address all the current capabilities offered by the solution and more specifically HCX, the Hybrid Cloud Extension offering that works in concert with VMware Cloud on AWS to facilitate moving complex workloads to the cloud. You’ll also review the advanced networking and security options available in the platform that help reinforce the level of security with features like traditional Gateway Firewall, Distributed Firewall, Micro-segmentation, Identity Firewall, and IDS/IPS. The book concludes with best practices to address operation tasks and get valuable insights into the VMware Cloud on AWS deployment. You will: Plan and Deploy VMware Cloud on AWS Migrate your workloads to the cloud with VMware Cloud on AWS and HCX Secure workloads on VMware Cloud on AWS Operate VMware Cloud on AWS.

Cloud computing. --- Amazon Web Services (Firm) --- VMware.

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Automate the process of building, training, and deploying machine learning applications to production with AWS solutions such as SageMaker Autopilot, AutoGluon, Step Functions, Amazon Managed Workflows for Apache Airflow, and more Key Features Explore the various AWS services that make automated machine learning easier Recognize the role of DevOps and MLOps methodologies in pipeline automation Get acquainted with additional AWS services such as Step Functions, MWAA, and more to overcome automation challenges Book Description AWS provides a wide range of solutions to help automate a machine learning workflow with just a few lines of code. With this practical book, you'll learn how to automate a machine learning pipeline using the various AWS services. Automated Machine Learning on AWS begins with a quick overview of what the machine learning pipeline/process looks like and highlights the typical challenges that you may face when building a pipeline. Throughout the book, you'll become well versed with various AWS solutions such as Amazon SageMaker Autopilot, AutoGluon, and AWS Step Functions to automate an end-to-end ML process with the help of hands-on examples. The book will show you how to build, monitor, and execute a CI/CD pipeline for the ML process and how the various CI/CD services within AWS can be applied to a use case with the Cloud Development Kit (CDK). You'll understand what a data-centric ML process is by working with the Amazon Managed Services for Apache Airflow and then build a managed Airflow environment. You'll also cover the key success criteria for an MLSDLC implementation and the process of creating a self-mutating CI/CD pipeline using AWS CDK from the perspective of the platform engineering team. By the end of this AWS book, you'll be able to effectively automate a complete machine learning pipeline and deploy it to production. What you will learn Employ SageMaker Autopilot and Amazon SageMaker SDK to automate the machine learning process Understand how to use AutoGluon to automate complicated model building tasks Use the AWS CDK to codify the machine learning process Create, deploy, and rebuild a CI/CD pipeline on AWS Build an ML workflow using AWS Step Functions and the Data Science SDK Leverage the Amazon SageMaker Feature Store to automate the machine learning software development life cycle (MLSDLC) Discover how to use Amazon MWAA for a data-centric ML process Who this book is for This book is for the novice as well as experienced machine learning practitioners looking to automate the process of building, training, and deploying machine learning-based solutions into production, using both purpose-built and other AWS services. A basic understanding of the end-to-end machine learning process and concepts, Python programming, and AWS is necessary to make the most out of this book.

Machine learning. --- Amazon Web Services (Firm)

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A non-developer's guide to harnessing the power of Amazon Honeycode apps to manage projects, customers, operations, approvals, resources, and teams Key Features A practical guide to Amazon Web Services (AWS) no-code app development for meeting specific needs of customers Create apps quickly without paying for costly developers using Honeycode's in-built templates and functions Learn how to use stable AWS services to supplement Honeycode's present limits Book Description Amazon Honeycode enables you to build fully managed, customizable, and scalable mobile and web applications for personal or professional use with little to no code. With this practical guide to Amazon Honeycode, you'll be able to bring your app ideas to life, improving your and your team's/organization's productivity. You'll begin by creating your very first app from the get-go and use it as a means to explore the Honeycode development environment and concepts. Next, you'll learn how to set up and organize the data to build and bind an app on Honeycode as well as deconstruct different templates to understand the common structures and patterns that can be used. Finally, you'll build a few apps from scratch and discover how to apply the concepts you've learned. By the end of this app development book, you'll have gained the knowledge you need to be able to build and deploy your own mobile and web applications. You'll also be able to invite and share your app with people you want to collaborate with. What you will learn Build mobile and web applications with simple drag-drops and customizations Deploy and share apps and collaborate in real-time with your team Understand how to create automated processes in apps Create a customized view for each app user or a group of users Import existing data from a CSV and build an app on top of it Create connectors to external data sources Build applications using Honeycode either from scratch or by modifying an existing template Explore Honeycode templates and understand what use cases are available out-of-the-box with these templates Who this book is for Like the platform, this book is meant for everyone - professional and novice developers alike - who want to build and deploy apps for their personal or professional use as an individual or as a team. However, for professional developers, it is important to note that the book will not focus on advanced use cases with features like using public APIs and 3P integrations. No programming knowledge or experience is needed to start creating basic apps. However, working knowledge of Microsoft Excel or similar spreadsheet tools and a general understanding of logical statements will be helpful to get the most out of this book.

Application software --- Development. --- Amazon Web Services (Firm)

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Build cost-effective and highly scalable Serverless applications using AWS Lambda. About This Book Leverage AWS Lambda to significantly lower your infrastructure costs and deploy out massively scalable, event-driven systems and applications Learn how to design and build Lambda functions using real-world examples and implementation scenarios Explore the Serverless ecosystem with a variety of toolsets and AWS services including DynamoDB, API Gateway, and much more! Who This Book Is For If you are a Cloud administrator and/or developer who wishes to explore, learn, and leverage AWS Lambda to design, build, and deploy Serverless applications in the cloud, then this is the book for you! The book assumes you have some prior knowledge and hands-on experience with AWS core services such as EC2, IAM, S3, along with the knowledge to work with any popular programming language such as Node.Js, Java, C#, and so on. What You Will Learn Understand the hype, significance, and business benefits of Serverless computing and applications Plunge into the Serverless world of AWS Lambda and master its core components and how it works Find out how to effectively and efficiently design, develop, and test Lambda functions using Node.js, along with some keen coding insights and best practices Explore best practices to effectively monitor and troubleshoot Serverless applications using AWS CloudWatch and other third-party services in the form of Datadog and Loggly Quickly design and develop Serverless applications by leveraging AWS Lambda, DynamoDB, and API Gateway using the Serverless Application Framework (SAF) and other AWS services such as Step Functions Explore a rich variety of real-world Serverless use cases with Lambda and see how you can apply it to your environments In Detail AWS is recognized as one of the biggest market leaders for cloud computing and why not? It has evolved a lot since the time it started out by providing just basic services such as EC2 and S3 and today; they go all the way from IoT to Machine Learning, Image recognition, Chatbot Frameworks, and much more! One of those recent services that is also gaining a lot of traction is AWS Lambda! Although seemingly simple and easy to use, Lambda is a highly effective and scalable compute service that provides developers with a powerful platform to design and develop Serverless event-driven systems and applications. The book begins with a high-level introduction into the world of Serverless computing a...

Application software --- Development. --- Amazon Web Services (Firm)

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Your #1 all-in-one reference and exam Study Guide for the UPDATED AWS SysOps Administrator certification! This comprehensive book guides readers through the role of a SysOps Administrator and helps prepare candidates to take the updated AWS Certified SysOps Administrator—Associate (SOA-C01) Exam. The AWS Certified SysOps Administrator—Associate certification validates technical expertise in deployment, management, and operations on the AWS platform. This Study Guide not only prepares readers for the AWS exam, but it makes sure the reader is ready to perform the duties expected of SysOps Administrators. The book focuses on the skill-set required of AWS professionals by filling in the gap between test preparation and real-world preparedness. Concepts covered include: Monitoring and Reporting High Availability Deployment and Provisioning Storage and Dada Management Security and Compliance Networking Automation and Optimization And More Readers will also have one year of free access to the Sybex interactive online learning environment and test bank, providing a suite of robust study tools including an assessment test, chapter tests, bonus practice exam, electronic flashcards, and a glossary of key terms.

Computers. --- Amazon Web Services (Firm) --- Examinations