6:00 PM - 7:00 PM (UTC)

Cosmos DB is designed out of the box to support both high throughput and high availability, with great features like turnkey Global Replication and Managed Failover. However, for a solution to make the best of these features it’s important to understand how to architect the platform and your applications correctly. This session will discuss how high availability works in Cosmos DB, with a particular focus on geo-replication, and will go deep on how to build applications that can take advantage of this key feature. Speaker: David Poulet - Global Black Belt for NoSQL, Microsoft David is a technical subject matter expert in Big Data and NoSQL advising Microsoft’s largest Cosmos DB customers across EMEA.

6:00 PM - 7:00 PM (UTC)

Anti-Money Laundering (AML) is a regulation created to combat financial crime (FinCrime). Using Cosmos DB I have built solutions for my customer that help identify customers with known links to FinCrime, Identify Transaction Anomaly and produce AML risk reporting. Host: Jay Gordon Jay Gordon is a Senior Program Manager with Azure Cosmos DB focused on reaching developer communities. Microsoft, Jay was part of teams at DigtialOcean, BuzzFeed and MongoDB. Jay lives in Brooklyn, NY with his wife and a weird dog. Speaker: Arunansu Pattanayak Arun is a Cloud Solution Architect specializing in Azure Data and AI at Microsoft US Financial Services organization. Before joining Microsoft he worked as a Consultant at many large financial institutions, where he built complex enterprise solutions using Big Data, Machine Learning and AI technologies. He is also a well known speaker at major conferences and user groups.

6:00 PM - 7:00 PM (UTC)

Azure Cosmos DB for PostgreSQL can support relational applications of any size - from the small prototypes to applications at global scale. In this presentation, you will see how to get started with Azure Cosmos DB for PostgreSQL. You will see the considerations around growth, including schema changes. By the end of this session, you should have a good understanding of why Azure Cosmos for PostgreSQL is a good host for your relational data apps at any scale. Host: Jay Gordon Jay Gordon is a Senior Program Manager with Azure Cosmos DB focused on reaching developer communities. Microsoft, Jay was part of teams at DigtialOcean, BuzzFeed and MongoDB. Jay lives in Brooklyn, NY with his wife and a weird dog. Speaker: Sarah Dutkiewicz has been in the technical realm since the late 90s. She has served in many roles – including technical support, manager, desktop support, server administrator, database administrator, developer, instructor, and mentor. Throughout her career, Sarah has found her place in the technical community – as an organizer, speaker, facilitator, author, editor, reviewer, blogger, and advocate. Due to her community involvement, Microsoft has awarded her the Microsoft Most Valuable Professional (MVP) award – 2009-2023 in Visual C# / .NET / Developer Technologies. Sarah loves sharing her passion for tech with the community whenever she can!

5:00 PM - 6:00 PM (UTC)

When running production applications with Azure Cosmos DB we need to check if the performance, security, and availability is configured in the best way. Your configuration should be adapted to your application specific needs. The default configurations when setting up your database may not be right for your application. In this session we’ll look at how and where to look for when best optimizing Azure Cosmos DB for your applications. In this session we’ll present methodology and some tools you can use to optimize your Azure Cosmos DB deployment. Host: Jay Gordon Guest Speaker: Emmanuel Deletang

5:00 PM - 6:00 PM (UTC)

Azure Cosmos DB has numerous use cases, including IoT. One of the challenges with IoT workloads, however, is dealing with the deluge of data that IoT devices generate. Processing large volumes of data in real time and storing it in an efficient manner requires careful planning and execution if you want to make an IoT solution fly. In this session, we'll look at a few ways you can do this with Azure Cosmos DB being central to these patterns. Host: Jay Gordon Guest Speaker: Blaze Stewart

5:00 PM - 6:00 PM (UTC)

In this session, we will go over how Cosmos DB change feed was used as a mechanism to orchestrate a two way SMS communication architecture using Azure Communication Services. We will talk about Cosmos DB change feed's capabilities and how easily they integrate with Azure services. Don't miss this opportunity to learn about one of the most powerful and flexible databases available today! Host: Jay Gordon Guest Speaker: Harpreet Gill

5:00 PM - 6:00 PM (UTC)

Azure Cosmos DB is a fully managed NoSQL database, offering different APIs and scalable across the globe. You can use it as a document database, where you store many different JSON files for example. But what happens when you need to run large analytical queries on top of your Cosmos DB? If the data is partitioned differently than your query access path, you might end scanning the whole thing? In this session, we will walk you through the concept of the analytical store on Cosmos DB, and how this can work together with the Azure Synapse Link feature of Azure Synapse to enable painless analytics on your data. We will show you how you can use Serverless SQL and Spark Pools to query the data. At the end, you should be able to assess if this solution will be a good match for your use cases.

5:00 PM - 6:00 PM (UTC)

There are many applications for the Cosmos DB Property Graph model, from business intelligence analytics to combating fraud. Thinking about the data model as a graph and storing and querying it in that format can be very powerful but at the end of the day, a human has to be in the loop to make decisions based on this data. Often, but not always, this comes down to visualization, but frequently, not enough attention is paid to the user experience when looking at large volumes of graph data. Simply plotting a bunch of nodes and links on the screen is more likely to be confusing than enlightening, especially to someone unfamiliar with the graph model. In this talk, I’ll discuss:What types of applications benefit from a visual front end of the graph • When creating a front end for exploring the graph, what techniques should be avoided • Overwhelming the user with too much data • Trying to many properties of the graph data in the visualization • Labeling everything with too much text

5:00 PM - 6:00 PM (UTC)

In this session we will cover an overview of some of the DevOps practices for Azure Cosmos DB solutions. From provisioning, testing, environment management, CI/CD and automated tasks.

5:00 PM - 6:00 PM (UTC)

Vector search is a method that helps you find similar items based on their content rather than exact matches on properties like keywords, tags, or other metadata, as keyword-based search systems do. In this session, we will discuss about vector search with Azure AI Vision and Azure Cosmos DB for PostgreSQL. We will explore how to use Azure AI Vision embedding models and enable the pgvector extension, an open-source vector similarity search extension for PostgreSQL. We will then go on to show how to build an image vector similarity search app that can take advantage of these technologies.

6:00 PM - 7:00 PM (UTC)

When working with Azure Cosmos DB, I was looking for a way to have reusable scripts for common actions I did with my team's data. I found the Azure Cosmos Python SDK, and was able to build out some basic python scripts that I could use in my day to day tasks. Now when I do things like bug fixes and other maintenance tasks, I can use the SDK to create new scripts, and refer back to them in the future.

6:00 PM - 7:00 PM (UTC)

LlamaIndex is a popular way of building applications that connect your data to a large language model, allowing you to answer questions and reason about your internal data, a technique known as Retrieval-Augmented Generation (RAG). We'll show how to build a simple RAG application using LlamaIndex and Cosmos DB.

6:00 PM - 7:00 PM (UTC)

Are you ready to unlock the power of your Azure Cosmos DB data with new OneLake lakehouse use cases? Fivetran’s 500+ fully managed and fully automated, out-of-the-box connectors (databases, applications, file systems, event systems) include support for both Azure Cosmos DB as a source and Microsoft Fabric OneLake as a destination so that you can build a modern lakehouse architecture that is both powerful and secure. Fivetran helps you unlock the full potential of your data, enabling you to run advanced analytics and AI models across any use case or dataset combination. During this show, we'll chat about (and demonstrate) how Fivetran’s support for Azure Cosmos DB and OneLake in Fabric can help you: Simplify data movement: Easily, quickly, and reliably connect Azure CosmosDB or any data source to OneLake, without the need for complex ETL pipelines. Empower lakehouse architecture: Combine the best of data warehouses and data lakes, giving you the flexibility to store and analyze your data in any way that you need. Automate for enhanced reliability: Automate your data pipelines with Fivetran, so you can be confident that your Azure Cosmos DB data is always up-to-date and accurate in OneLake. Join us for this discussion and live demo to learn how Fivetran, Azure Cosmos DB, and OneLake can help you build a lakehouse architecture that will transform your organization.

5:00 PM - 6:00 PM (UTC)

Azure Cosmos DB supports multiple data models and APIs, making it ideal for AI applications that deal with diverse and complex data. In this session, you’ll learn how to use Azure Cosmos DB with various Azure AI services, such as Azure AI Search, Azure Open AI, and more, to create a variety of intelligent scenarios. You’ll also get practical tips and best practices for designing and optimizing your AI architectures with Azure Cosmos DB.

5:00 PM - 6:00 PM (UTC)

Learn about the new capabilities of Azure Cosmos DB for MongoDB vCore and Semantic Kernel that enable you to use vector search and integrate your AI-based movie recommendation applications. Vector search enables you to efficiently store, index, and query high-dimensional vector data along with operational data that is stored directly in Cosmos DB for MongoDB vCore. Semantic Kernel enables integration with Azure OpenAI to perform retrieval augmented generation (RAG) and bring everything together. In this session, you'll learn about vector search, RAG, and the steps you need to perform to enable it using the semantic kernel, discover how to set up an Azure Cosmos DB for MongoDB vCore, deploy the Azure OpenAI chat and embedding model, learn about how the semantic kernel works, and integrate it in a quart app. Join us in building a Flask application capable of generating responses using vector search and RAG, catering to tech enthusiasts of all expertise levels.