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

Solution architecture use case

In the following sections, we will focus on a concrete use case (description follows). Our objective is to help you build a reference architecture, by using the map as your Azure compass to find the relevant options for a given business scenario.

Looking at a business scenario

Since we decided to zoom in a little more on containerization in this chapter, we will demonstrate one possible usage of containers in a workflow-like scenario.

For our example, we will consider the following requirements:

Contoso needs a configurable workflow tool that allows you to orchestrate multiple resource-intensive tasks. Each task must launch large datasets to perform in-memory calculations. For some reason, the datasets cannot be chunked into smaller pieces, which means that memory contention could quickly become an issue under a high load. A single task may take between a few minutes to an hour to complete. Workflows are completely unattended (no human interaction...