microsoft/sonic-gnmi-dev
Jun 2025 – Jun 2025
1 Month active
Languages Used
GoJSONMarkdown
Technical Skills
Data ModelingDatabase InteractionNetwork MonitoringNetwork TelemetryTelemetryTesting
mramezani95
PROFILE
Mramezani95
In June 2025, Mohammad Ramezani enhanced network telemetry in the microsoft/sonic-gnmi-dev repository by delivering two features focused on watermark observability. He implemented queue-level periodic watermark telemetry, exposing SAI queue statistics through PERIODIC_WATERMARKS and enabling queries by queue name. Additionally, he introduced virtual paths for periodic priority group watermarks, allowing port-name-based queries via OID-name resolution. These updates, developed in Go and leveraging gRPC, improved the system’s ability to monitor and diagnose watermark-related issues. Mohammad also updated documentation and tests, ensuring robust coverage and supporting data-driven capacity planning for more reliable network operations and faster troubleshooting.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
2
Lines of code
1,690
Activity Months1
Your Network
4177 people
Work History
June 2025
2 Commits • 2 Features
Jun 1, 2025June 2025: Delivered two telemetry enhancements in microsoft/sonic-gnmi-dev that strengthen observability and queryability of watermark metrics. Implemented queue-level periodic watermark telemetry exposed via PERIODIC_WATERMARKS and added virtual paths for periodic priority group watermarks, enabling port-name-based querying and easier capacity planning. Updated documentation and tests to reflect the new functionality. These changes improve troubleshooting speed, reduce mean time to detect and diagnose watermark-related issues, and support data-driven capacity planning. Technologies demonstrated include SAI queue stats, PERIODIC_WATERMARKS, virtual path mappings, and OID-name resolution.
2 Commits • 2 Features
Jun 1, 2025June 2025: Delivered two telemetry enhancements in microsoft/sonic-gnmi-dev that strengthen observability and queryability of watermark metrics. Implemented queue-level periodic watermark telemetry exposed via PERIODIC_WATERMARKS and added virtual paths for periodic priority group watermarks, enabling port-name-based querying and easier capacity planning. Updated documentation and tests to reflect the new functionality. These changes improve troubleshooting speed, reduce mean time to detect and diagnose watermark-related issues, and support data-driven capacity planning. Technologies demonstrated include SAI queue stats, PERIODIC_WATERMARKS, virtual path mappings, and OID-name resolution.
June 2025
Activity
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Quality Metrics
Correctness100.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
GoJSONMarkdown
Technical Skills
Data ModelingDatabase InteractionNetwork MonitoringNetwork TelemetryTelemetryTestinggRPC
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