eBPF-Driven Adaptive Lifetime-Aware Data Placement for Shared FDP SSDs

Abstract

NVMe Flexible Data Placement (FDP) reduces SSD write amplification by separating data with different lifetimes to minimize garbage collection (GC) copying. However, on shared servers, multiple tenants generate more lifetime classes than the available placement handles. Existing approaches rely on static mappings or application-specific knowledge, failing to capture runtime lifetimes and adapt to changing workloads. The challenge is to identify which data die together and determine which classes should be separated to maximize GC savings under a limited handle budget. We present eFDP, an eBPF-based system that automatically learns data lifetimes and manages FDP placement for unmodified applications on a stock Linux kernel. By tracking writes and invalidations, eFDP identifies lifetime classes and estimates the GC copying saved by separating them. It first assigns each tenant a handle, then allocates the remaining handles to the separations offering the greatest savings. It also re-plans placement when active tenants change. With four database tenants on an emulated FDP SSD, eFDP eliminates twice as much excess write amplification as tenant-level isolation and improves every writing tenant's throughput by 19-23%. On an enterprise FDP SSD, given RocksDB's levels, it matches a manually optimized placement using three handles instead of five. After a tenant switch, eFDP re-plans within seven minutes and maintains 25% lower write amplification than the original layout even after an hour.