ddtrace 4.7.0rc1

on Python PyPI

Estimated end-of-life date, accurate to within three months: 05-2027
See the support level definitions for more information.

New Features

• mlflow

  • Adds a request header provider (auth plugin) for MLFlow. If the environment variables DD_API_KEY, DD_APP_KEY and DD_MODEL_LAB_ENABLED are set, HTTP requests to the MLFlow tracking server will include the DD-API-KEY and DD-APPLICATION-KEY headers. #16685

• AI Guard

  • Calls to evaluate now block if blocking was enabled for the service in the AI Guard UI. This behavior can be disabled by passing the parameter block=False, which now defaults to block=True.
  • This updates the AI Guard API client to return Sensitive Data Scanner (SDS) results in the SDK response.
  • This introduces AI Guard support for Strands Agents. The Plugin API requires
    strands-agents>=1.29.0; the HookProvider works with any version that exposes the hooks system.

• azure_durable_functions

  • Add tracing support for Azure Durable Functions. This integration traces durable activity and entity functions.

• profiling

  • This adds process tags to profiler payloads. To deactivate this feature, set DD_EXPERIMENTAL_PROPAGATE_PROCESS_TAGS_ENABLED=false.

• runtime metrics

  • This adds process tags to runtime metrics tags. To deactivate this feature, set DD_EXPERIMENTAL_PROPAGATE_PROCESS_TAGS_ENABLED=false.

• remote configuration

  • This adds process tags to remote configuration payloads. To deactivate this feature, set DD_EXPERIMENTAL_PROPAGATE_PROCESS_TAGS_ENABLED=false.

• dynamic instrumentation

  • This adds process tags to debugger payloads. To deactivate this feature, set DD_EXPERIMENTAL_PROPAGATE_PROCESS_TAGS_ENABLED=false.

• crashtracking

  • This adds process tags to crash tracking payloads. To deactivate this feature, set DD_EXPERIMENTAL_PROPAGATE_PROCESS_TAGS_ENABLED=false.

• data streams monitoring

  • This adds process tags to Data Streams Monitoring payloads. To deactivate this feature, set DD_EXPERIMENTAL_PROPAGATE_PROCESS_TAGS_ENABLED=false.

• database monitoring

  • This adds process tags to Database Monitoring SQL service hash propagation. To deactivate this feature, set DD_EXPERIMENTAL_PROPAGATE_PROCESS_TAGS_ENABLED=false.

• Stats computation

  • This adds process tags to stats computation payloads. To deactivate this feature, set DD_EXPERIMENTAL_PROPAGATE_PROCESS_TAGS_ENABLED=false.

• LLM Observability

  • Experiment tasks can now optionally receive dataset record metadata as a third metadata parameter. Tasks with the existing (input_data, config) signature continue to work unchanged.
  • This introduces RemoteEvaluator which allows users to reference LLM-as-Judge evaluations configured in the Datadog UI by name when running local experiments. For more information, see the documentation: https://docs.datadoghq.com/llm_observability/guide/evaluation_developer_guide/#using-managed-evaluators
  • This adds cache creation breakdown metrics for the Anthropic integration. When making Anthropic calls with prompt caching, ephemeral_5m_input_tokens and ephemeral_1h_input_tokens metrics are now reported, distinguishing between 5 minute and 1 hour prompt caches.
  • Adds support for reasoning and extended thinking content in Anthropic, LiteLLM, and OpenAI-compatible integrations. Anthropic thinking blocks (type: "thinking") are now captured as role: "reasoning" messages in both streaming and non-streaming responses, as well as in input messages for tool use continuations. LiteLLM now extracts reasoning_output_tokens from completion_tokens_details and captures reasoning_content in output messages for OpenAI-compatible providers.

• tracer

  • This introduces API endpoint discovery support for Tornado applications. HTTP endpoints are now automatically collected at application startup and reported via telemetry, bringing Tornado in line with Flask, FastAPI, and Django.
  • This adds process tags to trace payloads. To deactivate this feature, set DD_EXPERIMENTAL_PROPAGATE_PROCESS_TAGS_ENABLED=false.

Bug Fixes

• CI Visibility
  • Fixes an issue where pytest plugins pytest-rerunfailures and flaky were silently overridden by the ddtrace plugin. With this change, external rerun plugins will now drive retries as expected when Auto Test Retries and Early Flake Detection features are both disabled, otherwise our retry mechanism takes precedence and a warning is emitted.
  • pytest:
    • Fixed missing ITR tags in the new pytest plugin that caused time saved by Test Impact Analysis to not appear in dashboards.
• tracing
  • Resolves an issue where a RuntimeError could be raised when iterating over the context._meta dictionary while creating spans or generating distributed traces.
  • fixes an issue where telemetry debug mode was incorrectly enabled by DD_TRACE_DEBUG instead of its own dedicated environment variable DD_INTERNAL_TELEMETRY_DEBUG_ENABLED. Setting DD_TRACE_DEBUG=true no longer enables telemetry debug mode. To enable telemetry debug mode, set DD_INTERNAL_TELEMETRY_DEBUG_ENABLED=true.
• LLM Observability
  • This fix resolves an issue where cache_creation_input_tokens and cache_read_input_tokens were not captured when using the LiteLLM integration with providers that support prompt caching (e.g., Anthropic, OpenAI, Deepseek).
• profiling
  • Fixes an issue where enabling the profiler with gevent workers caused gunicorn to skip graceful shutdown, killing in-flight requests immediately on SIGTERM instead of honoring --graceful-timeout. #16424
  • Fix potential reentrant crashes in the memory profiler by avoiding object allocations and frees during stack unwinding inside the allocator hook. #16661
  • the Profiler now correctly flushes profiles at most once per upload interval.
  • Fixes an AttributeError crash that occurred when the lock profiler or stack profiler encountered _DummyThread instances. _DummyThread lacks the _native_id attribute, so accessing native_id raises AttributeError. The profiler now falls back to using the thread identifier when native_id is unavailable.
  • Lock acquire samples are now only recorded if the acquire call was successful.
• Fix for potential crashes at process shutdown due to incorrect detection of the VM finalization state when stopping periodic worker threads.