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
Developed a live cluster CPU utilization–based enhancement for the Kafka capacity model in the Netflix-Skunkworks/service-capacity-modeling repository. This work integrated real-time cluster CPU data into the core estimation process, allowing the model to compute required resources more accurately and fall back to previous calculations when live data was unavailable. The implementation introduced a standardized function for handling CPU targets and refactored the estimation logic to prioritize live data. Comprehensive testing was added to validate the new workflow. Leveraged Python and Java, applying skills in capacity planning, performance analysis, and system modeling to improve resource provisioning and operational reliability.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
139
Activity Months1
Your Network
130 peopleSame Organization
@netflix.com103
Shared Repositories
27
argha-cMember
agali-09Member
Akashdeep GoelMember
Ammar KhakuMember
Alex McKeeMember
ayushisingh29Member
ayushisMember
ChengMember
cole perezMember
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
Loading activity data...
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
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline