Book Image

Azure Serverless Computing Cookbook - Third Edition

By : Praveen Kumar Sreeram
Book Image

Azure Serverless Computing Cookbook - Third Edition

By: Praveen Kumar Sreeram

Overview of this book

This third edition of Azure Serverless Computing Cookbook guides you through the development of a basic back-end web API that performs simple operations, helping you understand how to persist data in Azure Storage services. You'll cover the integration of Azure Functions with other cloud services, such as notifications (SendGrid and Twilio), Cognitive Services (computer vision), and Logic Apps, to build simple workflow-based applications. With the help of this book, you'll be able to leverage Visual Studio tools to develop, build, test, and deploy Azure functions quickly. It also covers a variety of tools and methods for testing the functionality of Azure functions locally in the developer's workstation and in the cloud environment. Once you're familiar with the core features, you'll explore advanced concepts such as durable functions, starting with a "hello world" example, and learn about the scalable bulk upload use case, which uses durable function patterns, function chaining, and fan-out/fan-in. By the end of this Azure book, you'll have gained the knowledge and practical experience needed to be able to create and deploy Azure applications on serverless architectures efficiently.
Table of Contents (14 chapters)
13
Index

Pushing custom metrics details to Application Insights Analytics

At times, businesses may ask developers to provide analytics reports for a derived metric within Application Insights. So, what is a derived metric? Well, by default, Application Insights provides us with many insights into metrics, such as requests, errors, and exceptions.

We can run queries on the information that Application Insights provides using its Analytics Query Language.

In this context, requests per hour is a derived metric, and to build a new report within Application Insights, we need to feed Application Insights data regarding the newly derived metric on a regular basis. Once the required data is fed regularly, Application Insights will take care of providing reports for our analysis.

We'll be using Azure Functions to feed Application Insights with a derived metric named requests per hour:

Feeding application-derived metrics to App Insights using Azure Functions
Figure 6.15: Feed Application—derived metrics to App Insights using...