google/perfetto
Nov 2024 – Oct 2025
8 Months active
Languages Used
C++SQLprotobufsqlPythonShellprotopython
Technical Skills
Android DevelopmentAndroid InternalsData ModelingData ParsingMetadata ManagementPerformance Analysis
elrakadm
PROFILE
Elrakadm
Elrakadm worked on the google/perfetto repository, delivering features and stability improvements to Perfetto’s trace analysis and metrics pipeline. Over eight months, Elrakadm enhanced trace data quality by standardizing Android trace slices, normalizing thread names, and enriching trace metadata for device-level insights. They implemented dimension specifications and explicit typing in Metrics v2, improving analytics precision and maintainability. Using C++, SQL, and Protocol Buffers, Elrakadm addressed performance bottlenecks, optimized data serialization, and fixed regressions affecting trace reliability. Their work included rigorous test automation and code refactoring, resulting in a more robust, scalable, and accurate tracing infrastructure for performance diagnostics.
Overall Statistics
Feature vs Bugs
67%Features
Repository Contributions
25Total
Bugs
4
Commits
25
Features
8
Lines of code
3,205
Activity Months8
Your Network
4376 people
Work History
October 2025
3 Commits • 1 Features
Oct 1, 2025This month focused on delivering substantial enhancements to the Perfetto trace summary to improve storage efficiency and trace analysis capabilities, with clean integration into the existing trace processing pipeline.
3 Commits • 1 Features
Oct 1, 2025This month focused on delivering substantial enhancements to the Perfetto trace summary to improve storage efficiency and trace analysis capabilities, with clean integration into the existing trace processing pipeline.
October 2025
August 2025
2 Commits
Aug 1, 2025August 2025 focused on stabilizing trace metrics and metric storage paths in google/perfetto. Reverted two risky changes that caused timeouts and regression, restoring reliable metric collection and reducing production risk. Clean-up and test hygiene improvements were performed to prevent recurrence and improve maintainability. Overall, the work safeguarded performance analytics integrity and preserved business value for users depending on accurate tracing data.
August 2025
2 Commits
Aug 1, 2025August 2025 focused on stabilizing trace metrics and metric storage paths in google/perfetto. Reverted two risky changes that caused timeouts and regression, restoring reliable metric collection and reducing production risk. Clean-up and test hygiene improvements were performed to prevent recurrence and improve maintainability. Overall, the work safeguarded performance analytics integrity and preserved business value for users depending on accurate tracing data.
July 2025
3 Commits
Jul 1, 2025Month: 2025-07 — Focused on stabilizing Perfetto's tracing data quality and reliability in google/perfetto. Key changes include reverting regression in Android frames missed callbacks tracking to restore stable android_frames data (removing related tables/functions and reverting the android_jank_cuj_frame_timeline join condition) and consolidating trace duration measurement fixes by switching to a monotonic clock for sched duration and updating tests. These changes reduce false positives/negatives in performance dashboards and improve reliability of performance analytics. Overall impact: improved accuracy of frame timing and scheduling duration measurements, reduced data drift due to system clock changes, and cleaner data model. Technologies/skills demonstrated: C++/repo maintenance, regression analysis, clock source selection, test updates, and data-model cleanup.
3 Commits
Jul 1, 2025Month: 2025-07 — Focused on stabilizing Perfetto's tracing data quality and reliability in google/perfetto. Key changes include reverting regression in Android frames missed callbacks tracking to restore stable android_frames data (removing related tables/functions and reverting the android_jank_cuj_frame_timeline join condition) and consolidating trace duration measurement fixes by switching to a monotonic clock for sched duration and updating tests. These changes reduce false positives/negatives in performance dashboards and improve reliability of performance analytics. Overall impact: improved accuracy of frame timing and scheduling duration measurements, reduced data drift due to system clock changes, and cleaner data model. Technologies/skills demonstrated: C++/repo maintenance, regression analysis, clock source selection, test updates, and data-model cleanup.
July 2025
May 2025
1 Commits • 1 Features
May 1, 2025For May 2025, the google/perfetto repository delivered notable Metrics v2 enhancements and stability improvements that directly support business analytics and data fidelity. The primary achievement was adding dimension specifications and explicit typing to Metrics v2, enabling precise dimension handling and safer metric emission. This work reduces ambiguity in metric data and sets a foundation for scalable analytics as usage grows. In addition, key bugs affecting dimension ordering and metric value emission were fixed, improving the reliability and determinism of metrics reporting. A new test case for simple_slices was added to validate the updated behavior and prevent regressions. Overall, this work strengthens the metrics pipeline, improves data quality, and enhances maintainability through stronger typing and expanded test coverage.
May 2025
1 Commits • 1 Features
May 1, 2025For May 2025, the google/perfetto repository delivered notable Metrics v2 enhancements and stability improvements that directly support business analytics and data fidelity. The primary achievement was adding dimension specifications and explicit typing to Metrics v2, enabling precise dimension handling and safer metric emission. This work reduces ambiguity in metric data and sets a foundation for scalable analytics as usage grows. In addition, key bugs affecting dimension ordering and metric value emission were fixed, improving the reliability and determinism of metrics reporting. A new test case for simple_slices was added to validate the updated behavior and prevent regressions. Overall, this work strengthens the metrics pipeline, improves data quality, and enhances maintainability through stronger typing and expanded test coverage.
March 2025
9 Commits • 2 Features
Mar 1, 2025Mar 2025 performance update for google/perfetto: Focused on elevating data quality and analytics readiness by standardizing Android trace data and extending task-intelligence in AndroidProcessMetadata. Delivered trace data standardization and thread name normalization to ensure consistent representation across traces, and added kernel-task visibility to enable targeted metrics. Implemented SQL-level data normalization capabilities (new __intrinsic_strip_hex, related refinements, and public exposure of thread_prefix) to simplify downstream queries and reduce normalization toil. Refactors to slice naming and thread-name normalization (removing non-essential digits, repeated patterns) to improve data cleanliness and maintainability. Business impact includes faster, more reliable trace analysis, reduced ad-hoc data cleansing, and more precise kernel-task analytics. Technologies/skills demonstrated include C++/Perfetto internals, protobufs, Perfetto SQL UDFs, and end-to-end data normalization and testing.
9 Commits • 2 Features
Mar 1, 2025Mar 2025 performance update for google/perfetto: Focused on elevating data quality and analytics readiness by standardizing Android trace data and extending task-intelligence in AndroidProcessMetadata. Delivered trace data standardization and thread name normalization to ensure consistent representation across traces, and added kernel-task visibility to enable targeted metrics. Implemented SQL-level data normalization capabilities (new __intrinsic_strip_hex, related refinements, and public exposure of thread_prefix) to simplify downstream queries and reduce normalization toil. Refactors to slice naming and thread-name normalization (removing non-essential digits, repeated patterns) to improve data cleanliness and maintainability. Business impact includes faster, more reliable trace analysis, reduced ad-hoc data cleansing, and more precise kernel-task analytics. Technologies/skills demonstrated include C++/Perfetto internals, protobufs, Perfetto SQL UDFs, and end-to-end data normalization and testing.
March 2025
February 2025
1 Commits • 1 Features
Feb 1, 2025February 2025: Key feature delivery in google/perfetto focused on Trace Processor slice name standardization for VSYNC and asset loading. Introduced _standardize_vsync_slice_name to map VSYNC-related slice names to a consistent format and broadened the existing standardization to cover asset loading and related entries, enabling clearer, more aggregable trace data across contexts.
February 2025
1 Commits • 1 Features
Feb 1, 2025February 2025: Key feature delivery in google/perfetto focused on Trace Processor slice name standardization for VSYNC and asset loading. Introduced _standardize_vsync_slice_name to map VSYNC-related slice names to a consistent format and broadened the existing standardization to cover asset loading and related entries, enabling clearer, more aggregable trace data across contexts.
December 2024
1 Commits • 1 Features
Dec 1, 2024December 2024 monthly summary for google/perfetto focused on feature delivery and data quality improvements in the tracing pipeline.
1 Commits • 1 Features
Dec 1, 2024December 2024 monthly summary for google/perfetto focused on feature delivery and data quality improvements in the tracing pipeline.
December 2024
November 2024
5 Commits • 2 Features
Nov 1, 2024November 2024: Implemented device-level context and reliability improvements in Perfetto to drive actionable performance insights and faster optimization loops. Delivered trace enrichment (device manufacturer) and CUJ/jank accuracy enhancements, with robust data quality improvements.
November 2024
5 Commits • 2 Features
Nov 1, 2024November 2024: Implemented device-level context and reliability improvements in Perfetto to drive actionable performance insights and faster optimization loops. Delivered trace enrichment (device manufacturer) and CUJ/jank accuracy enhancements, with robust data quality improvements.
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Quality Metrics
Correctness92.0%
Maintainability92.0%
Architecture90.8%
Performance88.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++ProtoPythonSQLShellprotoprotobufpythonsql
Technical Skills
Android DevelopmentAndroid InternalsBackend DevelopmentBug FixingBuild SystemsC++Code RefactoringCode RevertData ModelingData ParsingData ProcessingData SerializationDatabaseDebuggingMetadata Management
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