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2.19.0rc1

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@erikayasuda erikayasuda released this 20 Dec 20:56
v2.19.0rc1
315a48f
This commit was created on GitHub.com and signed with GitHub’s verified signature.
GPG key ID: B5690EEEBB952194
Learn about vigilant mode.

Upgrade Notes

  • Makes the library compatible with Python 3.13.
    • NOTE: Python 3.13 support is still in preview. Not all products may be fully compatible.

New Features

  • ASM

    • Introduces "Standalone SCA billing", opting out for APM billing and applying to only SCA. Enable this by setting these two environment variables: DD_APPSEC_SCA_ENABLED and DD_EXPERIMENTAL_APPSEC_STANDALONE_ENABLED

  • Code Security

    • Introduces stack trace reports for Code Security.

  • Profiling

    • Adds an experimental integration with the PyTorch profiler which can be enabled by setting DD_PROFILING_PYTORCH_ENABLED=true. This feature instruments the PyTorch profiler API so that GPU profiling data can be sent to Datadog for visualization. This feature supports torch version >= 1.8.1.

  • Tracing

    • azure_functions: Introduces support for Azure Functions.

Bug Fixes

  • ASM

    • Resolves an issue where AppSec was using a patched request and builtins functions, creating telemetry errors.

  • Lib-Injection

    • Fixes missing lib-injection telemetry for common abort scenarios.

  • LLM Observability

    • Resolves an issue where LLMObs.enable() ignored global patch configurations, specifically
      the DD_TRACE_<INTEGRATION>_ENABLED and DD_PATCH_MODULES environment variables.

  • Telemetry

    • Resolves deadlocks that could occur when sending instrumentation telemetry data after an unhandled exception is raised.

  • Tracing

    • datastreams: Logs at warning level for Kinesis errors that break the Data Streams Monitoring map.
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