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)
Section 1: Solution and Infrastructure
Section 2: Application Development, Data, and Security
Section 3: Summary

Automotive and transportation scenarios

Our three automotive and transportation scenarios build off the lessons we covered in Chapter 6, Data Architecture. All three of our architectures are fairly lightweight (what Microsoft currently refers to as solution ideas). They aren't deployable, but they can get your mind spinning down certain architectural paths to better understand your options. (We'll see some deployable architectures in our other verticals.) For our transportation scenarios, we have divided them into one that focuses on AI (predictive insights) and two that focus on analytics (predictive monitoring and IoT analytics).

Predictive insights with vehicle telematics

Our first architecture digs into applying AI to this industry, while our other two architectures take a differently flavored approach toward IoT analytics. For our AI scenario, we're looking to discover predictive insights on the health and driving habits of our vehicle. This impacts car dealerships...