Path to production for agents: a Microsoft Azure AI Tech Accelerator
Move AI agents from experimentation to production with trusted architecture, governance, and operations. Many organizations have made progress with AI prototypes, but struggle to turn early success into systems that are secure, reliable, and ready for real-world use. If you want to bridge that gap with practical, engineering-focused guidance across the full AI lifecycle—from foundational governance and architecture to deployment, security, and ongoing operation—don't miss this event. Learn how to establish trust in AI systems, design architectures that scale with control, and operate agentic solutions with confidence over time. Explore proven patterns for building production-ready foundations, managing risk and cost, and maintaining performance in dynamic, non-deterministic environments. Walk away with a clear path forward, offering actionable strategies and playbooks you can use to deliver secure, compliant, and high-performing AI solutions in your organization. I'm in. How do I participate? Sign in to the Tech Community. Click on a session topic below then Add to Calendar to and Attend on that page to receive event reminders. Day 1 - July 27, 2026 TIME TOPIC 8:00 AM PDT 3:00 PM UTC Build an AI Center of Excellence for agent governance 9:00 AM PDT 4:00 PM UTC Design Azure AI Landing Zones for production at scale 10:00 AM PDT 5:00 PM UTC A Microsoft blueprint for scalable agentic AI systems Day 2 - July 28, 2026 TIME TOPIC 8:00 AM PDT 3:00 PM UTC Monitor and govern AI agents in production with AgentOps 9:00 AM PDT 4:00 PM UTC What it looks like: Trusted, compliant AI systems at scale 10:00 AM PDT 5:00 PM UTC How to keep agentic workloads orchestrated, fast, and affordableHow to keep agentic workloads orchestrated, fast, and affordable
Getting AI to production is only half the battle. Once agentic workloads are live, organizations face compounding challenges: token costs that grow non-linearly, latency that degrades user trust, Retrieval-Augmented Generation (RAG) pipelines that return noise instead of signal, and orchestration overhead that multiplies with every agent added to the mesh. This is where the real engineering begins. Wrap up your Path to production Tech Accelerator experience with a practical optimization playbook for agentic AI, from model selection and inference routing to prompt compression, RAG tuning, and caching strategies. Learn how to manage orchestration complexity across multi-agent systems while improving signal quality and response times. Explore FinOps practices for AI, including capacity planning, batch processing, and intelligent model routing. Walk away with actionable techniques to reduce inference costs, cut latency, and scale reliably across regions. How do I participate? Select Add to Calendar to save the date, then click the Attend button to save your spot, receive event reminders, and participate in the Q&A. Not able to attend live? This session will be recorded and available on demand shortly after airing. Don't see Attend or Add to Calendar? Sign in to the Tech Community to join the conversation. This session is part of Path to production for agents: a Microsoft Azure AI Tech Accelerator. View the full agenda for more actionable strategies to help you deliver secure, compliant, and high-performing AI solutions across your organization.What it looks like: Trusted, compliant AI systems at scale
As AI systems move into production, the risk landscape expands beyond traditional app security. Examine emerging threats like prompt injection, data leakage, and autonomous tool misuse—and hear ways to mitigate threats using a defense-in-depth strategy. Find out how to apply layered controls across identity, data protection, orchestration, and runtime environments to keep AI systems secure and controllable. AI security and observability are essential for building trusted, compliant AI systems at scale. That's why we'll also cover how traceability, safety monitoring, and auditability help you maintain trust, prove compliance, and operate with confidence in real-world conditions. How do I participate? Select Add to Calendar to save the date, then click the Attend button to save your spot, receive event reminders, and participate in the Q&A. Not able to attend live? This session will be recorded and available on demand shortly after airing. Don't see Attend or Add to Calendar? Sign in to the Tech Community to join the conversation. This session is part of Path to production for agents: a Microsoft Azure AI Tech Accelerator. View the full agenda for more actionable strategies to help you deliver secure, compliant, and high-performing AI solutions across your organization.Monitor and govern AI agents in production with AgentOps
AgentOps brings discipline and reliability to deploying, monitoring, and scaling agentic AI in production. Getting an AI agent to work once is easy. Keeping it reliable over time is not. Dive into the full lifecycle of running agentic AI in production, from evaluation and CI/CD quality gates to observability, continuous monitoring, and incident response. Learn how to apply DevOps practices to AI’s unique challenges, including non-deterministic behavior, prompt regression, model drift, and tool-calling risks. If you are looking for a practical AgentOps operating model that can increase release confidence, catch issues earlier, and connect agent performance insights back into Microsoft Foundry and Azure Monitor, this is the session for you. How do I participate? Select Add to Calendar to save the date, then click the Attend button to save your spot, receive event reminders, and participate in the Q&A. Not able to attend live? This session will be recorded and available on demand shortly after airing. Don't see Attend or Add to Calendar? Sign in to the Tech Community to join the conversation. This session is part of Path to production for agents: a Microsoft Azure AI Tech Accelerator. View the full agenda for more actionable strategies to help you deliver secure, compliant, and high-performing AI solutions across your organization.A Microsoft blueprint for scalable agentic AI systems
Explore a governance-first, multi-agent architecture that embeds consistent controls and quality checks across every layer. Many AI pilots don't fail because of technology; they fail because the architecture isn't designed for trust. Agentic AI architecture enables trusted, scalable AI systems with built-in governance and control from user interactions and agent orchestration to integrations, data, and models. See how aligning these layers under a unified security and governance framework creates a resilient, enterprise-wide AI fabric. You'll leave with a clear blueprint for building interoperable, trustworthy AI systems that are designed to scale without compromising control. How do I participate? Select Add to Calendar to save the date, then click the Attend button to save your spot, receive event reminders, and participate in the Q&A. Not able to attend live? This session will be recorded and available on demand shortly after airing. Don't see Attend or Add to Calendar? Sign in to the Tech Community to join the conversation. This session is part of Path to production for agents: a Microsoft Azure AI Tech Accelerator. View the full agenda for more actionable strategies to help you deliver secure, compliant, and high-performing AI solutions across your organization.Build an AI Center of Excellence for agent governance
AI governance and Center of Excellence (CoE) strategies are key to scaling trusted AI. Too many AI initiatives stall in the proof of concept graveyard—not because of lack of innovation, but because trust, consistency, and accountability are missing. Learn how to establish an AI Center of Excellence and governance framework that acts as a consistent "quality gate" across every layer of your AI applications. See how this approach helps you deliver a single, organization-wide view of secure, responsible, and trustworthy AI so you can confidently move from experimentation to production and scale with control. How do I participate? Select Add to Calendar to save the date, then click the Attend button to save your spot, receive event reminders, and participate in the Q&A. Not able to attend live? This session will be recorded and available on demand shortly after airing. Don't see Attend or Add to Calendar? Sign in to the Tech Community to join the conversation. This session is part of Path to production for agents: a Microsoft Azure AI Tech Accelerator. View the full agenda for more actionable strategies to help you deliver secure, compliant, and high-performing AI solutions across your organization.Design Azure AI Landing Zones for production at scale
If you’re moving beyond AI experiments, you need more than great models; you need a foundation you can trust. Azure AI Landing Zones enable secure, scalable AI deployment with proven architectures and governance. Learn how to use Landing Zones as your production-ready blueprint for deploying AI applications and agents with built-in guardrails for networking, identity, security, and cost control. Get insights to help you apply the Cloud Adoption Framework and the Azure Well-Architected Framework to design platforms that support innovation without sacrificing compliance. Walk away knowing how to accelerate time-to-production using validated architectures, infrastructure as code (IaC), and seamless integration with your enterprise environment. How do I participate? Select Add to Calendar to save the date, then click the Attend button to save your spot, receive event reminders, and participate in the Q&A. Not able to attend live? This session will be recorded and available on demand shortly after airing. Don't see Attend or Add to Calendar? Sign in to the Tech Community to join the conversation. This session is part of Path to production for agents: a Microsoft Azure AI Tech Accelerator. View the full agenda for more actionable strategies to help you deliver secure, compliant, and high-performing AI solutions across your organization.Proactively design, deploy & monitor resilient Azure workloads
Do you want to know how to get resilient and stay resilient? Explore the architectural features needed to uphold stringent uptime requirements for critical deployments. Learn how to design resiliency into workloads and environments by implementing Azure landing zones and infrastructure-as-code modules. We will demo native bicep and Azure Verified Modules while explaining the scenarios in which you need those. We'll also show how to use the Azure Proactive Resiliency Library, Azure Advisor and Azure Monitor baseline alerts to minimize outage impacts and increase productivity. This session is part of Tech Accelerator: Mastering Azure and AI adoption. View the full agenda for more great sessions and insights.Microsoft Data and Analytics Forum
Join the Microsoft Data and Analytics Forum on October 30, 2024, at 8:00 AM Pacific Time to ensure your data is organized, secure, and ready for AI innovation. This one-day, digital event will give attendees the insight they need to unify data and analytics on an open and governed foundation and streamline data transformation, business intelligence, and generative AI using Microsoft solutions. By joining the Microsoft Data and Analytics Forum, you’ll: Hear real-world success stories and industry best practices from other organizations using Microsoft analytics tools to drive business growth and efficiency. Future-proof your skills and stay ahead of the curve with future trends and developments in data analytics and cloud computing. Gain insight to the latest advancements and innovations across the Microsoft Intelligent Data Platform. Learn about product updates, best practices, and cost-saving programs straight from Microsoft leaders, experts, and partners. See the products in action through breakout sessions and live demos. This helps you understand how to apply these tools to your own business scenarios. Register now to make sure you’re a part of the Microsoft Data and Analytics Forum. Microsoft Data and Analytics Forum Wednesday, October 30, 2024 8:00 AM-10:00 AM Pacific Time (UTC-7)Secure and Govern Azure AI Services
AI and the need to secure organizational data Data overexposure Data used by AI could be sensitive, including PII and PHI and could violate patient's privacy rights Loss of customer trust Data loss Data produced by AI may be vulnerable to unauthorized access or disclosure by malicious actors Diminished competitive edge Data compliance Data used and produced by AI may not comply with relevant regulations and AI ethics principles Heavy penalties Fortify data security with an integrated approach Discover and auto-classify data and prevent it from unauthorized use across apps, services, and devices Understand the user intent and context around sensitive data to identify the most critical risks Enable Adaptive Protection to assign appropriate DLP policies to high-risk users Enable Adaptive Protection with Microsoft Purview Optimize data protection automatically Context-aware detection Identify the most critical risks with ML-driven analysis of both content and user activities Dynamic controls Enforce effective controls on high-risk users while others maintain productivity Automated mitigation Minimize the impact of potential data security incidents and reduce admin overhead Sensitivity labels span your entire data estate They are a representation of your information taxonomy They describe the priority assigned to your categories of sensitive information.
