PeeR: First-Class Scheduling for Latency-Critical eBPF Applications
Jeremy Carin, Ben Holmes, Weiyang Wang, Ankit Bhardwaj, Manya Ghobadi
Abstract
We present PeeR, a novel eBPF runtime that makes latency-critical eBPF programs preemptable and schedulable while maintaining low overhead. As eBPF programs grow more complex, they expose a fundamental gap: performance-critical hooks execute in a non-preemptable softirq context, which is invisible to the scheduler. These programs bypass resource controls, break isolation, and cause head-of-line blocking, degrading tail latency. PeeR exploits two key properties of eBPF: the verifier enforces clean program state at helper function boundaries, making these sites natural preemption points, and non-trivial programs frequently call helpers, ensuring fine-grained preemption opportunities. Building on these properties, PeeR brings cooperative preemption to eBPF: lightweight budget checks, inserted at each helper call, force programs exceeding their budget to yield and resume later on per-CPU kernel threads. To handle a wide variety of workloads, PeeR uses a two-level scheduling model that integrates with sched e xt, where the outer level controls aggregate CPU time for eBPF workloads, while an inner micro-scheduler orders individual tasks according to an operator-defined policy. Our evaluation on Redis, Memcached, echo-server, and TPC-C workloads shows that PeeR reduces p99 latency for latency-sensitive requests by 3× to 19.8× over the current eBPF runtime, without starving competing long-running requests.
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