Modern large-scale performance testing often runs up against a fundamental limitation: traditional virtual machines simply don’t scale economically or practically when simulating thousands of systems. Provisioning and managing 4,000–5,000 VMs quickly becomes cost-prohibitive and operationally unmanageable, making it difficult to accurately emulate real-world distributed workloads.

In this talk, I present a container-based approach for high-density system simulation that replaces VM-centric test environments with lightweight containers orchestrated on a small number of powerful hosts. Using Podman to run large numbers of containers on a single machine, we demonstrate how to spin up thousands of isolated test environments rapidly with significantly lower overhead than VMs.

I will walk through the challenges faced in this approach - like resource exhaustion , kernel limits and how to overcome those.We would wrap up by discussing how to run tests and collect metrics under high load.