Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

While the industry focuses on LLM accuracy, technical decision-makers are facing a more complex challenge: How do we govern the autonomous AI agents that will soon operate across our entire infrastructure? Without a dedicated control plane, autonomous agents introduce significant risks to identity, authorization, and auditability. This session moves past the AI hype to discuss the architectural constraints and security patterns required to run agentic systems in highly regulated, enterprise environments.

A VM in your estate today sits on a VLAN, and that VLAN does more work than its configuration suggests. The VM's address comes from that subnet. Its default gateway is the SVI on that VLAN. The firewall rules that permit its traffic reference the subnet, not the machine. And if your segmentation zones are drawn on VLAN boundaries, as they are in most enterprises, then the VLAN is the thing putting that VM inside its zone.

While the industry focuses on LLM accuracy, technical decision-makers are facing a more complex challenge: How do we govern the autonomous AI agents that will soon operate across our entire infrastructure? Without a dedicated control plane, autonomous agents introduce significant risks to identity, authorization, and auditability. This session moves past the AI hype to discuss the architectural constraints and security patterns required to run agentic systems in highly regulated, enterprise environments.

If you have VMs running in Kubernetes you need a way to migrate them between nodes without dropping connections, breaking network configurations or accidentally bypassing security policies. With networking in bridge mode, by far the most popular configuration, VMs need persistent IP addresses rather than the ephemeral ones Kubernetes assigns to pods by default. This workshop will guide you through how this is achieved. It will show you how to configure the environment, run the migration, and read the system state at each step to understand what is actually happening under the hood.

While the industry focuses on LLM accuracy, technical decision-makers are facing a more complex challenge: How do we govern the autonomous AI agents that will soon operate across our entire infrastructure? Without a dedicated control plane, autonomous agents introduce significant risks to identity, authorization, and auditability. This session moves past the AI hype to discuss the architectural constraints and security patterns required to run agentic systems in highly regulated, enterprise environments.