Shopify/opentelemetry-ebpf-profiler
Dec 2024 – Sep 2025
7 Months active
Languages Used
GoCRegexpAssembly
Technical Skills
DebuggingPerformance OptimizationSystem ProgrammingCode DocumentationError HandlingFile Handling
Timo Teräs
PROFILE
Timo Teräs
Timo Teräs contributed to the Shopify/opentelemetry-ebpf-profiler by building and refining core profiling infrastructure focused on memory efficiency, unwind data handling, and trace customization. He engineered features such as optimized coredump utilities, robust unwind information extraction, and centralized executable metadata reporting, using Go, C, and eBPF. His technical approach included refactoring ELF parsing for performance, standardizing inline usage in eBPF code, and consolidating string interning to reduce allocations and garbage collection pressure. Timo’s work addressed cross-platform reliability, improved profiling accuracy, and enabled flexible embedding, demonstrating depth in low-level systems, memory management, and distributed tracing within a complex backend environment.
Overall Statistics
Feature vs Bugs
94%Features
Repository Contributions
29Total
Bugs
1
Commits
29
Features
17
Lines of code
76,517
Activity Months7
Your Network
102 people
Work History
September 2025
1 Commits • 1 Features
Sep 1, 2025September 2025 monthly summary for Shopify/opentelemetry-ebpf-profiler focusing on feature delivery, impact, and technical excellence.
1 Commits • 1 Features
Sep 1, 2025September 2025 monthly summary for Shopify/opentelemetry-ebpf-profiler focusing on feature delivery, impact, and technical excellence.
September 2025
August 2025
5 Commits • 4 Features
Aug 1, 2025August 2025 monthly summary for Shopify/opentelemetry-ebpf-profiler: Delivered core performance and reliability enhancements focusing on memory efficiency, unwind data handling, trace hashing stabilization, and centralized executable metadata reporting. These changes reduce runtime overhead, improve profiling accuracy, and simplify maintenance across ARM64 environments and kernel configurations.
August 2025
5 Commits • 4 Features
Aug 1, 2025August 2025 monthly summary for Shopify/opentelemetry-ebpf-profiler: Delivered core performance and reliability enhancements focusing on memory efficiency, unwind data handling, trace hashing stabilization, and centralized executable metadata reporting. These changes reduce runtime overhead, improve profiling accuracy, and simplify maintenance across ARM64 environments and kernel configurations.
July 2025
9 Commits • 3 Features
Jul 1, 2025Monthly work summary for 2025-07 (Shopify/opentelemetry-ebpf-profiler). Focused on delivering robust unwind information extraction, removing build-time dependencies to improve portability and build robustness, and code quality refactors to reduce allocations and improve maintainability. Also fixed a memory mapping edge case to ensure correct handling of anonymous mappings and updated tests.
9 Commits • 3 Features
Jul 1, 2025Monthly work summary for 2025-07 (Shopify/opentelemetry-ebpf-profiler). Focused on delivering robust unwind information extraction, removing build-time dependencies to improve portability and build robustness, and code quality refactors to reduce allocations and improve maintainability. Also fixed a memory mapping edge case to ensure correct handling of anonymous mappings and updated tests.
July 2025
June 2025
7 Commits • 3 Features
Jun 1, 2025June 2025 performance summary for Shopify/opentelemetry-ebpf-profiler: delivered core features, stabilized memory usage, and improved performance of ELF symbolization and kernel symbol handling. Achieved Node.js nsolid fork compatibility, enhanced ELF parsing and symbolization for memory efficiency and speed, and introduced a kallsyms-based kernel symbol storage approach. Resulted in a more reliable, scalable, and cost-effective profiling pipeline across interpreters with tangible performance and footprint improvements.
June 2025
7 Commits • 3 Features
Jun 1, 2025June 2025 performance summary for Shopify/opentelemetry-ebpf-profiler: delivered core features, stabilized memory usage, and improved performance of ELF symbolization and kernel symbol handling. Achieved Node.js nsolid fork compatibility, enhanced ELF parsing and symbolization for memory efficiency and speed, and introduced a kallsyms-based kernel symbol storage approach. Resulted in a more reliable, scalable, and cost-effective profiling pipeline across interpreters with tangible performance and footprint improvements.
May 2025
1 Commits • 1 Features
May 1, 2025Month: 2025-05. Focused on standardizing inline usage in the eBPF tracing code for Shopify/opentelemetry-ebpf-profiler by introducing the EBPF_INLINE macro and consolidating inline definitions. This replaces ad hoc __attribute__((__always_inline__)) usage to improve code hygiene, readability, and maintainability across the tracing infrastructure. Implemented in commit 2f120484e814e97569e7d40c697a3bfc18d7c9e1. No other major features or bug fixes reported this month. Overall impact: cleaner, more maintainable codebase with lower risk of inline-related issues; easier onboarding for new contributors; better alignment with project conventions. Technologies/skills demonstrated: eBPF, C macros, inline function patterns, codebase standardization, and tracing infrastructure improvements. Business value: reduced maintenance cost, more reliable profiling and tracing, and faster iteration for feature work in the profiler.
1 Commits • 1 Features
May 1, 2025Month: 2025-05. Focused on standardizing inline usage in the eBPF tracing code for Shopify/opentelemetry-ebpf-profiler by introducing the EBPF_INLINE macro and consolidating inline definitions. This replaces ad hoc __attribute__((__always_inline__)) usage to improve code hygiene, readability, and maintainability across the tracing infrastructure. Implemented in commit 2f120484e814e97569e7d40c697a3bfc18d7c9e1. No other major features or bug fixes reported this month. Overall impact: cleaner, more maintainable codebase with lower risk of inline-related issues; easier onboarding for new contributors; better alignment with project conventions. Technologies/skills demonstrated: eBPF, C macros, inline function patterns, codebase standardization, and tracing infrastructure improvements. Business value: reduced maintenance cost, more reliable profiling and tracing, and faster iteration for feature work in the profiler.
May 2025
April 2025
5 Commits • 4 Features
Apr 1, 2025April 2025 monthly summary for Shopify/opentelemetry-ebpf-profiler: Delivered core reliability and capabilities enhancements that improve memory management, cross-process data extraction, tooling robustness, and profiling accuracy. Key features include an Interpreter Data.Unload hook across interpreters to automatically cleanup resources when an executable is removed or its reference count reaches zero, reducing memory leaks and stale eBPF entries. Process.ExtractAsFile enables extraction of executables from various process contexts, with CoredumpProcess and systemProcess implementations and robust temporary-file handling in the StoreCoredump workflow. Tooling improvements standardize path handling and comment punctuation, increasing cross-platform reliability. Go stack unwinding improvements for aarch64 (Go 1.21+) strengthen stack traces and profiling data quality. These changes collectively reduce runtime risk, improve stability across platforms, and enhance the value delivered by profiling data to customers.
April 2025
5 Commits • 4 Features
Apr 1, 2025April 2025 monthly summary for Shopify/opentelemetry-ebpf-profiler: Delivered core reliability and capabilities enhancements that improve memory management, cross-process data extraction, tooling robustness, and profiling accuracy. Key features include an Interpreter Data.Unload hook across interpreters to automatically cleanup resources when an executable is removed or its reference count reaches zero, reducing memory leaks and stale eBPF entries. Process.ExtractAsFile enables extraction of executables from various process contexts, with CoredumpProcess and systemProcess implementations and robust temporary-file handling in the StoreCoredump workflow. Tooling improvements standardize path handling and comment punctuation, increasing cross-platform reliability. Go stack unwinding improvements for aarch64 (Go 1.21+) strengthen stack traces and profiling data quality. These changes collectively reduce runtime risk, improve stability across platforms, and enhance the value delivered by profiling data to customers.
December 2024
1 Commits • 1 Features
Dec 1, 2024December 2024 monthly summary for Shopify/opentelemetry-ebpf-profiler: Delivered Coredump Utility Optimization and Sysroot Support. The refactor enhances memory efficiency and dump time by introducing an optional sysroot argument and updating dumpCore to conditionally set the coredump filter based on the noModuleBundling flag, enabling efficient dumps when mapped ELF files are available. Commit 84cce0a2aff60bced9fc9d1543a6393837f8d63d captures this work with message 'coredump: no need for full dump with bundled files (#213)'.
1 Commits • 1 Features
Dec 1, 2024December 2024 monthly summary for Shopify/opentelemetry-ebpf-profiler: Delivered Coredump Utility Optimization and Sysroot Support. The refactor enhances memory efficiency and dump time by introducing an optional sysroot argument and updating dumpCore to conditionally set the coredump filter based on the noModuleBundling flag, enabling efficient dumps when mapped ELF files are available. Commit 84cce0a2aff60bced9fc9d1543a6393837f8d63d captures this work with message 'coredump: no need for full dump with bundled files (#213)'.
December 2024
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Quality Metrics
Correctness91.4%
Maintainability87.8%
Architecture89.0%
Performance84.8%
AI Usage20.6%
Skills & Technologies
Programming Languages
AssemblyCGoRegexp
Technical Skills
API DesignARM64 AssemblyAssembly Language AnalysisBackend DevelopmentBuild SystemsC programmingCGOCache ManagementCode DocumentationCode OrganizationCode RefactoringCode ReversionDebuggingDisassembler integrationDistributed Tracing
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