google/perfetto
Nov 2025 – Nov 2025
1 Month active
Languages Used
C++Python
Technical Skills
performance monitoringprotobufsystem programming
Dmitry
PROFILE
Dmitry
Dmitry Skiba enhanced performance and observability in the google/perfetto repository by developing new metrics to monitor memory management, specifically focusing on kswapd efficiency. He introduced tracking for the number of pages allocated and the duration of kswapd processes, surfacing delta_nr_allocated as a key metric within the kswapd_efficiency slice. Using C++, Python, and protobuf, Dmitry updated integrations to reflect recent event changes, ensuring accurate correlation between metrics and event data. His work improved visibility into memory pressure, enabling more informed optimization and capacity planning. The project demonstrated depth in tracing instrumentation, event-driven metrics design, and system programming.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
30
Activity Months1
Your Network
233 peopleShared Repositories
233
Work History
November 2025
1 Commits • 1 Features
Nov 1, 2025November 2025 (2025-11): Performance and Observability improvements in google/perfetto focused on memory management metrics. Delivered Enhanced Kswapd Efficiency Metrics by adding new metrics to track memory allocation performance (pages allocated) and kswapd duration, and surfaced delta_nr_allocated as 'pages allocated' in the kswapd_efficiency slice. Updated integration to include the latest pixel_mm_kswapd_done event changes for accurate event correlation. Addressed issues related to bug 453699564 to align metric presentation with event data. Result is improved visibility into memory pressure and actionable data for optimization and capacity planning. Demonstrated strengths in tracing instrumentation, event-driven metrics, code quality, and cross-team collaboration.
1 Commits • 1 Features
Nov 1, 2025November 2025 (2025-11): Performance and Observability improvements in google/perfetto focused on memory management metrics. Delivered Enhanced Kswapd Efficiency Metrics by adding new metrics to track memory allocation performance (pages allocated) and kswapd duration, and surfaced delta_nr_allocated as 'pages allocated' in the kswapd_efficiency slice. Updated integration to include the latest pixel_mm_kswapd_done event changes for accurate event correlation. Addressed issues related to bug 453699564 to align metric presentation with event data. Result is improved visibility into memory pressure and actionable data for optimization and capacity planning. Demonstrated strengths in tracing instrumentation, event-driven metrics, code quality, and cross-team collaboration.
November 2025
Activity
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Quality Metrics
Correctness100.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++Python
Technical Skills
performance monitoringprotobufsystem programming
Repositories Contributed To
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