
Apoorv developed two cross-repository features to enhance FLR observability and proactive maintenance within the sonic-net ecosystem. In sonic-utilities, Apoorv extended the portstat utility to support Forward Error Correction Frame Loss Rate statistics, updating data structures and formatting to display both observed and predicted FLR, and providing comprehensive tests and documentation. For sonic-swss, Apoorv implemented Lua-based FLR monitoring integrated with orchagent, applying linear regression to codeword error distributions for predictive analytics. Using C++, Lua, and data analysis techniques, Apoorv’s work improved network reliability and fault isolation, demonstrating depth in CLI development, network monitoring, and predictive maintenance engineering.

Month: 2025-10 — Two cross-repo features delivered to strengthen FLR observability and proactive maintenance across sonic-net projects. No major bugs fixed this period. Impact includes improved network reliability and faster fault isolation through enhanced visibility, accurate FLR measurements, and forward-looking predictions. Technologies/skills demonstrated include Lua scripting, orchestration integration (orchagent), data-structure/formatting enhancements, testing/documentation, and applying linear regression to codeword error distributions for FLR prediction.
Month: 2025-10 — Two cross-repo features delivered to strengthen FLR observability and proactive maintenance across sonic-net projects. No major bugs fixed this period. Impact includes improved network reliability and faster fault isolation through enhanced visibility, accurate FLR measurements, and forward-looking predictions. Technologies/skills demonstrated include Lua scripting, orchestration integration (orchagent), data-structure/formatting enhancements, testing/documentation, and applying linear regression to codeword error distributions for FLR prediction.
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