Modern Data Protection: Ensuring Recoverability of All Modern Workloads

Author:

Mike Loukides

Publisher:

Shroff/O'Reilly

Rs1500

Availability: Available

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Publisher

Shroff/O'Reilly

Publication Year 2021
ISBN-13

9789391043346

ISBN-10 9789391043346
Binding

Paperback

Number of Pages 388 Pages
Language (English)
Dimensions (Cms) 20X14X4
Weight (grms) 600
Give your organization the data protection it deserves without the uncertainty and cost overruns experienced by your predecessors or other companies. System and network administrators have their work cut out for them to protect physical and virtual machines in the data center and the cloud; mobile devices including laptops and tablets; SaaS services like Microsoft 365, Google Workspace, and Salesforce; and persistent data created by Kubernetes and container workloads. To help you navigate the breadth and depth of this challenge, this book presents several solutions so you can determine which is right for your company. You'll learn the unique requirements that each workload presents, then explore various categories of commercial backup hardware, software, and services available to protect these data sources, including the advantages and disadvantages of each approach. Learn the workload types that your organization should be backing up Explore the hardware, software, and services you can use to back up your systems Understand what's wrong with your current data protection system Pair your backed-up workloads to the appropriate backup system Learn the adjustments that will make your backups better, without wasting money

Mike Loukides

Mike Loukides is vice president of content strategy for O’Reilly Media. He’s edited many highly regarded books on technical subjects that don’t involve Windows programming. He’s particularly interested in programming languages, Unix and what passes for Unix these days, and system and network administration. Mike is the author of System Performance Tuning and a coauthor of Unix Power Tools. Most recently, he’s been fooling around with data and data analysis, languages like R, Mathematica, and Octave, and thinking about how to make books social.
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