Red Hat Summit: Connect 2026 Dallas, Texas

Deploying production applications to different environments on reusable, security-focused  foundations with a clear and simple way to build and manage them is a major challenge for IT. In this lab, we'll explore how using image mode for Red Hat Enterprise Linux (RHEL) to build images can deliver working applications on a more secure and manageable foundation. Creating a production system often requires collaboration and requirements from different teams. We'll build our sample application with a phased approach, detailing the fundamentals of image mode operations in a context you can take with you to your environment. This opinionated method will tackle the needs of the operators, the security team, and the developers in ways that are easy to understand and remix. Along the way, we'll highlight different benefits and approaches that image mode uniquely delivers. Today, you'll create a working application host by:Defining the standard baseline environment.Configuring the security posture and compliance.Delivering a common hardened platform for application deployments.Using a single source image for multiple environments.

Virtualizing workloads on a modern, container-native platform unlocks new levels of operational efficiency, resilience, and flexibility for teams managing traditional infrastructure. In this hands-on lab, you’ll work through the core capabilities of Red Hat OpenShift Virtualization, from day-one VM operations to advanced migration, storage, networking, and application integration. Attendees will learn how to: - Manage virtual machine lifecycle — create, configure, and right-size VMs directly on OpenShift. - Migrate existing VMware vSphere workloads to OpenShift Virtualization using the Migration Toolkit for Virtualization (MTV), with minimal disruption. - Navigate storage changes and manage persistent storage for VMs within the OpenShift ecosystem. - Protect workloads with backup and recovery workflows using OpenShift API for Data Protection (OADP). - Standardize VM deployments with reusable Templates and InstanceTypes to accelerate provisioning and enforce consistency. - Configure advanced networking, including L2 network mappings and User Defined Networks (UDN), to meet enterprise connectivity requirements. - Expose VM-hosted applications through services and routes, bridging the gap between virtualized workloads and modern application delivery. Join us to experience how OpenShift Virtualization delivers a unified, production-ready platform that simplifies VM operations and accelerates the path from legacy infrastructure to a cloud-native future.

Your open source vendors have figured out they gave away too much. So they changed the license. Then the pricing model. Then the terms around what "free" actually means. They're not done. This session is about what that costs you, and what you can do about it. We'll discuss open source MySQL, MongoDB, PostgreSQL, and Redis that run on your infrastructure, with engineering support from the people who maintain the code.

From ""Software is Eating the World"" to the ""Mythos Moment,"" organizations' dependency on software has expanded exponentially. With new AI-powered tools, hackers have more ability than ever to build and exploit vulnerabilities. In this session, you'll learn about Project Lightwell, and how Red Hat is helping companies better manage the Vulnerability Gap.

You've built the playbooks. You've got the automation running. Now everyone's asking about agentic AI — and you're trying to figure out what that actually means for the infrastructure you're responsible for keeping stable and secure. In this session, we'll explore the concept of multimode automation: a practical framework for understanding how task-driven, event-driven, and AI-driven automation can be orchestrated as a trusted execution layer for IT operations teams. We'll dig into how Red Hat Ansible empowers your team to implement a truly “governance-first” approach to automation, and why the guardrails you've already built matter more than ever in the agentic AI era. If you're an automator trying to figure out where AI actually fits without breaking what's already working, this session is for you.

Red Hat Summit 2025 unveiled our enterprise AI vision, including distributed inference with llm-d, an expanded model ecosystem, and Llama Stack and Model Context Protocol (MCP) for agentic AI, culminating in Red Hat AI 3. One year later, the focus shifts to enterprise-scale production and integrated intelligent systems, showcasing customer success in finance, telecommunications, and industrial automation. Join us for a comprehensive update and roadmap, diving deep into: -Distributed inferencing at scale, with llm-d for cost-effective, low-latency inference. -Enterprise Model-as-a-Service (MaaS) for self-service deployment and governance -Production retrieval-augmented generation (RAG) for reliable, scalable, auditable pipelines. -Continual alignment for model customization beyond fine-tuning. -Accuracy with inference time scaling (ITS) to boost model accuracy without retraining. -The evolution of Llama Stack for multi-agent collaboration and advanced tool use. -Our comprehensive approach to security, governance, and trust with security-focused AI/ML lifecycle, guardrails, and sovereign AI. This session highlights what's new and what's next with Red Hat AI, and how it provides an integrated, open foundation for AI applications with real-world results.

Red Hat’s edge solutions transform the complex, fragmented reality of edge computing—characterized by manual maintenance, security risks, and operational silos—into a scalable, consistent, and automated infrastructure. By integrating open-source technologies like Red Hat Enterprise Linux, MicroShift, and Ansible, this platform allows businesses to manage remote devices with the efficiency of centralized data centers, bridging the gap between IT and operational technology. Learn how organizations shift the focus from merely managing infrastructure challenges to leveraging edge data for real-time innovation, such as AI-driven predictive maintenance and autonomous operations, all while reducing costs and avoiding the constraints of vendor lock-in.

Security threats move in seconds, but manual incident response can take hours. In this hands-on workshop, you’ll learn how to transform slow, reactive security tasks into automated, production-safe workflows using Red Hat Ansible Automation Platform and Event-Driven Ansible. Through a series of practical lab exercises, you’ll respond to a live security vulnerability from initial alert to safe remediation. You will build and test automated pipelines across three core phases: Defend: Instantly isolate affected services, contain threats, and revoke compromised credentials using event-driven triggers the moment a vulnerability is detected. Contain: Apply critical patches quickly using policy-gated workflows that run safety checks and gather necessary approvals before changes touch production. Comply: Enforce continuous security guardrails by packaging hardened configurations into scanned, audit-ready deployments that satisfy compliance standards. Whether you manage enterprise infrastructure or oversee security operations, you will leave this session with actionable techniques to slash your Mean Time to Respond (MTTR) while keeping your environment safe and compliant.

Agentic AI apps don’t fail silently; they fail distributedly. This hands-on lab shows how to make multi-agent AI systems observable end-to-end on Red Hat AI. By exploring a multi-agent app integrated with Model Context Protocol (MCP) tools, we demonstrate an AgentOps discipline that delivers visibility from infrastructure to AI model backends. As organizations scale, teams face cascading errors, hidden latency, and complex integration bottlenecks. Attendees will leave with practical patterns for observing, troubleshooting, and evaluating agentic workflows. Attendees will also learn how to:Monitor the stack: Use Red Hat AI’s out-of-the-box observability stack to track key metrics and logs.Trace multi-agent executions: Track requests across multi-agent frameworks (like LangGraph/LangChain) and MCP tools to understand the complete decision-making path using Red Hat AI and MLFlow tracing features.Diagnose and fix distributed failures: Simulate real-world rollout issues, such as artificial delays in MCP servers or failing multi-agent communications, and use tracing to pinpoint the root cause and deploy the fix.Large language model (LLM) evaluations: Go beyond basic observability by combining tracing with LLM evaluations in MLflow, ensuring your agents maintain high-quality outputs alongside system reliability.

The shift from experimental AI to deploying enterprise AI at scale requires a fundamentally new software and hardware architecture. This session explores the expansion of the Red Hat and NVIDIA collaboration, including Red Hat Enterprise Linux for NVIDIA. We will detail how this specialized edition provides Day 0 support for new NVIDIA accelerated computing platforms, providing a hardened foundation for future AI and computationally dense workloads. Next, we will dive into the full-stack integration that defines the Red Hat AI Factory with NVIDIA. This new enterprise AI factory solution combines Red Hat AI Enterprise and NVIDIA AI Enterprise software capabilities, with support for NVIDIA’s latest accelerated computing platforms. You’ll hear how this full-stack AI factory solution transforms the ad-hoc creation, customization, and deployment of AI experiments into a repeatable, scalable, and safe-guarded process for production deployments.

Abstract: Many enterprises are anchored to legacy virtualization, facing vendor lock-in and modernization challenges. How do you seamlessly migrate thousands of virtual machines (VMs) and manage them alongside containers? How do you accelerate your application modernization strategy with so many VM-based workloads? Red Hat OpenShift Virtualization provides the answers.With OpenShift Virtualization as your strategic platform, you can run VMs on dedicated clusters, begin modernizing VM-based applications with cloud-native tools and processes, and eventually simultaneously convert them to cloud-native containers in the same environment.Join us and discover the capabilities OpenShift Virtualization provides to help you migrate and modernize VMs and applications at scale—whether in the cloud, in your datacenter, or at the edge of your network.In this interactive session, you will:Get a comprehensive look at the current features of Red Hat OpenShift Virtualization.Gain insight into key strategic themes and the 2026 roadmap.Learn from live demos showcasing day 2 virtualization operations.Get an opportunity to ask questions and offer feedback about how Red Hat can better adapt to meet your evolving needs.This session is ideal for IT administrators, solution architects, and technical decision makers planning their datacenter modernization and cloud-native journey. 

As AI-driven vulnerability discovery outpaces human remediation, organizations need more than an operating system—they need a closed-loop remediation partner. Red Hat’s “See it, Stage it, Ship it” approach brings together Red Hat Lightspeed, Satellite, and Ansible Automation Platform as a single, supported portfolio on a hardened Red Hat Enterprise Linux foundation. That helps teams offload much of the work of triaging and patching CVEs, so they can keep pace with AI-scale discovery, reduce downtime, and focus on their core business.

For highly regulated sectors—such as financial services, healthcare, defense, and the public sector—technological innovation is fundamentally bound by strict risk parameters. Navigating the modern threat landscape requires balancing stringent compliance directives (like DORA, NIS2, and the EU AI Act) against an explosion of AI-driven vulnerabilities, fragile software supply chains, and public cloud vendor lock-in. This session explores how Red Hat’s comprehensive portfolio addresses these challenges by transforming risk mitigation from a manual security checklist into an automated, architectural reality. We will analyze the core announcements from Red Hat Summit, focusing on the newly introduced Digital Autonomy Framework and its four foundational pillars: Data, Technical, Operational, and Assurance sovereignty. Crucially, the session will break down the groundbreaking Project Lightwell—a massive $5 billion joint initiative between IBM and Red Hat that combines advanced AI with over 20,000 engineers to form an industry-first security clearinghouse for open-source software. Attendees will discover how Red Hat enables enterprises to lower their active risk profile, eliminate configuration drift, and establish airtight guardrails from the upstream open-source supply chain to global cloud environments without sacrificing operational velocity.

What if the developer portal could also be the AI agent control plane? This talk shares how we built a Backstage plugin family that embeds multi-agent orchestration, MCP tool connectivity, RAG-grounded knowledge, and agent lifecycle governance into the developer portal -- using the new backend system and extension points. The live demo walks the full journey: a developer discovers agents in a built-in marketplace, starts a conversation that flows across specialist agents with real-time handoffs, and watches tool calls stream against live infrastructure via MCP. On the platform side, teams create agents through skills composition, a visual workflow builder, or bring-your-own frameworks and govern them from draft to published through a review queue. Attendees will leave with practical patterns for MCP authentication, pluggable AI provider architecture, and agent lifecycle governance -- applicable to any Backstage plugin integrating AI at scale.