Book description
Access detailed content and examples on Azure SQL, a set of cloud services that allows for SQL Server to be deployed in the cloud. This book teaches the fundamentals of deployment, configuration, security, performance, and availability of Azure SQL from the perspective of these same tasks and capabilities in SQL Server. This distinct approach makes this book an ideal learning platform for readers familiar with SQL Server on-premises who want to migrate their skills toward providing cloud solutions to an enterprise market that is increasingly cloud-focused.- Know the history of Azure SQL
- Deploy, configure, and connect to Azure SQL
- Choose the correct way to deploy SQL Server in Azure
- Migrate existing SQL Server instances to Azure SQL
- Monitor and tune Azure SQL’s performance to meet your needs
- Ensure your data and application are highly available
- Secure your data from attack and theft
Table of contents
- Cover
- Front Matter
- 1. SQL Server Rises to the Clouds
- 2. What Is Azure SQL?
- 3. SQL Server on Azure Virtual Machine
- 4. Deploying Azure SQL
- 5. Configuring Azure SQL
- 6. Securing Azure SQL
- 7. Monitoring and Tuning Performance for Azure SQL
- 8. Availability for Azure SQL
- 9. Completing Your Knowledge of Azure SQL
- 10. Go Big with the Cloud
- Back Matter
Product information
- Title: Azure SQL Revealed: A Guide to the Cloud for SQL Server Professionals
- Author(s):
- Release date: October 2020
- Publisher(s): Apress
- ISBN: 9781484259313
You might also like
video
Python Fundamentals
51+ hours of video instruction. Overview The professional programmer’s Deitel® video guide to Python development with …
book
Clean Code: A Handbook of Agile Software Craftsmanship
Even bad code can function. But if code isn't clean, it can bring a development organization …
book
Implementing Azure DevOps Solutions
A comprehensive guide to becoming a skilled Azure DevOps engineer Key Features Explore a step-by-step approach …
book
Data Science from Scratch, 2nd Edition
To really learn data science, you should not only master the tools—data science libraries, frameworks, modules, …