Session
Sandboxed Agents: Building Isolated, Governed and Scalable AI
Agents need to be isolated for what they can and can't access (files/folders, production envs, LLMs, MCP tools, runtimes, etc. - think autonomous and standard Agents) and at the same time, scale up and down based on load, if/how the Agent is being used, and how it's being used.
By default, Agents have access to every file, LLM, command, and authN/Z implementation that you do. At the same time, you're running Agents in a scalable, performant, and reliable way with a proven out orchestration/clustering platform.
Example: You want to run 200+ Agents, but only spread across 6-8 k8s Pods. The Agents still perform as well as expected while keeping the underlying infrastructure costs (both resources and actual financial costs) low.
In this session, you will learn about the OSS project that makes this happen - Agent Substrate, with key topics including:
1. Build on top of k8s primitives (clustering of resources for performant sandboxed Agents).
2. Implement a specialized and efficient a Control/Management Plane that's built for the world of agentic.
3. How Substrate Actors running Agents are 90% more efficient (proven in benchmarks) for cost optimization in comparison to Agents in k8s Pods.
4. Efficient and much smaller footprints for running Agents via Actors.
Michael Levan
Building High-Performing Agentic and Kubernetes Environments | AI Architect & Forward Deployed Engineer | AAIF & CNCF Ambassador | 4x Published Author & International Public Speaker
Saddle Brook, New Jersey, United States
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