Azure Arc-enabled Data Services Revealed: Deploying Azure Data Services on Any Infrastructure

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Ben Weissman Anthony E. Nocentino

Azure Arc-enabled Data Services Revealed

Deploying Azure Data Services on Any Infrastructure

Ben Weissman, Anthony E. Nocentino

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English

APress
22 February 2022

Microsoft programming; Databases

Get introduced to Azure Arc-enabled Data Services and the powerful capabilities to deploy and manage local, on-premises, and hybrid cloud data resources using the same centralized management and tooling you get from the Azure cloud. This book shows how you can deploy and manage databases running on SQL Server and Postgres in your corporate data center or any cloud as if they were part of the Azure platform. This second edition has been updated to the latest codebase, allowing you to use this book as your handbook to get started with Azure Arc-enabled Data Services today. Learn how to benefit from Azure's centralized management, the automated rollout of patches and updates, managed backups, and more. This book is the perfect choice for anyone looking for a hybrid or multi-vendor cloud strategy for their data estate. The authors walk you through the possibilities and requirements to get Azure SQL Managed Instance and PostgresSQL Hyperscale deployed outside of Azure, so the services are accessible to companies that cannot move to the cloud or do not want to use the Microsoft cloud exclusively. The technology described in this book will benefit those required to keep sensitive services, such as medical databases, away from the public cloud equally as those who can’t move to a public cloud for other reasons such as infrastructure constraints but still want to benefit from the Azure cloud and the centralized management and tooling that it supports.

What You Will Learn

Understand the fundamentals and architecture of Azure Arc-enabled data services

Build a multi-cloud strategy based on Azure Data Services Deploy Azure Arc-enabled data services on premises or in any cloud Deploy Azure Arc-enabled SQL Managed Instance on premises or in any cloud Deploy Azure Arc-enabled PostgreSQL Hyperscale on premises or in any cloud Backupand Restore your data that is managed by Azure Arc-enabled data services Manage Azure-enabled data services running outside of Azure Monitor Azure-enabled data services through Grafana and Kibana Monitor Azure-enabled data services running outside of Azure through Azure Monitor

Who This Book Is For Database administrators and architects who want to manage on-premises or hybrid cloud data resources from the Microsoft Azure cloud. Especially for those wishing to take advantage of cloud technologies while keeping sensitive data on premises and under physical control.

By: Ben Weissman, Anthony E. Nocentino
Imprint: APress
Country of Publication: United States
Edition: 2nd ed.
Dimensions: Height: 254mm, Width: 178mm,
Weight: 375g
ISBN: 9781484280843
ISBN 10: 1484280849
Pages: 173
Publication Date: 22 February 2022
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active

Ben Weissman is the owner and founder of Solisyon, a consulting firm based in Germany and focused on business intelligence, business analytics, and data warehousing. He is a Microsoft Data Platform MVP, the first German BimlHero, and has been working with SQL Server since SQL Server 6.5. Ben is also an MCSE, Charter Member of the Microsoft Professional Program for Big Data, Artificial Intelligence, and Data Science, and he is a Certified Data Vault Data Modeler. If he is not currently working with data, he is probably travelling to explore the world. Anthony E. Nocentino is the Founder and President of Centino Systems as well as a Pluralsight author, a Microsoft Data Platform MVP, and an industry recognized Kubernetes, SQL Server, and Linux expert. In his consulting practice, Anthony designs solutions, deploys the technology, and provides expertise on system performance, architecture, and security. He has bachelor's and master's degrees in computer science, with research publications in machine virtualization, high performance/low latency data access algorithms, and spatial database systems.