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Serverless Integration Design Patterns with Azure

By : Abhishek Kumar, Mahendrakar

4 (1)

Buy this Book

Serverless Integration Design Patterns with Azure

4 (1)

By: Abhishek Kumar, Mahendrakar

Buy this Book

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.

Preface

Who this book is for

What this book covers

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Free Chapter

Serverless Integration with Microsoft Azure

Introduction to serverless in the cloud

Benefits and disadvantages of serverless architecture

Azure Integration Services

Azure Logic Apps – cloud workflow engine

Azure Service Bus – cloud messaging service

Azure API Management – API gateway

Azure Functions

Azure Event Grid – event-handling platform

Summary

Azure Functions and Enterprise Integration

Azure Functions hosting architecture

Sample Azure Function

Understanding the components of an Azure Function

Sample scenario continued

Azure Function use cases

Important considerations when building Azure Functions

Durable Functions

Creating a sample durable function

Summary

Introduction to Azure Event Grid

Eventing or messaging for enterprise solutions

Event sources and event handlers

Azure Event Grid topics

Azure Event Grid security and authentication

Publishing events through custom topics

Azure Event Grid management access control

Azure Event Grid message delivery retry and event filtering

Dead-letter events with Azure Event Grid

Event filtering through Azure Event Grid subscription

Example 1 – storage events and Logic Apps single event listener

Example 2 – custom Azure Event Grid topic and event broadcast

Azure Event Grid domain for enterprise integration

Summary

Azure API Management

The API Management platform

Logistical company ShipAnyWhere – case study

Creating an APIM service

Creating REST endpoints for the ShipAnyWhere product service

Creating a SOAP pass through an API

Creating purchase order APIs with Logic Apps and Azure Functions

Handling large messages in hybrid integration scenarios

Versioning and production testing Logic Apps

Summary

Azure Service Bus with Integration Services

Azure Service Bus use cases

Summary

Introduction to Logic Apps

The components of Azure Logic Apps

An overview of triggers

Actions in Logic Apps

Parameters in the Logic Apps workflow template

Outputs in the Logic Apps workflow template

Example 1 – Debatching in Logic Apps with the splitOn property and Azure Functions change feed with Cosmos DB

Example 2 – Concurrency control and singleton patterns in Logic Apps with schema validation

Summary

Control Flow Actions and Custom Connectors

Logic Apps control flow actions

The workflow expression language and content types

Custom connectors and Cosmos graph databases

Summary

Patterns with Azure Integration Services

Azure Functions and Logic Apps

Example 1 – The batching or aggregator pattern in Logic Apps

Example 2 – Asynchronous patterns for long-running APIs

Example 3 – Messages with API Management, Event Grid, Logic App, and Azure Functions

Example 4 – Session Management with Logic Apps and Service Bus

Summary

B2B/EDI Solutions for Enterprise Integration with Azure Logic Apps

Enterprise integration pack

B2B scenario

Creating integration accounts

Uploading certificates to Azure Key Vault

Uploading schemas and maps

Creating partners in an integration account

Creating AS2 agreements

Creating an X12 agreement

Creating the ContosoSendOrder Logic App

The Logic Apps B2B solution

Handling EDI batches

B2B disaster recovery

Summary

Hybrid Integration, BizTalk Server 2016 and an On-Premises Data Gateway

Introduction to hybrid integration

Why hybrid integration?

Introduction to the on-premises data gateway

Enabling Hybrid Integration with Microsoft BizTalk Server 2016

The Logic Apps adapter

Summary

Intelligence in Integration Using Azure Cognitive Services

Machine learning and digital transformation

Microsoft and the democratization of AI

The Microsoft AI platform

Intelligence in serverless integration

Case study – ShipAnywhere feedback analysis

Summary

DevOps for Azure Integration

Benefits of DevOps

DevOps for integration

ARM templates

Azure Event Grid and DevOps

Azure API Management and DevOps with Git version control

Azure Functions with DevOps

Logic Apps continuous integration and deployment with DevOps

Summary

Monitoring for Azure Integration

Types of monitoring

Different types of monitoring

Sending notifications of issues or events

Benefits of monitoring

Azure integration service monitoring

Azure Service Bus monitoring with Serverless360

Setting up monitoring in Serverless360

Summary

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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: