This sample shows how to take text documents as a input via BlobTrigger, does Text Summarization & Sentiment Score processing using the AI Congnitive Language service, and then outputs to another text document using BlobOutput binding. Uses Azure Functions Python v2 programming model.

This C# demo is based on azure-search-openai-demo and uses a static web app for the frontend and Azure functions for the backend API's. This solution uses the Azure Functions OpenAI triggers and binding extension for the backend capabilities.

An integration between SonarQube and MS Teams, implemented as an Azure Function.

This Quickstart uses Azure Developer command-line (azd) tools to create functions that respond to HTTP requests. After testing the code locally, you deploy it to a new serverless function app you create running in a Flex Consumption plan in Azure Functions. This follows current best practices for secure and scalable Azure Functions deployments

This Quickstart uses Azure Developer command-line (azd) tools to create functions that respond to HTTP requests. After testing the code locally, you deploy it to a new serverless function app you create running in a Flex Consumption plan in Azure Functions. This follows current best practices for secure and scalable Azure Functions deployments

Microsoft Teams notifier for Secret Scanning alerts from GitHub Advanced Security, using a GitHub App and Azure Function

This is an Azure Function that converts CSV text to JSON. It can be used standalone or as the api behind a custom connector in Power Automate.

Rachael - C# Azure Bot

This sample shows how to take text documents as a input via BlobTrigger, does Text Summarization & Sentiment Score processing using the AI Congnitive Language service, and then outputs to another text document using BlobOutput binding.

This Quickstart uses Azure Developer command-line (azd) tools to create functions that respond to HTTP requests. After testing the code locally, you deploy it to a new serverless function app you create running in a Flex Consumption plan in Azure Functions. This follows current best practices for secure and scalable Azure Functions deployments

This Quickstart uses Azure Developer command-line (azd) tools to create functions that respond to HTTP requests. After testing the code locally, you deploy it to a new serverless function app you create running in a Flex Consumption plan in Azure Functions. This follows current best practices for secure and scalable Azure Functions deployments

Demonstration of Azure Functions deployment using Github Actions workflows

This repository gathers a set of projects to increase productivity through automation of serverless services in the cloud.

This Quickstart uses Azure Developer command-line (azd) tools to create functions that respond to HTTP requests. After testing the code locally, you deploy it to a new serverless function app you create running in a Flex Consumption plan in Azure Functions. This follows current best practices for secure and scalable Azure Functions deployments

This Quickstart uses Azure Developer command-line (azd) tools to create functions that respond to HTTP requests. After testing the code locally, you deploy it to a new serverless function app you create running in a Flex Consumption plan in Azure Functions. This follows current best practices for secure and scalable Azure Functions deployments

In this project, we will create an Event Grid Topic in Azure for a publish-subscribe demo. Our subscriber will be an Azure function that is triggered by an event published to the Event Grid Topic. We will create the Azure function app, subscribe to our Event Grid Topic, and then demo it in action. We will use Postman to set up a POST request to …

This repository contains the implementation of an order processing workflow with Durable Functions in C#. The sample is deployed to Azure Functions Flex Consumption using the Azure Developer CLI (azd) and is configured with managed identity as the authentication mechanism.

This project serves as an interactive tutorial series showcasing the integration of Azure Durable Functions with Semantic Kernel, enhanced with a Flask CLI frontend. Each part of the series introduces new functionalities, from simple Q&A agents to complex orchestrations, demonstrating the power of combining cloud computing with AI.

Azure Function to create GraphQL endpoint against Cosmos DB

A Terraform module that manages the app service resources from the azurerm provider.