
Over four months, Josh Koch developed and enhanced capacity planning tools within the Netflix-Skunkworks/service-capacity-modeling repository. He built automated solutions for integrating AWS EC2 pricing data, generating instance family configurations, and expanding support for new AWS instance types, all aimed at improving cost modeling and capacity accuracy. Using Python, Jupyter Notebook, and JSON, Josh implemented deterministic data outputs, robust merge logic, and reproducible notebook-based estimators leveraging Erlang-C models. His work reduced manual configuration, improved automation reliability, and enabled data-driven decision-making for cloud infrastructure planning, demonstrating depth in backend development, data modeling, and cloud computing with a focus on maintainability.
October 2025 monthly summary for the Netflix-Skunkworks service-capacity-modeling repo focused on expanding real-world coverage for capacity planning and ensuring reliable outputs in automation. The work delivers broader instance-type support, performance modeling improvements, and a reliability-focused bug fix with clear business value.
October 2025 monthly summary for the Netflix-Skunkworks service-capacity-modeling repo focused on expanding real-world coverage for capacity planning and ensuring reliable outputs in automation. The work delivers broader instance-type support, performance modeling improvements, and a reliability-focused bug fix with clear business value.
May 2025 monthly summary for Netflix-Skunkworks/service-capacity-modeling focusing on business value and technical achievements. Delivered automated AWS Instance Family Configuration Generator to improve capacity modeling. The tool automatically generates missing AWS instance family configurations, updates tests and instance family definitions to cover new instance types and performance characteristics, and broadens coverage of AWS hardware options. This automation reduces manual configuration, accelerates onboarding of new instance types, and increases accuracy of capacity planning across services.
May 2025 monthly summary for Netflix-Skunkworks/service-capacity-modeling focusing on business value and technical achievements. Delivered automated AWS Instance Family Configuration Generator to improve capacity modeling. The tool automatically generates missing AWS instance family configurations, updates tests and instance family definitions to cover new instance types and performance characteristics, and broadens coverage of AWS hardware options. This automation reduces manual configuration, accelerates onboarding of new instance types, and increases accuracy of capacity planning across services.
February 2025 Monthly Summary for Netflix-Skunkworks/service-capacity-modeling: Focused on delivering headroom estimation tooling to enable data-driven capacity planning and cost optimization.
February 2025 Monthly Summary for Netflix-Skunkworks/service-capacity-modeling: Focused on delivering headroom estimation tooling to enable data-driven capacity planning and cost optimization.
January 2025 monthly summary for Netflix-Skunkworks/service-capacity-modeling focused on delivering deterministic EC2 pricing integration and robust data handling to sharpen capacity planning and cost modeling. Key accomplishments include the delivery of the EC2 Pricing Data Integration and Deterministic Pricing Outputs feature, which fetches latest EC2 pricing from AWS, supports multiple pricing files sorted lexicographically, refactors pricing data loading and fetching for clarity and maintainability, ensures deterministic JSON output, and implements robust pricing merge logic with tests. The work is backed by targeted commits that show end-to-end development and quality improvements.
January 2025 monthly summary for Netflix-Skunkworks/service-capacity-modeling focused on delivering deterministic EC2 pricing integration and robust data handling to sharpen capacity planning and cost modeling. Key accomplishments include the delivery of the EC2 Pricing Data Integration and Deterministic Pricing Outputs feature, which fetches latest EC2 pricing from AWS, supports multiple pricing files sorted lexicographically, refactors pricing data loading and fetching for clarity and maintainability, ensures deterministic JSON output, and implements robust pricing merge logic with tests. The work is backed by targeted commits that show end-to-end development and quality improvements.

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