profiling

This release addresses several critical bug fixes across various integrations and internal components, including memory leak resolutions and stability improvements for Python versions 3.9-3.12.3. It also resolves issues with span export, trace data handling, and LLM observability.

This release addresses several memory growth issues related to profiling and symbol database handling. It also resolves a span generation problem with OpenRouter requests when the OpenAI integration is active.

This release addresses several critical bug fixes related to application crashes in specific Python versions and potential memory growth issues during stack profiling.

This release includes several bug fixes across IAST, bootstrap, and profiling. Notably, it addresses false positives in IAST, improves compatibility with PyYAML consumers like Airflow, and resolves a crash in the profiling stack sampler.

This release introduces several new features for LLM Observability, including improved tracing, experiment evaluation, and Git metadata integration. It also enhances API security features for Flask, FastAPI, and Starlette, and improves database and Kafka monitoring capabilities.

This release focuses on stability and correctness, fixing critical bugs related to tracing duplication after forking and improving LLM observability by cleaning up metadata.

This release focuses on stability improvements, specifically addressing issues related to process forking in tracing and profiling components.

This release focuses on stability improvements, specifically addressing issues related to process forking in tracing and profiling components.

This release focuses on stability and data completeness, fixing several crashes related to interpreter teardown and profiling, and ensuring accurate runtime metrics collection on cgroup v2 systems.

This release focuses on stability and data integrity, fixing several bugs across LLM Observability, runtime metrics, IAST, profiling, and tracing components.

This release focuses on stability, addressing several crashes related to IAST, profiling, and pytest integration, while also improving runtime metric accuracy on cgroup v2 hosts.

This release introduces significant performance improvements to profiling via Cython compilation and adds extensive new features across MLFlow, AI Guard, Azure Durable Functions, and deep enhancements to LLM Observability, including Pydantic evaluation support and incremental experiment reporting. Process tags are now propagated across many components by default.

This release primarily addresses a bug fix related to greenlet behavior during profiling when using `gevent.joinall`.

This release focuses on stability, addressing critical bugs in Celery integration, Data Streams Monitoring auto-enabling, and gevent profiling interactions.

This release primarily addresses a stability issue in profiling by fixing a crash related to memory profiling during forking.

This release primarily focuses on bug fixes, addressing an evaluation error in dynamic instrumentation and a TypeError during profiling of subclassed locks.

This release focuses on bug fixes across CI Visibility and profiling modules, addressing issues related to code coverage instrumentation, uvloop/forking crashes, memory profiler loading, and asyncio dependency tracking.

This release primarily focuses on bug fixes, addressing a crash related to Ray job metadata and correcting the native extension module location for profiling builds.

This release focuses on several bug fixes across different components, including improved event deduplication in OpenFeature, resolution of API key parsing issues in OpenAI, and stability fixes in the profiler.