How to model and partition data in a distributed NoSQL database to achieve cloud scale

The era of cloud computing has ushered in a new era where applications now demand unprecedented levels of scale and size. Relational databases which have been with us for 50 years were never designed to ingest vast quantities of data per second, grow to Petabytes in size, or provide 99.999% availability. Enter distributed NoSQL databases which were designed specifically to deal with these and other unique challenges brought about by the cloud.

In this session we will take the relational data model for a simple e-commerce application and migrate it to a horizontally partitioned, NoSQL database. Along the way you will learn the concepts, techniques and technologies needed to model for a horizontally partitioned NoSQL database that will allow your application to achieve millisecond response times with near unlimited size and scalability.

Design high performance AI applications with native DiskANN using Azure OpenAI & Azure Cosmos DB

Azure Cosmos DB is a distributed NoSQL database providing unmatched availability, performance and scalability. Azure Cosmos DB is used by OpenAI to store all the chat history for ChatGPT allowing it to grow to 100 million daily active users in record time. This performance is now combined with the new vector capabilities of DiskANN developed by Microsoft Research. This makes it the best database service in Azure for building Intelligent, AI-enabled applications with industry-leading performance and scale.

In this session, we will explore how to build rea-time AI-enabled applications using Azure Cosmos DB. This includes how to implement RAG pattern in C# with vectorized data along-side transactional data in Azure Cosmos DB demonstrating both vector and hybrid search techniques over data with extreme throughput and concurrency. We will also demonstrate how to design and implement chat history using Cosmos DB and demonstrate how you can vectorize this data as well to analyze and improve the performance, cost and accuracy of your RAG Pattern apps.

This will be first announced at BUILD 2024. Target audience are developers.

Build high performance AI apps using Azure OpenAI & Azure Cosmos DB

Azure Cosmos DB is a distributed NoSQL database providing unmatched availability, performance and scalability and now offers vector database capabilities developed by Microsoft Research for building AI applications with industry-leading performance and scale.

In this session we’ll dive straight into vector embeddings, and what makes them different and so powerful for search. We will show how Azure Cosmos DB enables you to store your data and vectors together and perform blazing fast vector search at enormous scale, using native SDK's as well as Semantic Kernel and LangChain in both C# and Python. We will then tie all this together with more demos showing how Azure Cosmos DB can be leveraged for RAG, chat history, and semantic caching to elevate your generative AI applications to the next level. If you want to learn how to build the next generation of AI-enabled applications, attend this session to accelerate your AI readiness for the future!

Targeting developers. Features available at Microsoft BUILD in May 2024

How to build infinitely scalable Copilot applications in Azure

In this session we’ll walk you through how to build Generative AI applications in C# that can scale from the very small to a practically infinite level of size and scale. We will also cover many key concepts and implementation details required to build this new generation of applications including:

* Vector embeddings and how do they work in representing semantically similar data.
* Vectorize, index and store for effective and efficient vector queries to find semantically relevant data in a vector-enabled database.
* Enable natural conversational interactions with an LLM using a context window (chat history) for users.
* Manage request payload sizes for Azure OpenAI Service for effective token management.
* Building a semantic cache for improved performance and cost.

Growing from zero to infinity requires an architecture and design that can scale. We will cover key aspects for how to achieve this, including how to design a data model that can scale with a distributed NoSQL database, Azure Cosmos DB, which powers OpenAI's ChatGPT and allowed it to scale to 180M daily active users.

Throughout this session we will walk through the code for how to implement all of this and provide you with the code you need to learn and do this yourself.

If you want to learn how to build the next generation of AI-enabled applications in C# and Azure, attend this session to accelerate your AI readiness for the future!