2.14.1

New Features

• Code Security (IAST): 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.

Bug Fixes

• tracing: Removes a reference cycle that caused unnecessary garbage collection for top-level spans.
• Code Security: fix potential memory leak on IAST exception handling.
• profiling: Fixes endpoint profiling when using libdatadog exporter, either with DD_PROFILING_EXPORT_LIBDD_ENABLED or DD_PROFILING_TIMELINE_ENABLED.

2.13.0

New Features

• Datastreams Monitoring (DSM): Adds support for schema tracking.
• Exception Replay will capture any exceptions that are manually attached to a span with a call to set_exc_info.
• LLM Observability: The LangChain integration now submits vectorstore similarity_search spans to LLM Observability as retrieval spans.
• langchain : Adds support for tracing tool invocations.
• LLM Observability: Adds support for capturing tool calls returned from LangChain chat completions.
• LLM Observability: Introduces the ability to set ml_app and timestamp_ms fields in LLMObs.submit_evaluation
• openai: Introduces model tag for openai integration metrics for consistency with the OpenAI SaaS Integration. It has the same value as openai.request.model.

Deprecation Notes

• tracing: All public patch modules are deprecated. The non-deprecated methods are included in the __all__ attribute.
• yaaredis: The yaaredis integration is deprecated and will be removed in a future version. As an alternative to the yaaredis integration, the redis integration should be used.
• tracing: Deprecates the priority_sampling argument in ddtrace.tracer.Tracer.configure(...).

Bug Fixes

• library injection: Resolves an issue where the version of attrs installed by default on some Ubuntu installations was treated as incompatible with library injection
• anthropic: Resolves an issue where attempting to tag non-JSON serializable request arguments caused a TypeError. The Anthropic integration now safely tags non-JSON serializable arguments with a default placeholder text.
• postgres: Fixes circular imports raised when psycopg automatic instrumentation is enabled.
• ASM: Resolves an issue where exploit prevention was not properly blocking requests with custom redirection actions.
• CI Visibility: Resolves an issue where exceptions other than timeouts and connection errors raised while fetching the list of skippable tests for ITR were not being handled correctly and caused the tracer to crash.
• CI Visibility: Fixes a bug where .git was incorrectly being stripped from repository URLs when extracting service names, resulting in g, i, or t being removed (eg: test-environment.git incorrectly becoming test-environmen)
• botocore: Resolves a regression where trace context was not being injected into the input of Stepfunction start_execution commands. This re-enables distributed tracing when a Python service invokes a properly instrumented Step Function.
• LLM Observability: Resolves an issue where custom trace filters were being overwritten in forked processes.
• LLM Observability: Resolves an issue where LLM Observability spans were not being submitted in forked processes, such as when using celery or gunicorn workers. The LLM Observability writer thread now automatically restarts when a forked process is detected.
• tracing: Fixes a side-effect issue with module import callbacks that could cause a runtime exception.
• tracing: Fixes an issue with some module imports with native specs that don't support attribute assignments, resulting in a TypeError exception at runtime.
• tracing: Improves the accuracy of X-Datadog-Trace-Count payload header.
• tracing: Resolves an issue where ddtrace package files were published with incorrect file attributes.
• tracing: Resolves an issue where django db instrumentation could fail.
• LLM Observability: Resolves an issue where session_id was being defaulted to trace_id, which was causing unexpected UI behavior.
• openai: Fixes a bug where asyncio.TimeoutErrors were not being propagated correctly from canceled OpenAI API requests.
• profiling: Propagates tags in DD_PROFILING_TAGS and DD_TAGS to the libdatadog exporter, a new exporter codepath which is enabled when either one of the following is set, DD_PROFILING_STACK_V2_ENABLED, DD_PROFILING_EXPORT_LIBDD_ENABLED, or DD_PROFILING_TIMELINE_ENABLED or dd-trace-py is running in an injected environment.
• ASM: Fixes a memory leak on the native slice aspect.

Other Changes

• tracing: Removes the DD_PRIORITY_SAMPLING configuration option. This option is not used in any ddtrace>=2.0 releases.

2.14.0

Deprecation Notes

• Tracing
  • Deprecates the DD_TRACE_SPAN_AGGREGATOR_RLOCK environment variable. It will be removed in v3.0.0.
  • Deprecates support for APM Legacy App Analytics. This feature and its associated configuration options are deprecated and will be removed in v3.0.0.
  • DD_HTTP_CLIENT_TAG_QUERY_STRING configuration is deprecated and will be removed in v3.0.0. Use DD_TRACE_HTTP_CLIENT_TAG_QUERY_STRING instead.

New Features

• DSM

  • Introduces new tracing and datastreams monitoring functionality for Avro Schemas.
  • Introduces new tracing and datastreams monitoring functionality for Google Protobuf.

• LLM Observability

  • Adds support to automatically submit Gemini Python SDK calls to LLM Observability.
  • The OpenAI integration now captures tool calls returned from streamed responses when making calls to the chat completions endpoint.
  • The LangChain integration now submits tool spans to LLM Observability.
  • LLM Observability spans generated by the OpenAI integration now have updated span name and model_provider values. Span names are now prefixed with the OpenAI client name (possible values: OpenAI/AzureOpenAI) instead of the default openai prefix to better differentiate whether the request was made to Azure OpenAI or OpenAI. The model_provider field also now corresponds to openai or azure_openai based on the OpenAI client.
  • The OpenAI integration now ensures accurate token data from streamed OpenAI completions and chat completions, if provided in the streamed response. To ensure accurate token data in the traced streamed operation, ensure that the stream_options={"include_usage": True} option is set on the completion or chat completion call.
  • Introduces the LLMObs.annotation_context() context manager method, which allows modifying the tags of integration generated LLM Observability spans created while the context manager is active.
  • Introduces prompt template annotation, which can be passed as an argument to LLMObs.annotate(prompt={...}) for LLM span kinds. For more information on prompt annotations, see the docs.
  • google_generativeai: Introduces tracing support for Google Gemini API generate_content calls.
    See the docs for more information.
  • openai: The OpenAI integration now includes a new openai.request.client tag with the possible values OpenAI/AzureOpenAI to help differentiate whether the request was made to Azure OpenAI or OpenAI.
  • openai: The OpenAI integration now captures token data from streamed completions and chat completions, if provided in the streamed response. To ensure accurate token data in the traced streamed operation, ensure that the stream_options={"include_usage": True} option is set on the completion or chat completion call.

• Profiling

  • Captures asyncio.Lock usages with with context managers.

• Other

  • botocore: Adds span pointers to some successful AWS botocore spans. Currently only supports S3 PutObject.
  • pymongo: Adds support for pymongo>=4.9.0

Bug Fixes

• Code Security (ASM)

  • Fixes a bug in the IAST patching process where AttributeError exceptions were being caught, interfering with the proper application cycle.
  • Resolves an issue where exploit prevention was not properly blocking requests with custom redirection actions.

• LLM Observability

  • Fixes an issue where the OpenAI and LangChain integrations would still submit integration metrics even in agentless mode. Integration metrics are now disabled if using agentless mode via LLMObs.enable(agentless_enabled=True) or setting DD_LLMOBS_AGENTLESS_ENABLED=1.
  • Resolves an issue in the LLMObs.annotate() method where non-JSON serializable arguments were discarded entirely. Now, the LLMObs.annotate() method safely handles non-JSON-serializable arguments by defaulting to a placeholder text.
  • Resolves an issue where attempting to tag non-JSON serializable request/response parameters resulted in a TypeError in the OpenAI, LangChain, Bedrock, and Anthropic integrations.
  • anthropic: Resolves an issue where attempting to tag non-JSON serializable request arguments caused a TypeError. The Anthropic integration now safely tags non-JSON serializable arguments with a default placeholder text.
  • langchain: Resolves an issue where attempting to tag non-JSON serializable tool config arguments resulted in a TypeError. The LangChain integration now safely tags non-JSON serializable arguments with a default placeholder text.

• Other

  • SSI: This fix ensures injection denylist is included in published OCI package.
  • postgres: Fixes circular imports raised when psycopg automatic instrumentation is enabled.
  • pymongo: Ensures instances of the pymongo.MongoClient can be patch after pymongo is imported.

2.14.0rc1

Deprecation Notes

• tracing: Deprecates the DD_TRACE_SPAN_AGGREGATOR_RLOCK environment variable. It will be removed in 3.0.0.
• tracing: Deprecates support for APM Legacy App Analytics. This feature and its associated configuration options are deprecated and will be removed in a future release.
• tracing: DD_HTTP_CLIENT_TAG_QUERY_STRING configuration is deprecated and will be removed in v3.0.0. Use DD_TRACE_HTTP_CLIENT_TAG_QUERY_STRING instead.

New Features

• google_generativeai: Introduces tracing support for Google Gemini API generate_content calls.
  See the docs for more information.

• LLM Observability: Adds support to automatically submit Gemini Python SDK calls to LLM Observability.

• LLM Observability: The OpenAI integration now captures tool calls returned from streamed responses when making calls to the chat completions endpoint.

• LLM Observability: The LangChain integration now submits tool spans to LLM Observability.

• openai: The OpenAI integration now includes a new openai.request.client tag with the possible values OpenAI/AzureOpenAI to help differentiate whether the request was made to Azure OpenAI or OpenAI.

• LLM Observability: LLM Observability spans generated by the OpenAI integration now have updated span name and model_provider values. Span names are now prefixed with the OpenAI client name (possible values: OpenAI/AzureOpenAI) instead of the default openai prefix to better differentiate whether the request was made to Azure OpenAI or OpenAI. The model_provider field also now corresponds to openai or azure_openai based on the OpenAI client.

• openai: The OpenAI integration now captures token data from streamed completions and chat completions, if provided in the streamed response. To ensure accurate token data in the traced streamed operation, ensure that the stream_options={"include_usage": True} option is set on the completion or chat completion call.

• LLM Observability: The OpenAI integration now ensures accurate token data from streamed OpenAI completions and chat completions, if provided in the streamed response. To ensure accurate token data in the traced streamed operation, ensure that the stream_options={"include_usage": True} option is set on the completion or chat completion call.

• DSM: Introduces new tracing and datastreams monitoring functionality for Avro Schemas.

• DSM: Introduces new tracing and datastreams monitoring functionality for Google Protobuf.

• LLM Observability: Introduces the LLMObs.annotation_context() context manager method which allows modifying the tags of integration generated LLM Observability spans created while the context manager is active.

• profiling: Captures asyncio.Lock usages with with context managers

• pymongo: Adds support for pymongo>=4.9.0

• botocore: Adds span pointers to some successful AWS botocore spans. Currently only supports S3 PutObject.

• LLM Observability: Introduces prompt template annotation, which can be passed as an argument to LLMObs.annotate(prompt={...}) for LLM span kinds. For more information on prompt annotations, see Annotating a Span.

Bug Fixes

• library injection: Resolves an issue where the version of attrs installed by default on some Ubuntu installations was treated as incompatible with library injection
• anthropic: Resolves an issue where attempting to tag non-JSON serializable request arguments caused a TypeError. The Anthropic integration now safely tags non-JSON serializable arguments with a default placeholder text.
• LLM Observability: Fixes an issue where the OpenAI and LangChain integrations would still submit integration metrics even in agentless mode. Integration metrics are now disabled if using agentless mode via LLMObs.enable(agentless_enabled=True) or setting DD_LLMOBS_AGENTLESS_ENABLED=1.
• LLM Observability: Resolves an issue in the LLMObs.annotate() method where non-JSON serializable arguments were discarded entirely. Now, the LLMObs.annotate() method safely handles non-JSON-serializable arguments by defaulting to a placeholder text.
• LLM Observability: Resolves an issue where attempting to tag non-JSON serializable request/response parameters resulted in a TypeError in the OpenAI, LangChain, Bedrock, and Anthropic integrations.
• langchain: Resolves an issue where attempting to tag non-JSON serializable tool config arguments resulted in a TypeError. The LangChain integration now safely tags non-JSON serializable arguments with a default placeholder text.
• SSI: This fix ensures injection denylist is included in published OCI package.
• postgres: Fixes circular imports raised when psycopg automatic instrumentation is enabled.
• ASM: This fix resolves an issue where exploit prevention was not properly blocking requests with custom redirection actions.
• Code Security: This fixes a bug in the IAST patching process where AttributeError exceptions were being caught, interfering with the proper application cycle.
• kafka: Fixes an issue where a TypeError exception would be raised if the first message's topic() returned None during consumption.
• kinesis: Resolves an issue where unparsable data in a Kinesis record would cause a NoneType error.
• pymongo: Ensures instances of the pymongo.MongoClient can be patch after pymongo is imported.

2.12.2

Bug Fixes

• library injection: Resolves an issue where the version of attrs installed by default on some Ubuntu installations was treated as incompatible with library injection
• Code Security: This fixes a bug in the IAST patching process where AttributeError exceptions were being caught, interfering with the proper application cycle.

2.11.6

Bug Fixes

• library injection: Resolves an issue where the version of attrs installed by default on some Ubuntu installations was treated as incompatible with library injection
• Code Security: This fixes a bug in the IAST patching process where AttributeError exceptions were being caught, interfering with the proper application cycle.

2.12.1

Bug Fixes

• SSI: This fix ensures injection denylist is included in published OCI package.

2.11.5

Bug Fixes

• SSI: This fix ensures injection denylist is included in published OCI package.

2.13.0rc1

Deprecation Notes

• tracing: All public patch modules are deprecated. The non-deprecated methods are included in the __all__ attribute.
• yaaredis: The yaaredis integration is deprecated and will be removed in a future version. As an alternative to the yaaredis integration, the redis integration should be used.
• tracing: Deprecates the priority_sampling argument in ddtrace.tracer.Tracer.configure(...).

New Features

• Datastreams Monitoring (DSM): Adds support for schema tracking.
• debugging: Exception Replay will capture any exceptions that are manually attached to a span with a call to set_exc_info.
• LLM Observability: The LangChain integration now submits vectorstore similarity_search spans to LLM Observability as retrieval spans.
• langchain : Adds support for tracing tool invocations.
• LLM Observability: Adds support for capturing tool calls returned from LangChain chat completions.
• LLM Observability: Introduces the ability to set ml_app and timestamp_ms fields in LLMObs.submit_evaluation.
• openai: Introduces model tag for openai integration metrics for consistency with the OpenAI SaaS Integration. It has the same value as openai.request.model.

Bug Fixes

• CI Visibility: Resolves an issue where exceptions other than timeouts and connection errors raised while fetching the list of skippable tests for ITR were not being handled correctly and caused the tracer to crash.

• CI Visibility: Fixes a bug where .git was incorrectly being stripped from repository URLs when extracting service names, resulting in g, i, or t being removed (eg: test-environment.git incorrectly becoming test-environmen)

• botocore: Resolves a regression where trace context was not being injected into the input of Stepfunction start_execution commands. This re-enables distributed tracing when a Python service invokes a properly instrumented Step Function.

• LLM Observability: Resolves an issue where custom trace filters were being overwritten in forked processes.

• LLM Observability: Resolves an issue where LLM Observability spans were not being submitted in forked processes, such as when using celery or gunicorn workers. The LLM Observability writer thread now automatically restarts when a forked process is detected.

• tracing: Fix for a side-effect issue with module import callbacks that could cause a runtime exception.

• tracing: Fixes an issue with some module imports with native specs that don't support attribute assignments, resulting in a TypeError exception at runtime.

• tracing: Improves the accuracy of X-Datadog-Trace-Count payload header.

• tracing: Resolves an issue where ddtrace package files were published with incorrect file attributes.

• tracing: Resolves an issue where django db instrumentation could fail.

• LLM Observability: Resolves an issue where session_id was being defaulted to trace_id, which was causing unexpected UI behavior.

• openai: Fixes a bug where asyncio.TimeoutErrors were not being propagated correctly from canceled OpenAI API requests.

• profiling: Propagates tags in DD_PROFILING_TAGS and DD_TAGS to the libdatadog exporter, new exporter codepath which is enabled when either one of the following is set, DD_PROFILING_STACK_V2_ENABLED, DD_PROFILING_EXPORT_LIBDD_ENABLED, or DD_PROFILING_TIMELINE_ENABLED or dd-trace-py is running in an injected environment.

• Security: Fix a memory leak on the native slice aspect.

Other Changes

• tracing: Removes the DD_PRIORITY_SAMPLING configuration option. This option is not used in any ddtrace>=2.0 releases.

2.12.0

New Features

• openai: Introduces the model tag for openai integration metrics for consistency with the OpenAI SaaS Integration. It has the same value as openai.request.model.
• database_clients: Adds server.address tag to all <database>.query spans (ex: postgres.query). This tag stores the name of the database host.
• LLM Observability: Flushes the buffer of spans to be sent when the payload size would otherwise exceed the payload size limit for the event platform.
• LLM Observability: Span events that exceed the event platform event size limit (1 MB) will now have their inputs and outputs dropped.
• tracing: Adds ddtrace.trace.Context to the public api. This class can now be used to propagate context across execution boundaries (ex: threads).

Deprecation Notes

• config: DD_TRACE_128_BIT_TRACEID_LOGGING_ENABLED is deprecated. Trace id logging format is now configured automatically.
• tracing: Deprecates all modules in the ddtrace.contrib.[integration_name] package. Use attributes exposed in ddtrace.contrib.[integration_name].__all__ instead. The following are impacted:
  • aioredis, algoliasearch. anthropic, aredis, asgi, asyncpg, aws_lambda, boto, botocore, bottle, cassandra, celery, cherrypy, consul, coverage, django, dogpile_cache, dramatiq, elasticsearch, falcon, fastapi, flask, flask_cache, futures, gevent, graphql, grpc, httplib, httpx, jinja2, kafka, kombu, langchain, logbook, logging, loguru, mako, mariadb, molten, mongoengine, mysql, mysqldb, openai, psycopg, pylibmc, pymemcache, pymongo, pymysql, pynamodb, pyodbc, pyramid, redis, rediscluster, requests, sanic, snowflake, sqlalchemy, sqlite3, starlette, structlog, subprocess, tornado, urllib, urllib3, vertica, webbrowser, wsgi, yaaredis

Bug Fixes

• CI Visibility: Resolves an issue where exceptions other than timeouts and connection errors raised while fetching the list of skippable tests for ITR were not being handled correctly and caused the tracer to crash.

• CI Visibility: Fixes a bug where .git was incorrectly being stripped from repository URLs when extracting service names, resulting in g, i, or t being removed (eg: test-environment.git incorrectly becoming test-environmen)

• LLM Observability: Resolves an issue where custom trace filters were being overwritten in forked processes.

• tracing: Fixes a side-effect issue with module import callbacks that could cause a runtime exception.

• LLM Observability: Resolves an issue where session_id was being defaulted to trace_id, which was causing unexpected UI behavior.

• LLM Observability: Resolves an issue where LLM Observability spans were not being submitted in forked processes, such as when using celery or gunicorn workers. The LLM Observability writer thread now automatically restarts when a forked process is detected.

• tracing: Fixes an issue with some module imports with native specs that don't support attribute assignments, resulting in a TypeError exception at runtime.

• tracing: Resolves an issue where ddtrace package files were published with incorrect file attributes.

• tracing: Resolves an issue where django db instrumentation could fail.

• openai: Fixes a bug where asyncio.TimeoutErrors were not being propagated correctly from canceled OpenAI API requests.

• aiobotocore: Fixes an issue where the _make_api_call arguments were not captured correctly when using keyword arguments.

• tracing(django): Resolves a bug where ddtrace was exhausting a Django stream response before returning it to user.

• LLM Observability: Fixes an issue in the OpenAI integration where integration metrics would still be submitted even if LLMObs.enable(agentless_enabled=True) was set.

• internal: Fixes the Already mutably borrowed error when rate limiter is accessed across threads.

• internal: Fixes the Already mutably borrowed error by reverting back to pure-python rate limiter.

• Code Security: Adds null pointer checks when creating new objects ids.

• profiling: Fixes an issue where the profiler could erroneously try to load protobuf in autoinjected environments, where it is not available.

• crashtracking: Fixes an issue where crashtracking environment variables for Python were inconsistent with those used by other runtimes.

• profiling: Fixes endpoint profiling for stack v2 when DD_PROFILING_STACK_V2_ENABLED is set.

• profiling: Turns on the new native exporter when DD_PROFILING_TIMELINE_ENABLED=True is set.