open-edge-platform/edge-ai-libraries
May 2025 – May 2025
1 Month active
Languages Used
DockerfileINIPythonShell
Technical Skills
ContainerizationData VisualizationPerformance AnalysisSystem MonitoringTelemetry
Daya Kulkarni
PROFILE
Daya Kulkarni
Developed and deployed a streaming telemetry feature for the open-edge-platform/edge-ai-libraries repository, focusing on real-time observability for edge AI pipelines. The work integrated Telegraf for continuous data collection and Supervisord for process monitoring, with telemetry data parsed into Pandas DataFrames and visualized through interactive Plotly dashboards. Legacy telemetry components were refactored or removed to streamline maintenance and improve reliability. Using Python, Dockerfile, and Shell, the solution enhanced system monitoring and performance analysis, providing immediate visibility into pipeline and system health. This enabled faster issue detection and supported data-driven optimization, delivering measurable business value through improved runtime metrics and decision support.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
1,236
Activity Months1
Your Network
2197 peopleSame Organization
@intel.com2109
Work History
May 2025
1 Commits • 1 Features
May 1, 2025Month: 2025-05 | Focused on delivering robust streaming telemetry for edge AI pipelines and enhancing observability. Implemented end-to-end telemetry ingestion, processing, and visualization, and cleaned up legacy components to reduce surface area and maintenance burden. This month yielded measurable business value in improved runtime visibility and data-driven decision support.
1 Commits • 1 Features
May 1, 2025Month: 2025-05 | Focused on delivering robust streaming telemetry for edge AI pipelines and enhancing observability. Implemented end-to-end telemetry ingestion, processing, and visualization, and cleaned up legacy components to reduce surface area and maintenance burden. This month yielded measurable business value in improved runtime visibility and data-driven decision support.
May 2025
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
DockerfileINIPythonShell
Technical Skills
ContainerizationData VisualizationPerformance AnalysisSystem MonitoringTelemetry
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