
Worked on a comprehensive overhaul of the Capacity Planner in the Netflix-Skunkworks/service-capacity-modeling repository, focusing on enhancing the accuracy and flexibility of capacity planning. Leveraged Python and backend development skills to integrate real-time cluster utilization into capacity_desires, enabling more data-driven decisions. The approach involved removing network and CPU-specific filtering, allowing the model to dynamically determine resource requirements. Calculation steps were refactored to ensure instance data availability before per-instance computations, and a disk utilization metric was added for more holistic modeling. This work improved system design and data modeling, reducing hard-coded constraints and supporting more adaptable cloud capacity planning workflows.
February 2025: Delivered a major overhaul of the Capacity Planner in Netflix-Skunkworks/service-capacity-modeling. Consolidated five commits into a cohesive upgrade that integrates current cluster utilization into capacity_desires, removes network filtering, reorders calculation steps to ensure data availability before per-instance calculations, removes CPU-specific filtering so the model determines CPU requirements, and adds a disk utilization metric for more holistic capacity modeling. No major bugs fixed this month; changes improve planning accuracy, reduce hard-coded behavior, and enable data-driven decisions across clusters.
February 2025: Delivered a major overhaul of the Capacity Planner in Netflix-Skunkworks/service-capacity-modeling. Consolidated five commits into a cohesive upgrade that integrates current cluster utilization into capacity_desires, removes network filtering, reorders calculation steps to ensure data availability before per-instance calculations, removes CPU-specific filtering so the model determines CPU requirements, and adds a disk utilization metric for more holistic capacity modeling. No major bugs fixed this month; changes improve planning accuracy, reduce hard-coded behavior, and enable data-driven decisions across clusters.

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