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Cloud Data Design, Orchestration, and Management Using Microsoft Azure: Master and Design a Solution Leveraging the Azure Data Platform 1st ed. [Mīkstie vāki]

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  • Formāts: Paperback / softback, 438 pages, height x width: 254x178 mm, weight: 8496 g, 302 Illustrations, black and white; XVIII, 438 p. 302 illus., 1 Paperback / softback
  • Izdošanas datums: 29-Jun-2018
  • Izdevniecība: APress
  • ISBN-10: 1484236149
  • ISBN-13: 9781484236147
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Cloud Data Design, Orchestration, and Management Using Microsoft Azure: Master and Design a Solution Leveraging the Azure Data Platform 1st ed.Palielināt
  • Formāts: Paperback / softback, 438 pages, height x width: 254x178 mm, weight: 8496 g, 302 Illustrations, black and white; XVIII, 438 p. 302 illus., 1 Paperback / softback
  • Izdošanas datums: 29-Jun-2018
  • Izdevniecība: APress
  • ISBN-10: 1484236149
  • ISBN-13: 9781484236147
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9781484236147.html
Keywords:
Use Microsoft Azure to optimally design your data solutions and save time and money. Scenarios are presented covering analysis, design, integration, monitoring, and derivatives.

This book is about data and provides you with a wide range of possibilities to implement a data solution on Azure, from hybrid cloud to PaaS services. Migration from existing solutions is presented in detail. Alternatives and their scope are discussed. Five of six chapters explore PaaS, while one focuses on SQL Server features for cloud and relates to hybrid cloud and IaaS functionalities.

What You'll Learn
  • Know the Azure services useful to implement a data solution
  • Match the products/services used to your specific needs
  • Fit relational databases efficiently into data design
  • Understand how to work with any type of data using Azure hybrid and public cloud features
  • Use non-relational alternatives to solve even complex requirements
  • Orchestrate data movement using Azure services
  • Approach analysis and manipulation according to the data life cycle

Who This Book Is For

Software developers and professionals with a good data design background and basic development skills who want to learn how to implement a solution using Azure data services

About the Authors ix
About the Technical Reviewers xi
Foreword xiii
Introduction xvii
Chapter 1 Working with Azure Database Services Platform
1(82)
Understanding the Service
1(7)
Connectivity Options
3(2)
Sizing & Tiers
5(3)
Designing SQL Database
8(12)
Multi-tenancy
9(4)
Index Design
13(7)
Migrating an Existing Database
20(5)
Preparing the Database
20(2)
Moving the Database
22(3)
Using SQL Database
25(23)
Design for Failures
26(3)
Split between Read/Write Applications
29(5)
Hot Features
34(3)
Development Environments
37(2)
Worst Practices
39(9)
Scaling SQL Database
48(8)
Managing Elasticity at Runtime
51(2)
Pooling Different DBs Under the Same Price Cap
53(2)
Scaling Up
55(1)
Governing SQL Database
56(22)
Security Options
56(7)
Backup options
63(2)
Monitoring Options
65(13)
MySQL and PostgreSQL
78(4)
MySQL
79(2)
PostgreSQL
81(1)
Summary
82(1)
Chapter 2 Working with SQL Server on Hybrid Cloud and Azure IaaS
83(86)
Database Server Execution Options On Azure
84(1)
A Quick Overview of SQL Server 2017
85(9)
Installation of SQL Server 2017 on Linux and Docker
87(4)
SQL Server Operations Studio
91(3)
Hybrid Cloud Features
94(38)
Azure Storage
95(9)
Backup to Azure Storage
104(22)
SQL Server Stretched Databases
126(6)
Migrate databases to Azure laaS
132(5)
Migrate a Database Using the Data-Tier Application Framework
134(3)
Run SQL Server on Microsoft Azure Virtual Machines
137(15)
Why Choose SQL Server on Azure Virtual Machines
137(2)
Azure Virtual Machines Sizes and Preferred Choice for SQL Server
139(6)
Embedded Features Available and Useful for SQL Server
145(3)
Design for Storage on SQL Server in Azure Virtual Machines
148(4)
Considerations on High Availability and Disaster Recovery Options with SQL Server on Hybrid Cloud and Azure IaaS
152(15)
Hybrid Cloud HA/DR Options
153(4)
Azure only HA/DR Options
157(10)
Summary
167(2)
Chapter 3 Working with NoSQL Alternatives
169(94)
Understanding NoSQL
169(6)
Simpler Options
172(1)
Document-oriented NoSQL
173(2)
NoSQL alternatives in Microsoft Azure
175(1)
Using Azure Storage Blobs
175(26)
Understanding Containers and Access Levels
176(3)
Understanding Redundancy and Performance
179(13)
Understanding Concurrency
192(4)
Understanding Access and Security
196(5)
Using Azure Storage Tables
201(15)
Planning and Using Table Storage
202(6)
Understanding Monitoring
208(7)
Using Azure Monitor
215(1)
Using Azure Redis Cache
216(24)
Justifying the Caching Scenario
216(7)
Understanding Features
223(10)
Understanding Management
233(7)
Using Azure Search
240(21)
Using SQL to Implement Search
242(3)
Understanding How to Start with Azure Search
245(3)
Planning Azure Search
248(6)
Implementing Azure Search
254(7)
Summary
261(2)
Chapter 4 Orchestrate Data with Azure Data Factory
263(64)
Azure Data Factory Introduction
263(9)
Main Advantages of using Azure Data Factory
265(1)
Terminology
266(6)
Azure Data Factory Administration
272(1)
Designing Azure Data Factory Solutions
272(44)
Exploring Azure Data Factory Features using Copy Data
273(15)
Anatomy of Azure Data Factory JSON Scripts
288(9)
Azure Data Factory Tools for Visual Studio
297(4)
Working with Data Transformation Activities
301(13)
Microsoft Data Management Gateway
314(2)
Considerations of Performance, Scalability and Costs
316(6)
Copy Activities
317(4)
Costs
321(1)
Azure Data Factory v2 (Preview)
322(3)
Azure Data Factory v2 Key Concepts
322(3)
Summary
325(2)
Chapter 5 Azure Data Lake Store and Azure Data Lake Analytics
327(66)
How Azure Data Lake Store and Analytics were Born
329(1)
Azure Data Lake Store
330(33)
Key Concepts
330(2)
Hadoop Distributed File System
332(1)
Create an Azure Data Lake Store
333(3)
Common Operations on Files in Azure Data Lake Store
336(5)
Copy Data to Azure Data Lake Store
341(20)
Considerations on Azure Data Lake Store Performance
361(2)
Azure Data Lake Analytics
363(28)
Key Concepts
363(1)
Built on Apache YARN
364(2)
Tools for Managing ADLA and Authoring U-SQL Scripts
366(5)
U-SQL Language
371(20)
Azure HDInsight
391(1)
Summary
392(1)
Chapter 6 Working with In-Transit Data and Analytics
393(34)
Understanding the Need for Messaging
394(24)
Use Cases of Uni-Directional Messaging
396(3)
Using Service Bus
399(10)
Using Event Hubs
409(9)
Understanding Real-Time Analytics
418(7)
Understanding Stream Analytics
419(3)
Understanding AppInsights
422(3)
Summary
425(2)
Index 427
Francesco Diaz joined Insight in 2015 and is responsible for the cloud solutions & services area for a few countries in the EMEA region. In his previous work experience, Francesco worked at Microsoft for several years, in Services, Partner, and Cloud & Enterprise divisions. He is passionate about data and cloud, and he speaks about these topics at events and conferences. Roberto Freato works as a freelance consultant for tech companies, helping to kick off IT projects, defining architectures, and prototyping software artifacts. He has been awarded the Microsoft MVP award for seven years in a row and has written books about Microsoft Azure. He loves to participate in local communities and speaks at conferences during the year.