Red Hat Summit: Connect 2025 Toronto, ON

Get started with RHEL 10 today! After a short briefing on RHEL 10 updates, you will get hands-on with several of the core new RHEL 10 features like: building and managing image mode built images; working with the command-line assistant, an on-system AI driven assistant to help you manage your systems; and implementing security standards with RHEL system roles, powered by Ansible. Of course, with RHEL 10 machines at your disposal, you can also explore the latest RHEL distribution with the topics interested to you as well!

Organizations are increasingly turning to AI for transformative business insights and task automation. This session offers a practical introduction to LLM-as-a-Service (LLMaaS), showing you how to build and manage custom Large Language Models (LLMs) to meet specific enterprise needs. These LLMs can be served for business insights as well as linked to other AI agents to perceive the world around them and complete tasks. We'll cover deploying LLMs securely within your private cloud, ensuring data security, scalability, and compliance. You'll get a clear overview of integrated services, access controls, and usage metrics for chargeback. We'll also explore practical, high-impact use cases like AI-powered code assistants for developers and agentic AI applications, demonstrating the immediate business value LLMaaS can deliver.

Join Red Hat for our Mission-Critical Automation Workshop, a dynamic hands-on experience designed to introduce participants to Ansible Automation Platform and to immerse you in the journey of a new automator joining a team, progressing from using automation for information gathering to maturing their automation journey and building responsive automation that prevents and mitigates outages, minimizes downtime, and ensures mission-critical workloads remain operational.

In hybrid and multicloud environments, secure management of sensitive data like secrets, credentials, and certificates is critical to maintaining robust security across Kubernetes clusters. This session explores Kubernetes secrets and how integrating external secret managers such as HashiCorp Vault with Red Hat OpenShift enhances security by providing centralized secret management across hybrid and multicloud Kubernetes infrastructure. Attendees will learn about: Kubernetes secrets and how to secure them; accessing credentials with secret store CSI driver and external secrets; automating certificate management with cert-manager; encrypting etcd data both at rest and in-transit; and integrating secret management in CI/CD and GitOps workflows. This session will include practical insights into streamlining access to sensitive data, improving security posture, and managing secrets effectively across Red Hat OpenShift and Kubernetes clusters and is ideal for security and platform engineers looking to enhance security in Red Hat OpenShift deployments.

AI success isn’t just about choosing the right model or deploying the latest technology. It’s about creating a clear, actionable path from bold ideas to measurable outcomes. In this hands-on interactive session, we’ll walk through a practical framework to take AI concepts from ideation to implementation, aligning your technical approach with business priorities every step of the way. Whether you're at the start of your AI journey or looking to accelerate progress, this session will provide you with the necessary tools to effectively bridge the gap between AI’s potential and its real-world value.

Large Language Models (LLMs) offer unprecedented innovation opportunities, yet recent high-profile incidents demonstrate the critical risks of unguarded AI. From financial penalties to severe brand damage, LLMs can "go rogue" due to their non-deterministic nature, rendering traditional software assessment methods inadequate for safeguarding your business. This session will expose these vulnerabilities and unveil the essential blueprint for trusted AI: strategic LLM evaluation and the indispensable role of proactive AI guardrails. Through compelling examples and a powerful live demonstration, we will illustrate how these critical layers not only prevent disastrous missteps but also drive significant business value. Discover how Red Hat OpenShift AI, featuring Language Model Evaluation as a Service (LM-Eval-aaS) and innovative AI Guardrails, empowers organizations across all sectors to confidently deploy and govern AI. Join us to learn how Red Hat's approach ensures your AI initiatives become trusted, responsible, and secure assets.

This session will delve into a novel approach that empowers customers to securely and efficiently customize open-source AI models using their private data, all while maximizing the utilization of their existing GPU infrastructure. We will explore how a service-oriented architecture can facilitate on-premise or secure cloud-based fine-tuning, ensuring data privacy and sovereignty. Furthermore, we will highlight the crucial role of model quantization in dramatically reducing model size and inference costs, making these powerful custom models practical for deployment in resource-constrained environments.

Have you wanted to take advantage of Red Hat Insights, but faced regulations that restrict data processing in Red Hat Hybrid Cloud Console? Red Hat Insights advisor is now available on-premise as an installable component of Red Hat Satellite.

Designed for developers and security engineers, this lab provides hands-on experience with the Red Hat Advanced Developer Suite integrated with Jenkins–demonstrating how Trusted Application Pipeline elevates Jenkins CI/CD workflows with advanced security. Participants will use tools like Red Hat Trusted Artifact Signer, Red Hat Trusted Profile Analyzer, SBOMs, SLSA compliance, and sigstore for image signing to transition from non-secure to security-focused pipelines.

In this hands-on lab, you’ll learn how to use Red Hat OpenShift Virtualization and Red Hat Ansible Automation Platform for essential administration and optimization practices. You’ll experience OpenShift Virtualization’s capabilities beyond initial deployment and how it supports efficient and reliable platform and VM management. After working through real-world scenarios, you’ll be ready to use OpenShift Virtualization not only to host VMs but also to operate and automate in a way that aligns with your organization’s evolving needs.

Agentic AI promises to revolutionize enterprise operations by creating autonomous systems that perceive, decide, and act to achieve goals. These intelligent agents automate complex, multi-step tasks, driving efficiency and innovation. However, enterprises often struggle with complex workflow orchestration, ensuring reliability, and efficiently scaling deployments. This session will explore how Red Hat AI provides a robust, open hybrid platform to overcome these challenges and accelerate Agentic AI innovation. We'll demonstrate how its unified API experience and out-of-the-box agent frameworks streamline complex workflow assembly and facilitate seamless integration through support for Model Communication Protocol (MCP). Discover how Red Hat AI ensures governed, trustworthy agent deployment with integrated monitoring, and delivers scalable, cost-optimized infrastructure across hybrid cloud environments, empowering organizations to capture the full potential of Agentic AI.

As organizations unify virtualized and containerized workloads, migrating virtual machines (VMs) with Red Hat OpenShift Virtualization is transformative. This session provides the tools and insights to understand VM migration, allowing you to integrate VMs within Kubernetes clusters, unlocking flexibility and efficiency. We’ll begin with prerequisites for preparing VMs, covering setup, connectivity, and compatibility tips for a smooth experience. Next, we will explore the migration toolkit for virtualization (MTV), a Red Hat tool used to migrate VMs to Red Hat OpenShift at scale. We will discuss how you can move your workloads once they are on the platform. This session explores cold, warm, and live migrations, with practical use cases. You’ll also learn hands-on techniques for managing live migrations in diverse environments, ensuring smooth operations across clusters with varying hardware. Key takeaways: steps to prepare VMs for OpenShift Virtualization; how MTV simplifies VM migration; what you need to know about cold, warm, and live migration scenarios along with best use cases; techniques for live migrations in hybrid clusters; practical solutions to networking and storage challenges; and scaling migration and Day 2 operations with Red Hat Ansible Automation Platform.

OpenShift Container Platform (OCP) Hosted Control Planes (HCP) are designed to simplify the management of complex hybrid clusters across diverse infrastructures. This innovative solution operates on the principle of a centralized management cluster that hosts multiple OCP control planes. These hosted control planes then extend their reach to manage compute nodes deployed across various environments, including on-premises data centers, public cloud providers (AWS, Azure, GCP), and edge locations. This session will explore the various use cases for OCP Hosted Control Planes, focusing on their application in managing hybrid clusters. We will delve into the underlying architectural components, design principles, and employed technologies. Furthermore, the session will detail different deployment strategies to guide organizations in effectively implementing OCP Hosted Control Planes to meet their specific hybrid cloud requirements.

Financial institutions need AI that is both high-performing and secure. Relying on external AI services for tasks like inference is risky, as it exposes sensitive data and can lead to broken systems if models are unexpectedly changed or removed. The solution is for these organizations to use self-managed, open-source AI engines, which give them full control over their data and operations.Following the recent Red Hat and Meta collaboration, we'll explore how this partnership accelerates open-source AI innovation. The session will focus on vLLM, showing how financial institutions can use it to self-manage models for maximum throughput and lowest latency, all while ensuring data privacy and protecting against model deprecation. We'll also cover how these capabilities form the basis for creating agentic AI architectures—autonomous systems for tasks like trading and compliance. The talk will also detail how to leverage Meta's Llama Stack and Red Hat's OpenShift AI to build intelligent applications, covering core patterns like Retrieval-Augmented Generation (RAG) and ReAct. By bringing together self-controlled AI operations, top-tier performance, and agent management, financial firms can confidently adopt AI. This approach protects sensitive data and moves them from simple inference to intelligent, autonomous decision-making. Attendees will get a roadmap for using open-source AI to gain a competitive edge.