Browse Azure Videos (168)

Paula Santamaría and Julia Schröder Langhaeuser present a production Retrieval-Augmented Generation (RAG) architecture built on Azure Database for PostgreSQL, explaining why Postgres can be a solid foundation for RAG at scale and what it takes to move from prototype to production with performance tuning and monitoring.

Dingding Lu explains why Microsoft built Azure HorizonDB for PostgreSQL and how its shared-storage design targets predictable performance, fast failover, and scalable reads for modern Postgres workloads running on Azure.

Abe Omorogbe explains how PostgreSQL is evolving into a backbone for production AI agent workflows, focusing on reliable and safe data retrieval. He covers MCP-based agent patterns, common failure modes when agents generate SQL, and emerging approaches like context correction and blended retrieval across relational, vector, and graph techniques.

Varun Dhawan explains why PostgreSQL is increasingly used as an “everything database” and how its extensibility lets teams consolidate workloads like OLTP, analytics, and vector search. He also connects these capabilities to Azure Database for PostgreSQL and scaling patterns such as Citus.

Amar Digamber Patil explains what viewers will learn from the Budget Bytes series, focusing on building AI-powered applications on Azure SQL and how to evolve from simple setups to more scalable architectures while keeping costs within a $25 budget.

Amar Digamber Patil introduces the Budget Bytes series and explains what viewers will learn about building AI-powered apps with Azure SQL, covering approaches that start simple and scale up while staying within a $25 budget.

Microsoft Developer previews Livestream 3 of POSETTE 2026 with short introductions to 11 PostgreSQL talks, including WAL, logical replication, testing and coverage, consistency in clusters, performance tuning, and a session on production RAG at scale using Azure Database for PostgreSQL.

John Savill walks through recent identity and authentication changes for Azure Files, focusing on Microsoft Entra ID–integrated authentication scenarios including managed identity access, cloud-only identity access, and macOS Platform SSO (PSSO) access.

Adithya Kumaranchath shares field-tested strategies for migrating multi-terabyte Oracle databases to Azure Database for PostgreSQL Flexible Server with minimal downtime, covering planning, tuning, and common pitfalls that show up at very large scale.

Murat Tuncer walks through how PostgreSQL authentication evolved from early trust-based local setups to modern certificate and token-based approaches, explaining why each method exists, what trade-offs it made, and the common mistakes teams still run into when choosing auth for production deployments.

Microsoft Developer shares a short trailer previewing Livestream 2 of POSETTE 2026, highlighting 11 PostgreSQL talks including a session on migrating very large databases from Oracle to Azure Database for PostgreSQL, plus upcoming Postgres features, performance internals, authentication changes, and operational patterns like queueing and connection pooling.

Affan Dar and Charles Feddersen share how Microsoft is investing in PostgreSQL upstream and how that work feeds into Azure Database for PostgreSQL, including scaling features, HorizonDB, developer tooling, and a look at building AI pipelines inside Postgres.

Matt McFarland explains how PostgreSQL developer tooling is being extended from the VS Code PostgreSQL extension into AI-driven environments like Cursor and the GitHub Copilot CLI, using an MCP server as a shared interface for connections, queries, schema inspection, and performance analysis.

Andrew Ruffin explains how to choose Azure infrastructure for PostgreSQL workloads, focusing on VM family selection, benchmarking results, and cost/performance trade-offs. The talk compares IaaS vs PaaS deployment choices and highlights hardware features and security options that can improve Postgres performance while controlling cloud spend.

dotnet explains patterns for modernizing data and migrating line-of-business applications incrementally, focusing on moving the database first and evolving the app through stable API layers and modern data access approaches.

dotnet introduces the Modernize CLI and how it’s used to modernize and migrate .NET applications to Azure, focusing on practical workflow steps for moving existing apps toward cloud-ready deployment targets.

Griffin Norris demonstrates how AI agents and Microsoft Copilot can speed up robotics development by generating robot control code from natural language, connecting robots to AI models via MCP servers, and adding vision-based scene understanding for interactive, feedback-driven control.

Microsoft Developer shares a 4-minute trailer previewing Livestream 1 of POSETTE 2026, highlighting 11 PostgreSQL-focused talks that include Microsoft’s Postgres roadmap, performance tuning, AI tooling, Azure infrastructure choices, and a comparison of PostgreSQL vs. SQL Server security models.

Ayan Gupta, Sandra Ahlgrimm, and Yoshio Terada show how GitHub Copilot can be used to modernize a legacy Java application through a structured workflow, using a real migration from Java 5/Struts to Java 21/Spring Boot and finishing with deployment to Azure.

John Savill gives an overview of Azure HorizonDB, explaining how it relates to PostgreSQL and walking through its cloud-native architecture, core components, and key capabilities like standby replicas and other platform features, plus a high-level look at pricing and where to find the official docs.

John Savill gives a very quick introduction to HorizonDB, framing it in the context of Azure and PostgreSQL as a cloud database option.

John Savill rounds up a week of Azure platform changes and retirements, spanning compute/storage updates, database and identity improvements, monitoring changes, and several developer-facing AI items including GitHub Copilot Agent Mode in SSMS and Azure AI Foundry agent licensing and model availability.

Bruno Capuano and Tommaso Stocchi walk through building distributed multi-agent applications using .NET Aspire and Microsoft Agent Framework (MAF), focusing on how multiple agents coordinate across services and exchange context. The session connects these patterns to Foundry-oriented scenarios and demonstrates them with a ski resort example.

John Savill gives a fast-paced rundown of key announcements from Microsoft Build 2026, highlighting notable platform updates across Azure, AI, and identity/security topics such as Entra and passkeys.

Dan Wahlin demonstrates an “agentic journey” workflow that takes an app idea through planning, coding, infrastructure creation, and deployment to Azure, using GitHub Copilot CLI and Azure skills to handle tasks like Bicep templates, health probes, and database wiring for an app backed by Azure SQL and Microsoft Foundry.

Henk Boelman live-codes a real-time, voice-first multimodal agent in Azure AI Foundry using the Voice Live API, showing how to combine speech input, model reasoning, and speech output, then connect the agent to external tools via MCP so it can take real actions.

John Savill runs through a Build-special weekly Azure update, covering a wide set of platform announcements across compute, containers, integration, monitoring, databases, Fabric/Databricks, and Azure AI Foundry—plus security-focused items like confidential computing and Purview agent integrations.

Charles Feddersen and Abe Omorogbe explain how AI apps and agents change database design, focusing on reasoning over operational data instead of only transactions. They demo new capabilities across Azure SQL Database, Azure Cosmos DB, and Azure HorizonDB (cloud-native PostgreSQL) to simplify architectures and reduce latency.

Seth Juarez explains how Azure AI Foundry Toolboxes let teams build, discover, and govern tools across multiple AI agents, reducing duplicated integration work around authentication, credentials, and endpoint wiring.

Milos Colic shares how Xoople scaled Python-based AI workloads on Azure using Ray via Anyscale, covering the distributed-systems challenges behind data ingestion, training, and inference, and why the team prioritized delivering outcomes over operating clusters.

Nikisha Reyes-Grange introduces Azure HorizonDB and Rayfin, focusing on how these Azure Data and Microsoft Fabric innovations aim to modernize PostgreSQL operations and simplify building and running data applications, including SQL-level AI functions and hybrid search concepts.

Jeff Hollan and Lee Stott explain how hosted agents in Microsoft Foundry help teams move from local agent prototypes to production-grade AI systems, with a focus on identity, isolation, evaluation, and lifecycle management so developers can deploy secure, scalable agents with clearer operational boundaries.

Vivek Chauhan shares a quick on-the-show-floor update from Microsoft Build 2026 on Fireworks AI, including the scale they run at and how their partnership with Microsoft connects to Azure AI Foundry for governance, security, and reliability.

Adrian Macias discusses how open-source AI development is shifting across local AI PCs and Azure, covering agentic AI, AI-assisted coding, and the practical need for flexible deployment options as teams experiment and scale AI workloads.

Nish Anil, Hazem El-Hammamy, and Jeff Fritz present a Microsoft Build 2026 session on using GitHub Copilot’s modernization capabilities and agentic AI to analyze large legacy codebases, map dependencies, plan upgrades, and refactor safely with governance controls, including examples spanning mainframe and .NET modernization.

Mark Russinovich and Ion Stoica discuss how AI platforms need to evolve for agentic, multimodal, globally distributed workloads, covering infrastructure fundamentals, training and real-time serving architectures, and why open source, security, and governance are becoming core platform requirements.

Sameer Nori, Pranay Bakre, and Govardhani Babu show how to run and scale LLM inference for agentic, cloud-native apps on Azure using Arm-based Azure Cobalt VMs, including an AKS demo and practical guidance on performance, scaling, and cost trade-offs.

Scott Guthrie shares a fast-paced builder’s view of what matters for developers in the current AI wave, covering how Microsoft is scaling Azure infrastructure and what “AI-ready” systems look like from silicon to software.

Mike Richter shows how Elastic Agent Builder (Elasticsearch 9.4) can help AI agents manage long-running context by using a conversation context store, selective compaction, and dynamically loaded skills, with an emphasis on deploying these patterns in the Microsoft ecosystem on Azure and with Azure AI Foundry models.

Edo Segal demonstrates how to build multimodal AI agents with persistent memory, including a live walkthrough of provisioning Napster as an Azure resource and integrating the agent securely with Azure AI Foundry.