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Azure Serverless Computing Cookbook

Azure Serverless Computing Cookbook

By : Praveen Kumar Sreeram, Marston
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Azure Serverless Computing Cookbook

Azure Serverless Computing Cookbook

By: Praveen Kumar Sreeram, Marston

Overview of this book

Microsoft provides a solution for easily running small segments of code in the cloud with Azure Functions. The second edition of Azure Serverless Computing Cookbook starts with intermediate-level recipes on serverless computing along with some use cases demonstrating the benefits and key features of Azure Functions. You’ll explore the core aspects of Azure Functions, such as the services it provides, how you can develop and write Azure Functions, and how to monitor and troubleshoot them. As you make your way through the chapters, you’ll get practical recipes on integrating DevOps with Azure Functions, and providing continuous integration and continuous deployment with Azure DevOps. This book also provides hands-on, step-by-step tutorials based on real-world serverless use cases to guide you through configuring and setting up your serverless environments with ease. You will also learn how to build solutions for complex, real-world, workflow-based scenarios quickly and with minimal code using Durable Functions. In the concluding chapters, you will ensure enterprise-level security within your serverless environment. The most common tips and tricks that you need to be aware of when working with Azure Functions on production environments will also be covered in this book. By the end of this book, you will have all the skills required for working with serverless code architecture, providing continuous delivery to your users.
Table of Contents (13 chapters)
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Introduction

When working on developing modern applications that need to be hosted on the cloud, you need to make sure that the applications are stateless. Statelessness is an essential factor for developing cloud-aware applications. For example, you should avoid persisting any data in the resource that is specific to any virtual machine (VM) instance that's provisioned to any Azure Service (for example, an app service, the API, and so on). If you do so, you cannot leverage some of the services, such as auto-scaling functionality, as the provisioning of instances is dynamic. If you depend on any VM-specific resources, you will end up facing issues with unexpected behaviors.

Having said that, the downside of the previously mentioned approach is that you end up working on identifying ways of persisting data in different mediums, depending on your application architecture.

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