Book Image

Serverless Integration Design Patterns with Azure

By : Abhishek Kumar, Srinivasa Mahendrakar
Book Image

Serverless Integration Design Patterns with Azure

By: Abhishek Kumar, Srinivasa Mahendrakar

Overview of this book

With more enterprises adapting cloud-based and API-based solutions, application integration has become more relevant and significant than ever before. Parallelly, Serverless Integration has gained popularity, as it helps agile organizations to build integration solutions quickly without having to worry about infrastructure costs. With Microsoft Azure’s serverless offerings, such as Logic Apps, Azure Functions, API Management, Azure Event Grid and Service Bus, organizations can build powerful, secure, and scalable integration solutions with ease. The primary objective of this book is to help you to understand various serverless offerings included within Azure Integration Services, taking you through the basics and industry practices and patterns. This book starts by explaining the concepts of services such as Azure Functions, Logic Apps, and Service Bus with hands-on examples and use cases. After getting to grips with the basics, you will be introduced to API Management and building B2B solutions using Logic Apps Enterprise Integration Pack. This book will help readers to understand building hybrid integration solutions and touches upon Microsoft Cognitive Services and leveraging them in modern integration solutions. Industry practices and patterns are brought to light at appropriate opportunities while explaining various concepts.
Table of Contents (15 chapters)

Intelligence in Integration Using Azure Cognitive Services

In October 2015, Google's artificial intelligence (AI) program Alpha Go beat Lee Sedol in the very complex board game Go. It also beat the world number one player Ke Jie in 2017. Voice recognition systems such as Cortana and Amazon Echo are not only able to identify words being spoken, but are also capable of understanding various nuances and semantics of spoken language. Netflix's recommendation engine identifies a user's taste and suggests appropriate programs. Based on millions of historical trips, tech giants such as Uber and Lyft can estimate arrival times accurately. All of these innovations can be directly attributed to major developments in the field of AI and machine learning. This development has been rapid, particularly in recent years. There are three main reasons for this trend:

  • The internet...