DataDog/dd-trace-py v2.15.0rc1

2.15.0rc1

on GitHub

Deprecation Notes

• Tracing
  • Deprecates the DD_TRACE_SAMPLE_RATE environment variable. It will be removed in 3.0.0. Use DD_TRACE_SAMPLING_RULES to configure sampling rates instead.
  • Deprecates DD_TRACE_API_VERSION=v0.3. Use v0.4 or v0.5 instead.

New Features

• CI Visibility
  • Adds the test_session.name tag to test events. The test session name can be set via the DD_TEST_SESSION_NAME environment variable. If DD_TEST_SESSION_NAME is not specified, the test session name is set from the CI job id and the test command.
• LLM Observability
  • Introduces prompt and name arguments to LLMObs.annotation_context to support setting an integration generated span's name and prompt field. For more information on annotation contexts, see docs.
  • LangChain streamed calls (llm.stream, chat_model.stream, and chain.stream) submit to LLM Observability.
  • langchain: Adds support for tracing stream calls on LCEL chains, chat completion models, or completion models. Note that due to an upstream issue with the langchain library itself, streamed responses will not be tagged correctly based on the choice index when the underlying model is configured to return n>1 choices. Please refer to this github issue for more details.
• Profiling
  • Introduces Code Origin for Span, a new feature that allows collecting information about where entry and exit spans have been created in the user code . This feature is disabled by default and can be enabled by setting the DD_CODE_ORIGIN_FOR_SPANS_ENABLED environment variable to true.
• Tracing
  • Adds DD_TRACE_HTTP_CLIENT_ERROR_STATUSES environment variable to configure the list of HTTP status codes that should be considered errors when instrumenting HTTP severs.
  • botocore: Adds span pointers for successful S3 CompleteMultipartUpload spans.
  • botocore: Adds span pointers for successful S3 CopyObject spans.

Bug Fixes

• Code Security

  • Always report a telemetry log error when an IAST propagation error raises, regardless of whether the _DD_IAST_DEBUG environment variable is enabled or not.
  • Ensures that only the IAST propagation context is cleared instead of all contexts, which could otherwise cause propagation loss in multithreaded applications. Additionally, it improves validations in both the Processor and Vulnerability Reporter, depending on whether IAST is active or not.

• LLM Observability

  • Resolves an issue where LLMObs.enable() did not patch google_generativeai library.
  • Resolves an issue where LLM Observability evaluation metrics were not being submitted in forked processes. The evaluation metric writer thread now automatically restarts when a forked process is detected.
  • The OpenAI, LangChain, Anthropic, Bedrock, and Gemini integrations now will handle and log errors during LLM Observability span processing to avoid disrupting user applications.

• Profiling

  • Improves the error message when the native exporter fails to load and stops profiling from starting if ddtrace is also being injected.
  • All files with platform-dependent code have had their filenames updated to reflect the platform they are for. This fixes issues where the wrong file would be used on a given platform.
  • Fixes endpoint profiling for stack v2 when DD_PROFILING_STACK_V2_ENABLED is set.
  • Enables code provenance when using libdatadog exporter with DD_PROFILING_EXPORT_LIBDD_ENABLED, DD_PROFILING_STACK_V2_ENABLED, or DD_PROFILING_TIMELINE_ENABLED.
  • Fixes an issue where flamegraph was upside down for stack v2 withDD_PROFILING_STACK_V2_ENABLED.
  • Fixes endpoint profiling when using libdatadog exporter, either with DD_PROFILING_EXPORT_LIBDD_ENABLED or DD_PROFILING_TIMELINE_ENABLED.

• Tracing

  • Removes a reference cycle that caused unnecessary garbage collection for top-level spans.
  • Ensures DD_TRACE_RATE_LIMIT environment variable is only applied to spans for which tracer sampling is configured. For spans not matching sampling rules default rate limits should be applied by the Datadog Agent.
  • celery: Fixes an issue where celery.apply spans didn't close if the after_task_publish or task_postrun signals didn't get sent when using apply_async, which can happen if there is an internal exception during the handling of the task. This update also marks the span as an error if an exception occurs.
  • celery: Fixes an issue where celery.apply spans using task_protocol 1 didn't close by improving the check for the task id in the body.

• Other

  • Updates import path in FastAPI module to use the new ASGI module location.