
Edgar Arriaga contributed to the google/perfetto and android/snippets repositories by building modular profiling and trace analysis tools that improved reliability, maintainability, and developer onboarding. He introduced a reusable clock synchronizer in C++ to decouple clock tracking, refactored trace processing utilities for better testability, and enhanced the trace redactor with clock collection and call stack support to improve data sanitization. Edgar also delivered PyPI packaging and protobuf support for Bigtrace, streamlining cloud deployment and installation workflows using Python and Docker. His work demonstrated depth in system programming, build system configuration, and documentation, resulting in more robust and accessible performance engineering infrastructure.

October 2025 performance summary for google/perfetto. Delivered substantive enhancements to the Trace Redactor and Trace Processor, improving time-based analysis, data sanitization, reliability, and maintainability. Business value includes more accurate, robust trace data for performance diagnoses and streamlined test infrastructure for faster iteration and lower maintenance costs. Highlights include new clock collection, perf event pruning, and call stack support in the redactor; a stability fix for perf samples without PID; and refactoring that decouples trace blob utilities and consolidates trace processor loading in tests.
October 2025 performance summary for google/perfetto. Delivered substantive enhancements to the Trace Redactor and Trace Processor, improving time-based analysis, data sanitization, reliability, and maintainability. Business value includes more accurate, robust trace data for performance diagnoses and streamlined test infrastructure for faster iteration and lower maintenance costs. Highlights include new clock collection, perf event pruning, and call stack support in the redactor; a stability fix for perf samples without PID; and refactoring that decouples trace blob utilities and consolidates trace processor loading in tests.
September 2025: Delivered a reusable clock-tracking utility by introducing Clock Synchronizer, decoupling clock tracking from TraceProcessorContext and refactoring into a template with a listener interface. This modular design enables cross-component reuse, simplifies integration, and reduces coupling, laying groundwork for broader clock-related functionality. The work improves maintainability and accelerates feature delivery by enabling clock-related capabilities to be reused across Perfetto components.
September 2025: Delivered a reusable clock-tracking utility by introducing Clock Synchronizer, decoupling clock tracking from TraceProcessorContext and refactoring into a template with a listener interface. This modular design enables cross-component reuse, simplifies integration, and reduces coupling, laying groundwork for broader clock-related functionality. The work improves maintainability and accelerates feature delivery by enabling clock-related capabilities to be reused across Perfetto components.
2025-07 monthly summary: Delivered Profiling Capabilities Documentation and Examples for ProfilingManager in the android/snippets repository, including build configuration updates and new sample Java/Kotlin files for recording and processing profiling data. No major bugs fixed this month. Impact includes improved developer onboarding for profiling, concrete samples to validate profiling workflows, and alignment with DAC/docs standards to improve consistency and adoption. Technologies demonstrated include Java/Kotlin profiling samples, build configuration changes, and documentation craftsmanship.
2025-07 monthly summary: Delivered Profiling Capabilities Documentation and Examples for ProfilingManager in the android/snippets repository, including build configuration updates and new sample Java/Kotlin files for recording and processing profiling data. No major bugs fixed this month. Impact includes improved developer onboarding for profiling, concrete samples to validate profiling workflows, and alignment with DAC/docs standards to improve consistency and adoption. Technologies demonstrated include Java/Kotlin profiling samples, build configuration changes, and documentation craftsmanship.
May 2025 focused on accelerating Bigtrace adoption, improving reliability, and strengthening deployment/packaging workflows. Delivered packaging and protobuf support to enable easy installation and structured query capabilities, improved container environments for consistent builds, and corrected deployment guidance to prevent misconfigurations and streamline verification.
May 2025 focused on accelerating Bigtrace adoption, improving reliability, and strengthening deployment/packaging workflows. Delivered packaging and protobuf support to enable easy installation and structured query capabilities, improved container environments for consistent builds, and corrected deployment guidance to prevent misconfigurations and streamline verification.
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