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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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Monitoring tweets using Logic Apps and notifying users when a popular user tweets

One of my colleagues, who works for a social grievance management project, is responsible for monitoring the problems that users post on social media platforms, such as Facebook, Twitter, and so on. Recently, he faced the problem of continuously monitoring the tweets that were posted on his customer's Twitter handle with specific hashtags. His main job was to respond quickly to the tweets by users with a huge follower count, say, users with more than 50,000 followers. So, he was looking for a solution that kept monitoring a particular hashtag and alerted him whenever a user with more than 50,000 followers tweeted so that he could quickly have his team respond to that user.

Note that for the sake of simplicity, we will have the condition check for 200 followers instead of 50,000 followers.

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