Book Image

The Azure Cloud Native Architecture Mapbook

By : Stéphane Eyskens, Ed Price
Book Image

The Azure Cloud Native Architecture Mapbook

By: Stéphane Eyskens, Ed Price

Overview of this book

Azure offers a wide range of services that enable a million ways to architect your solutions. Complete with original maps and expert analysis, this book will help you to explore Azure and choose the best solutions for your unique requirements. Starting with the key aspects of architecture, this book shows you how to map different architectural perspectives and covers a variety of use cases for each architectural discipline. You'll get acquainted with the basic cloud vocabulary and learn which strategic aspects to consider for a successful cloud journey. As you advance through the chapters, you'll understand technical considerations from the perspective of a solutions architect. You'll then explore infrastructure aspects, such as network, disaster recovery, and high availability, and leverage Infrastructure as Code (IaC) through ARM templates, Bicep, and Terraform. The book also guides you through cloud design patterns, distributed architecture, and ecosystem solutions, such as Dapr, from an application architect's perspective. You'll work with both traditional (ETL and OLAP) and modern data practices (big data and advanced analytics) in the cloud and finally get to grips with cloud native security. By the end of this book, you'll have picked up best practices and more rounded knowledge of the different architectural perspectives.
Table of Contents (13 chapters)
1
Section 1: Solution and Infrastructure
6
Section 2: Application Development, Data, and Security
10
Section 3: Summary

Introducing AI solutions

AI has been on everyone's lips for many years now. In this section, we will review the most important AI concepts and their corresponding Azure services.

Figure 6.14 is a summary of Azure's AI landscape:

Figure 6.14 – AI solutions in Azure

Figure 6.14 – AI solutions in Azure

We say this is a summary because Azure Cognitive Services (alone) can be regrouped into about 20 different services. We already talked about most of these services, but this time we will take the AI-specific angle. Let's start with the machine learning and deep learning options.

Understanding machine learning and deep learning

The services depicted in Figure 6.15 are quite close, in terms of capabilities, and they are all intermingled. This makes it very hard to position them for a specific use case:

Figure 6.15 – Machine learning in Azure

Figure 6.15 – Machine learning in Azure

The only no-brainer is Azure Cognitive Services (ACS), a full set of pre-built AI capabilities...