Book Image

Implementing Azure Cloud Design Patterns

By : Oliver Michalski, Stefano Demiliani
Book Image

Implementing Azure Cloud Design Patterns

By: Oliver Michalski, Stefano Demiliani

Overview of this book

A well designed cloud infrastructure covers factors such as consistency, maintenance, simplified administration and development, and reusability. Hence it is important to choose the right architectural pattern as it has a huge impact on the quality of cloud-hosted services. This book covers all Azure design patterns and functionalities to help you build your cloud infrastructure so it fits your system requirements. This book initially covers design patterns that are focused on factors such as availability and data management/monitoring. Then the focus shifts to complex design patterns such as multitasking, improving scalability, valet keys, and so on, with practical use cases. The book also supplies best practices to improve the security and performance of your cloud. By the end of this book, you will thoroughly be familiar with the different design and architectural patterns available with Windows Azure and capable of choosing the best pattern for your system.
Table of Contents (16 chapters)
Title Page
Dedication
Packt Upsell
Contributors
Preface
Index

Choosing the right data solution


Our first task is choosing the right data solution. Now the question immediately arises of: how do we approach this task?

Let's start with one of the big Vs. In our case, V is for variety.

What is variety?

The term variety describes the type and the nature of the data. For us, the following three types of data are relevant:

  • Structured data: Structured data is defined in a data model or in any form of schema (schema-on-write model), where the data is described. As a solution for the structured data area, the Azure platform offers the so-called Azure SQL as a service, services.

  • Semi-structured data: Semi-structured data does not have the formal structure of a data model, but contains tags or other types of markers to separate elements, and enforce hierarchies of records and fields within the data. Therefore, it is also known as the self-describing structure. Typical examples of a self-describing structure are XML or JSON. As a solution for the semi-structured data...