google/perfetto
Nov 2024 – Oct 2025
9 Months active
Languages Used
SQLPythonTypeScriptBPGNprotobuf
Technical Skills
Database DesignPerformance AnalysisSQLPythonRegular ExpressionsScripting
devianb
PROFILE
Devianb
Devarshi Bhattacharya contributed to the google/perfetto repository by engineering data model upgrades and performance analytics features for Android frame rendering and jank analysis. He designed and evolved SQL schemas, integrating new tables and metrics pipelines to improve the fidelity and granularity of frame and blocking-call data. Using Python, SQL, and TypeScript, Devarshi implemented cross-process metric collection, refactored build systems, and enhanced plugin reliability. His work included debugging, code cleanup, and rollback management to maintain telemetry stability. The depth of his contributions is reflected in robust test coverage, documentation updates, and a focus on maintainable, scalable performance analysis infrastructure.
Overall Statistics
Feature vs Bugs
57%Features
Repository Contributions
34Total
Bugs
9
Commits
34
Features
12
Lines of code
4,899
Activity Months9
Your Network
4376 people
Work History
October 2025
1 Commits
Oct 1, 2025October 2025 monthly summary for google/perfetto: Reverted the CUJ counters integration added to the standard library, restoring baseline behavior and removing references to sysui_cuj_counters.sql from build files and metrics SQL. The rollback centers on commit fd4ade59058ba1d7fdb501f7bee0642cf7073afa and preserves stable telemetry dashboards and release integrity. This work focused on risk mitigation, repo hygiene, and clear rollback traceability to support future feature work.
1 Commits
Oct 1, 2025October 2025 monthly summary for google/perfetto: Reverted the CUJ counters integration added to the standard library, restoring baseline behavior and removing references to sysui_cuj_counters.sql from build files and metrics SQL. The rollback centers on commit fd4ade59058ba1d7fdb501f7bee0642cf7073afa and preserves stable telemetry dashboards and release integrity. This work focused on risk mitigation, repo hygiene, and clear rollback traceability to support future feature work.
October 2025
September 2025
9 Commits • 1 Features
Sep 1, 2025September 2025 monthly summary for google/perfetto focused on Android Jank CUJ metrics overhaul and System UI plugin reliability. Delivered a major data-model overhaul for Jank CUJ analytics, integrating new frames/slices tables with stdlib tables, enabling more accurate end-to-end jank analysis across System UI CUJs. Implemented System UI Plugin Package Name Fix to ensure proper registration. Reverted Android Jank CUJ stdlib migration to address issues encountered in early rollout, followed by stabilization efforts. Achieved improved data quality, faster insight into UI performance, and a more maintainable metrics pipeline. Demonstrated proficiency in data modeling, stdlib integration, plugin packaging, and dependency management.
September 2025
9 Commits • 1 Features
Sep 1, 2025September 2025 monthly summary for google/perfetto focused on Android Jank CUJ metrics overhaul and System UI plugin reliability. Delivered a major data-model overhaul for Jank CUJ analytics, integrating new frames/slices tables with stdlib tables, enabling more accurate end-to-end jank analysis across System UI CUJs. Implemented System UI Plugin Package Name Fix to ensure proper registration. Reverted Android Jank CUJ stdlib migration to address issues encountered in early rollout, followed by stabilization efforts. Achieved improved data quality, faster insight into UI performance, and a more maintainable metrics pipeline. Demonstrated proficiency in data modeling, stdlib integration, plugin packaging, and dependency management.
August 2025
5 Commits • 2 Features
Aug 1, 20252025-08 performance engineering sprint in google/perfetto delivering data-model enhancements and reliability improvements for blocking-call analysis. Implemented new blocking-call SQL module, added a debug visualization track for max-duration frames, and resolved several metric calculation and pinning issues to improve bottleneck identification, accuracy of per-frame metrics, and UI integration.
5 Commits • 2 Features
Aug 1, 20252025-08 performance engineering sprint in google/perfetto delivering data-model enhancements and reliability improvements for blocking-call analysis. Implemented new blocking-call SQL module, added a debug visualization track for max-duration frames, and resolved several metric calculation and pinning issues to improve bottleneck identification, accuracy of per-frame metrics, and UI integration.
August 2025
July 2025
10 Commits • 3 Features
Jul 1, 2025July 2025 performance summary for google/perfetto. Focused on improving accuracy, reliability, and maintainability of tracing metrics, with clear business value in faster diagnostics and richer performance insights. Delivered architectural shifts to standardize CUJ metrics, enhanced data flow for graphics performance, and improved documentation to streamline trace analysis.
July 2025
10 Commits • 3 Features
Jul 1, 2025July 2025 performance summary for google/perfetto. Focused on improving accuracy, reliability, and maintainability of tracing metrics, with clear business value in faster diagnostics and richer performance insights. Delivered architectural shifts to standardize CUJ metrics, enhanced data flow for graphics performance, and improved documentation to streamline trace analysis.
May 2025
4 Commits • 2 Features
May 1, 2025Month: 2025-05 — google/perfetto: Focused performance observability improvements, critical data processing fix, and codebase cleanup to reduce maintenance overhead and enable scalable analytics.
4 Commits • 2 Features
May 1, 2025Month: 2025-05 — google/perfetto: Focused performance observability improvements, critical data processing fix, and codebase cleanup to reduce maintenance overhead and enable scalable analytics.
May 2025
March 2025
1 Commits • 1 Features
Mar 1, 2025March 2025 — Delivered a key feature for google/perfetto: added a ts_end end timestamp column for android_frames_layers (ts_end = ts + dur) to ensure consistent end timestamps, enabling data integrity and smoother stdlib migration. The change updated SQL schemas, queries, and tests. No major bugs fixed this month. Impact: improved frame-layer analytics accuracy and prepared groundwork for downstream migrations. Technologies/skills demonstrated: SQL schema evolution, data modeling, test-driven changes, and cross-repo collaboration.
March 2025
1 Commits • 1 Features
Mar 1, 2025March 2025 — Delivered a key feature for google/perfetto: added a ts_end end timestamp column for android_frames_layers (ts_end = ts + dur) to ensure consistent end timestamps, enabling data integrity and smoother stdlib migration. The change updated SQL schemas, queries, and tests. No major bugs fixed this month. Impact: improved frame-layer analytics accuracy and prepared groundwork for downstream migrations. Technologies/skills demonstrated: SQL schema evolution, data modeling, test-driven changes, and cross-repo collaboration.
January 2025
1 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary for google/perfetto focusing on enhancing observability for Auto-pin Debug Track. Implemented per-frame blocking call metrics instrumentation, updated metric key parsing to support per-frame data, and added unit tests to ensure correct parsing and handling. These changes enable more granular frame-level performance analysis, supporting faster diagnosis of frame-time bottlenecks and improved end-to-end tracing.
1 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary for google/perfetto focusing on enhancing observability for Auto-pin Debug Track. Implemented per-frame blocking call metrics instrumentation, updated metric key parsing to support per-frame data, and added unit tests to ensure correct parsing and handling. These changes enable more granular frame-level performance analysis, supporting faster diagnosis of frame-time bottlenecks and improved end-to-end tracing.
January 2025
December 2024
2 Commits • 1 Features
Dec 1, 2024December 2024 monthly summary for google/perfetto focusing on reliability, observability, and correctness. Key features delivered: - Improved frame timeline metrics across processes: Removed the upid check in the jank CUJ frame timeline table, enabling metrics to populate when the Surface layer is generated in a different process. Uses layer ID comparison and a vsync range check to maintain accurate timeline data across process boundaries. Major bugs fixed: - Banned Drop Script - Correct Object Name Extraction: Fixed incorrect regex capture indexing (group 2 to group 1) in the check_banned_drop script, ensuring the object name is accurately extracted and the banned drop check behaves as intended. Overall impact and accomplishments: - Enhanced observability with reliable cross-process frame timeline data, improving debugging and performance analysis capabilities. - Correctness, stability, and data quality improvements with minimal risk and quick remediation. Technologies/skills demonstrated: - Regex and string parsing accuracy, cross-process metric collection, and data population logic. - Refactoring to remove process-bound checks without sacrificing correctness. - Concrete commit-level changes with per-feature traceability.
December 2024
2 Commits • 1 Features
Dec 1, 2024December 2024 monthly summary for google/perfetto focusing on reliability, observability, and correctness. Key features delivered: - Improved frame timeline metrics across processes: Removed the upid check in the jank CUJ frame timeline table, enabling metrics to populate when the Surface layer is generated in a different process. Uses layer ID comparison and a vsync range check to maintain accurate timeline data across process boundaries. Major bugs fixed: - Banned Drop Script - Correct Object Name Extraction: Fixed incorrect regex capture indexing (group 2 to group 1) in the check_banned_drop script, ensuring the object name is accurately extracted and the banned drop check behaves as intended. Overall impact and accomplishments: - Enhanced observability with reliable cross-process frame timeline data, improving debugging and performance analysis capabilities. - Correctness, stability, and data quality improvements with minimal risk and quick remediation. Technologies/skills demonstrated: - Regex and string parsing accuracy, cross-process metric collection, and data population logic. - Refactoring to remove process-bound checks without sacrificing correctness. - Concrete commit-level changes with per-feature traceability.
November 2024
1 Commits • 1 Features
Nov 1, 2024November 2024 monthly summary for google/perfetto. Key feature delivered: introduced android_frames_layers to capture layer IDs per actual frame, refining the android_frames table for granular, accurate frame data. This data model upgrade improves analytics fidelity for Android frame rendering, supports precise performance investigations, and comes with updated documentation. Business impact: improved telemetry accuracy reduces investigation time and informs optimization priorities for frame rendering paths. Skills demonstrated: data modeling, schema evolution, SQL/data pipelines, data quality improvements, and cross-team collaboration.
1 Commits • 1 Features
Nov 1, 2024November 2024 monthly summary for google/perfetto. Key feature delivered: introduced android_frames_layers to capture layer IDs per actual frame, refining the android_frames table for granular, accurate frame data. This data model upgrade improves analytics fidelity for Android frame rendering, supports precise performance investigations, and comes with updated documentation. Business impact: improved telemetry accuracy reduces investigation time and informs optimization priorities for frame rendering paths. Skills demonstrated: data modeling, schema evolution, SQL/data pipelines, data quality improvements, and cross-team collaboration.
November 2024
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Quality Metrics
Correctness91.2%
Maintainability88.2%
Architecture88.8%
Performance85.2%
AI Usage20.0%
Skills & Technologies
Programming Languages
BPGNPythonSQLTypeScriptprotobuf
Technical Skills
Android DevelopmentAndroid InternalsAndroid Performance AnalysisBuild System ConfigurationBuild SystemsCode RefactoringDatabaseDatabase DesignDatabase OptimizationDebuggingDocumentationPerformance AnalysisPerformance MetricsPerformance OptimizationPlugin Development
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