Memory-aware scheduling for mmap-backed stateful nodes

Memory-aware scheduling for mmap-backed stateful nodes targets a $3.6B = 36,000 enterprises × $100K ACV total addressable market with medium saturation and a year-over-year growth rate of 12% YoY — based on Gartner/IDC reporting on observability and cloud infrastructure software growth 2023-2025.

Key trends driving demand: Kernel-level observability is maturing — eBPF and sidecar telemetry make resident-set measurement feasible and low-overhead, creating product opportunities for memory-aware scheduling.; Stateful, mmap-heavy workloads (vector search, columnar OLAP, media indexing) are growing, increasing demand for specialized operational tooling.; Cloud providers and platform teams prefer operator-friendly integrations (daemonsets, CSI drivers, scheduler plugins), enabling a thin-surface product to attach to existing control planes.; SRE and platform engineering headcount is constrained, so teams favor automated mitigations and prescriptive policy over raw dashboards..