DataDog/dd-trace-java
Nov 2024 – Jan 2025
2 Months active
Languages Used
GroovyJavaTOML
Technical Skills
Agent DevelopmentAgent InstrumentationException HandlingJFRJava DevelopmentJava Profiling
Richard Startin
PROFILE
Richard Startin
Richard Startin enhanced the DataDog/dd-trace-java repository by developing advanced profiling and queue event tracking features for the Java agent. He introduced post-commit rate limiting for profiling data collection, leveraging Java and JFR to improve sampling accuracy and reduce noise. His work included robust exception handling in agent instrumentation and enabled SystemGC event tracking for deeper garbage collection insights. In January 2025, Richard added queue type and length reporting at enqueue time, providing granular visibility into queue-heavy workloads. Throughout, he focused on concurrency, profiling, and testing, delivering targeted improvements that strengthened observability and laid groundwork for future performance optimizations.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
5Total
Bugs
0
Commits
5
Features
3
Lines of code
428
Activity Months2
Your Network
925 people
Work History
January 2025
1 Commits • 1 Features
Jan 1, 2025January 2025: Delivered Queue Event Tracking Enhancement for DataDog/dd-trace-java, adding queue type and length captured at enqueue time and reporting them alongside existing queue timing information to provide granular insights into queue behavior and potential performance bottlenecks. Implemented under commit af5f4412a1ed1e26982102fbfd3966a95eb3f959 (references #8242). This work strengthens end-to-end tracing, improves observability of queue-heavy workloads, and lays groundwork for targeted performance optimization with minimal surface-area changes and backward compatibility.
1 Commits • 1 Features
Jan 1, 2025January 2025: Delivered Queue Event Tracking Enhancement for DataDog/dd-trace-java, adding queue type and length captured at enqueue time and reporting them alongside existing queue timing information to provide granular insights into queue behavior and potential performance bottlenecks. Implemented under commit af5f4412a1ed1e26982102fbfd3966a95eb3f959 (references #8242). This work strengthens end-to-end tracing, improves observability of queue-heavy workloads, and lays groundwork for targeted performance optimization with minimal surface-area changes and backward compatibility.
January 2025
November 2024
4 Commits • 2 Features
Nov 1, 2024In 2024-11, the DataDog/dd-trace-java team delivered major profiling enhancements and instrumentation robustness for the Java agent. Key features and fixes include a rate-limiting optimization for profiling data collection that applies after an event is committed, with a new Timing.sample() to sample based on committed events, and updates to QueueTimerHelper and DatadogProfiler to support accurate sampling. Instrumentation robustness was improved with paranoid exception handling when setting profiling thread context, enablement of SystemGC JFR events, and extended unwrapping support for LogExceptionRunnable to improve task instrumentation. Commit-level work includes 74760649c3967278ca82b30123c3aefc0a8fce38 (delay queue time rate limiting until event is committed), 99355a3b6a0753005a38690dbe3f3481003c1241 (paranoid exception handling when setting profiling thread context), 3a207fff3c2f5779f5317546933cb12ba1571902 (enable SystemGC events), and 047fabf42b1d6cf51d3fc41770fcfbb509b55d41 (unwrap LogExceptionRunnable). These changes reduced sampling noise, increased data fidelity, and improved production stability, delivering tangible business value through better observability and faster issue diagnosis.
November 2024
4 Commits • 2 Features
Nov 1, 2024In 2024-11, the DataDog/dd-trace-java team delivered major profiling enhancements and instrumentation robustness for the Java agent. Key features and fixes include a rate-limiting optimization for profiling data collection that applies after an event is committed, with a new Timing.sample() to sample based on committed events, and updates to QueueTimerHelper and DatadogProfiler to support accurate sampling. Instrumentation robustness was improved with paranoid exception handling when setting profiling thread context, enablement of SystemGC JFR events, and extended unwrapping support for LogExceptionRunnable to improve task instrumentation. Commit-level work includes 74760649c3967278ca82b30123c3aefc0a8fce38 (delay queue time rate limiting until event is committed), 99355a3b6a0753005a38690dbe3f3481003c1241 (paranoid exception handling when setting profiling thread context), 3a207fff3c2f5779f5317546933cb12ba1571902 (enable SystemGC events), and 047fabf42b1d6cf51d3fc41770fcfbb509b55d41 (unwrap LogExceptionRunnable). These changes reduced sampling noise, increased data fidelity, and improved production stability, delivering tangible business value through better observability and faster issue diagnosis.
Activity
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Quality Metrics
Correctness86.0%
Maintainability84.0%
Architecture80.0%
Performance76.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
GroovyJavaTOML
Technical Skills
Agent DevelopmentAgent InstrumentationConcurrencyException HandlingJFRJava DevelopmentJava ProfilingProfilingRate LimitingTesting
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