Netflix-Skunkworks/service-capacity-modeling
Mar 2025 – Mar 2025
1 Month active
Languages Used
JavaPython
Technical Skills
Capacity PlanningPerformance AnalysisPython DevelopmentSystem ModelingTesting
Nick Mahilani
PROFILE
Nick Mahilani
In March 2025, Nikhil Mahilani enhanced the Kafka capacity model in the Netflix-Skunkworks/service-capacity-modeling repository by integrating live cluster CPU utilization into core estimation logic. Using Python and system modeling techniques, he refactored the model to prioritize real-time CPU data for more accurate capacity planning, while maintaining a fallback to previous calculations when live data was unavailable. He introduced a standardized target_cpu_utilzation function and developed new tests to validate the updated workflow. This work improved the model’s responsiveness and reliability, demonstrating Nikhil’s strengths in capacity planning, performance analysis, and rigorous testing within dynamic, data-driven environments.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
139
Activity Months1
Your Network
111 people
Work History
March 2025
1 Commits • 1 Features
Mar 1, 2025March 2025: Delivered a live cluster CPU utilization–based enhancement to the Kafka capacity model in Netflix-Skunkworks/service-capacity-modeling. The model now uses current cluster CPU utilization to compute needed cores, with a fallback to the previous calculation when live data is unavailable. Introduced a target_cpu_utilzation function and updated the estimation logic to prioritize live data. Added test_plan_certain to validate the new behavior. This work improves capacity planning accuracy and responsiveness, enabling better resource provisioning, cost efficiency, and reliability in dynamic environments. Demonstrated strengths in data-driven modeling, live data integration, test planning, and clean refactoring.
1 Commits • 1 Features
Mar 1, 2025March 2025: Delivered a live cluster CPU utilization–based enhancement to the Kafka capacity model in Netflix-Skunkworks/service-capacity-modeling. The model now uses current cluster CPU utilization to compute needed cores, with a fallback to the previous calculation when live data is unavailable. Introduced a target_cpu_utilzation function and updated the estimation logic to prioritize live data. Added test_plan_certain to validate the new behavior. This work improves capacity planning accuracy and responsiveness, enabling better resource provisioning, cost efficiency, and reliability in dynamic environments. Demonstrated strengths in data-driven modeling, live data integration, test planning, and clean refactoring.
March 2025
Activity
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Quality Metrics
Correctness90.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
JavaPython
Technical Skills
Capacity PlanningPerformance AnalysisPython DevelopmentSystem ModelingTesting
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