OSS + ELC EU 2026

AI agents are fast becoming how modern software gets built. But taking one from prototype to safe, production-grade operation is still genuinely challenging, and how they behave at scale remains largely uncharted. Agents are stochastic, so testing becomes continuous evaluation. They run code nobody wrote, so a shared kernel stops being a boundary you can trust. They decide their own network calls at runtime, so egress is no longer predictable. And they still need what any service needs: source control, CI/CD, observability, memory, and tool access.

This session walks the full lifecycle of running agents on Kubernetes, open source the whole way. The "outer loop" (build, deploy, trace, evaluate) runs on tools like GitLab, Argo, Langfuse, Milvus, and MCP gateways. The "inner loop" (isolated execution) runs on the kubernetes-sigs Agent Sandbox CRD, gVisor, and FQDN-aware egress via Cilium. We'll show what maps cleanly from the platform you run, what changes for agents, and the production gotchas no quickstart warns you about, drawn from building these in the open with teams running from a handful of developer sandboxes to the hundreds of thousands that frontier-scale RL spins up.