As AI workloads grow, infrastructure must keep pace. This session covers Azure’s silicon-to-systems optimization, hardware-software codesign, and datacenter advances in cooling, power, network, and security. Learn about Azure’s latest AI infrastructure powered by NVIDIA Grace Blackwell Superchips and Quantum-2 InfiniBand, including ND GB200/GB300 VMs with exascale performance and 860K+ tokens/sec on LLAMA 70B. We’ll also cover NC H100 and NC RTX Blackwell VMs for enterprise inferencing.

With models from OpenAI, Anthropic, Cohere, Black Forest Labs, Mistral AI, Meta, xAI and more, Microsoft Foundry brings the world’s most advanced AI models together in one secure, unified platform. Learn how to select, evaluate, and intelligently route models to achieve the right balance of cost, latency, and accuracy—all while maintaining enterprise-grade security, responsible AI practices, and built-in governance across every workload.

As organizations adopt AI to boost productivity and creativity, concerns grow about data security and possible leaks through generative AI tools like Copilot, ChatGPT, and Gemini. Microsoft’s Data Security Posture Management (DSPM) for AI helps organizations monitor AI activities, enforce data protection policies, and meet regulatory standards, allowing safe, productive AI use without compromising sensitive information.

Learn to leverage agent-framework, the new unified platform from Semantic Kernel and AutoGen engineering teams, to build A2A compatible agents similar to magnetic-one. Use SWE Agents (GitHub Copilot coding agent and Codex with Azure OpenAI models) to accelerate development. Implement MCP tools for secure enterprise agentic workflows. Experience hands-on building, deploying, and orchestrating multi-agent systems with pre-release capabilities. Note: Contains embargoed content.

Please RSVP and arrive at least 5 minutes before the start time, at which point remaining spaces are open to standby attendees.

AI has changed how developers find answers - your docs are now context for both humans and LLMs.

Learn how to make your documentation AI-native with Mintlify.

Join Rackspace as we explore the "Power of Three", Microsoft Co-pilot in Power Platform, Microsoft 365, and Azure OpenAI. Through real-world use cases, discover the potential of agent-based solutions, using conversational AI assistants to revolutionize knowledge management, customer service, and business process automation that can integrate, retrieve, and act on data securely from diverse enterprise systems. See Rackspace Intelligent Technology Assistant (RITA) in action.

In the age of AI, SAP supercharges it’s portfolio with natively embedded AI features, AI agents, access to 40+ LLMs, and tools for developers to increase productivity. Developers find GitHub Copilot in VS Code invaluable in assisting with code writing in popular languages. With SAP's domain-specific Advanced Business Application Programming (ABAP) language, developers can work in its ecosystem through writing code in ABAP. SAP is now making a fine-tuned ABAP AI model available to help developers

Connecting LLMs to your secure, operational database involves complexity, security risks, and hallucinations. This session shows how to build context-aware AI agents directly on your existing data, going from live database to production-ready, secure AI agent in hours. You'll see how to ship personalized experiences that will define the next generation of software. RavenDB's CEO will demonstrate this approach.

DevEx 2.0 means giving developers guardrails that accelerate delivery instead of slowing it. This session shows how continuous security integrates with Azure and GitHub pipelines. You’ll see IDE coaching and SAST at commit. With Microsoft Copilot and Azure OpenAI using GPT-5, developers can cut through false positives and receive actionable fixes directly in the code. Builds include SBOM generation, container scans, and dependency checks. Staging environments add DAST and API testing.

AI is reshaping NetOps from scripted automation to intelligent, data driven workflows. We will show uses: incident triage, knowledge retrieval, traffic analysis, prediction, and contrast legacy monitoring with ML, NLP, and LLMs. See how RAG, text to SQL, and agent workflows enable real time insights across hybrid data. We will outline data pipelines and MLOps, address accuracy, reliability, cost, compliance, and weigh build vs buy. We will cover API integration and human in the loop guardrails.

This demo showcases Finout’s ability to manage and optimize cloud spend across Azure and services like Kubernetes, Datadog, and OpenAI. It highlights Finout’s unified “MegaBill” view for exploring Azure resources, subscriptions, and tags. The session introduces Virtual Tags for dynamic, rules-based cost allocation and covers shared cost distribution, dashboards, anomaly detection, and alerting—empowering teams to improve Azure cost efficiency.

Learn to leverage agent-framework, the new unified platform from Semantic Kernel and AutoGen engineering teams, to build A2A compatible agents similar to magnetic-one. Use SWE Agents (GitHub Copilot coding agent and Codex with Azure OpenAI models) to accelerate development. Implement MCP tools for secure enterprise agentic workflows. Experience hands-on building, deploying, and orchestrating multi-agent systems with pre-release capabilities. Note: Contains embargoed content.

With Eon on Azure, backups don’t just sit idle—they become a first-class data source. Eon transforms cloud backups into Iceberg tables in Blob Storage, instantly queryable through Microsoft Fabric and OneLake. Learn how backup data flows into Fabric engines like SQL, Spark, and KQL, and how it fuels AI innovation with Azure OpenAI. See how organizations can collaborate more effectively by unifying protection, analytics, and AI on Eon’s data lake.

Whether you're building a chat application, a RAG system, or other AI tools, monitoring remains crucial. We'll show you how Datadog's comprehensive Azure monitoring can help you:

• Get started with PostgresSQL on Azure • Track PostgreSQL performance metrics that matter for GenAI workloads • Create dashboards and alerts that provide meaningful insights