A complete microservice application featuring Dapr Pub-Sub, deployed to Azure Container Apps and Azure Service Bus Topics with dead-lettering support.

A complete microservice application featuring Dapr Pub-Sub, deployed to Azure Container Apps and Azure Service Bus Topics with dead-lettering support.

A complete microservice application featuring Dapr Pub-Sub, deployed to Azure Container Apps and Azure Service Bus Topics with dead-lettering support.

Create two microservices that communicate using Dapr's Service Invocation API. The Service Invocation API enables your applications to communicate reliably and securely by leveraging auto-mTLS and built-in retries

Create a microservice app to demonstrate Dapr's bindings API to work with external systems as inputs and outputs. The service listens to input binding events from a system CRON and then outputs the contents of local data to a PostreSql output binding.

Create a microservice app to demonstrate Dapr's bindings API to work with external systems as inputs and outputs. The service listens to input binding events from a system CRON and then outputs the contents of local data to a PostreSql output binding.

Create a microservice app to demonstrate Dapr's bindings API to work with external systems as inputs and outputs. The service listens to input binding events from a system CRON and then outputs the contents of local data to a PostreSql output binding.

Create two microservices that communicate using Dapr's Service Invocation API. The Service Invocation API enables your applications to communicate reliably and securely by leveraging auto-mTLS and built-in retries

Create two microservices that communicate using Dapr's Service Invocation API. The Service Invocation API enables your applications to communicate reliably and securely by leveraging auto-mTLS and built-in retries

A sample app for the Retrieval-Augmented Generation pattern running in Azure, using Azure AI Search for retrieval and Azure OpenAI large language models to power ChatGPT-style and Q&A experiences.

A Solution Accelerator for the RAG pattern running in Azure, using Azure AI Search for retrieval and Azure OpenAI large language models to power ChatGPT-style and Q&A experiences. This includes most common requirements and best practices.

A RAG app to ask questions about rows in a database table. Deployable on Azure Container Apps with PostgreSQL Flexible Server.

A blueprint for getting a React.js web app with a Java API and a MongoDB database on Azure. The blueprint includes sample application code (a ToDo web app) which can be removed and replaced with your own application code. Add your own source code and leverage the Infrastructure as Code assets (written in Bicep) to get up and running quickly.

This provides some reference use cases while using Azure API Center

A sample for implementing retrieval augmented generation using Azure Open AI to generate embeddings, Azure Cosmos DB for MongoDB vCore to perform vector search, and semantic kernel.

A FastAPI that can generate maps using the py-staticmaps package. Designed for deployment to Azure Functions + Azure CDN, using the Azure Developer CLI and Bicep files.

Sharing the learning along the way we been gathering to enable Azure OpenAI at enterprise scale in a secure manner. GPT-RAG core is a Retrieval-Augmented Generation pattern running in Azure, using Azure Cognitive Search for retrieval and Azure OpenAI large language models to power ChatGPT-style and Q&A experiences.

The reliable web app pattern is a set of objectives to help your web application converge on the cloud. This repo contains a reference implementation of a reliable web application for Java.

Intelligent enterprise-grade reference architecture for JavaScript, featuring OpenAI integration, Azure Developer CLI template and Playwright tests.

A blueprint for getting a React.js web app with Python (FastAPI) API and a MongoDB API in Cosmos database onto Azure. It includes sample application code (a ToDo web app) which can be removed and replaced with your own application code. Add your own source code and leverage the Infrastructure as Code assets (Terraform) to get up and running quickly