In a detailed exploration of enhancing performance predictability and isolation for multi-tenant systems like CockroachDB, the text examines the application of control theory to the Go scheduler. It discusses challenges in managing CPU-heavy tasks, such as backups, which can impact latency-sensitive workloads. Traditional static rate limiting was insufficient, leading to the development of more dynamic solutions, such as feedback control systems that adjust CPU usage for elastic tasks based on scheduling latency. The text highlights the use of probabilistic tracing to capture latency outliers and the integration of cooperative scheduling, where elastic work self-regulates its CPU usage through token grants. Additionally, it outlines modifications to the Go runtime to track CPU time per goroutine, enhancing the ability to manage elastic workloads without OS-level interventions. Through experimentation, the scheme proved effective in reducing scheduling latency spikes, thus protecting the latency of foreground tasks.