Karin Inbar is a Chief System & FW Architect for next-gen Enterprise SSDs at SanDisk. In this role, she defines end-to-end system solutions from compute to storage, ASIC requirements and firmware flows, tailored to evolving industry standards and customer requirements. Her expertise spans the entire storage stack from NVMe to NAND, including flash management, data path, performance, QoS, and analysis of complex problems.
Karin was named a finalist for the 2025 GSA Women of Influence Award, holds over 35 granted U.S. patents (Feb 2026), and earned her Computer Science & Biology B.Sc. with distinction from Tel Aviv University.
Enterprise SSDs inevitably undergo performance degradation as they accumulate wear, driven by diminishing available spares, rising write amplification, and block retirement. While modern SSDs expose a variety of health indicators, the industry lacks a predictable, data‑driven approach for identifying when an SSD is about to experience a significant performance drop. Existing telemetry provides raw indicators, but no practical framework connects them to an actionable EOL performance threshold.
By systematically leveraging SMART attributes and OCP‑defined log pages—including available spares, over‑provisioning utilization, and total bytes written (TBW)—operators can establish a reliable model for tracking SSD aging. These parameters enable determining a repurposing point before the device reaches its performance cliff, ensuring that drives transition smoothly to lower‑demand roles rather than causing unexpected service degradation.