Practical Guide to Container Isolation

The promise of containers is that they can "run anywhere," but for platform teams, the reality is often "escape anywhere" due to the shared host kernel. Standard containerization is not isolation, leaving your platform vulnerable to security breaches and performance degradation. This session moves beyond the basics of containerization to provide a practical guide to workload isolation. We will dissect the spectrum of isolation technologies—from Linux primitives like namespaces, cgroups, and seccomp to stronger boundaries like microVMs (e.g., Firecracker) and confidential computing. We’ll also look at how Apple’s Containerization Framework has made strong container isolation possible in development environments. Finally, we’ll dive into the next frontier: GPU isolation for AI workloads and discuss why sharing powerful hardware creates new, significant risks and how to architect a robust, efficient, and truly multi-tenant platform for the era of AI. You’ll come away with an understanding of the real-world tradeoffs of each approach for your platform's security, performance, and operational goals.