chore(deps): update submissions

[renovate]

This PR contains the following updates:

Package	Change	Age	Adoption	Passing	Confidence	Type	Update
anndata	==0.10.8 -> ==0.10.9						patch
ddtrace (changelog)	==2.1.4 -> ==2.14.2						minor
numba	==0.59.1 -> ==0.60.0						minor
numpy (source, changelog)	<2 -> <3						major
public.ecr.aws/lambda/python	3.8 -> 3.12					final	minor
public.ecr.aws/lambda/python	3.9 -> 3.12					final	minor
pyvips	==2.2.2 -> ==2.2.3						patch
s3fs	==0.4.2 -> ==2024.9.0						major
scanpy	==1.9.8 -> ==1.10.3						minor
tiledb	==0.25.0 -> ==0.32.3						minor

---

Release Notes

scverse/anndata (anndata)

v0.10.9

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DataDog/dd-trace-py (ddtrace)

v2.14.2

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Bug Fixes

• Tracing

  • 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.

• Profiling

  • 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.
  • Enables code provenance when using libdatadog exporter, 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, DD_PROFILING_STACK_V2_ENABLED.

v2.14.1

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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.

v2.14.0

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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

v2.13.1

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Bug Fixes

• 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.
  • Code Security: Fixes potential memory leak on IAST exception handling.

• Profiling:

  • Updates filenames for all files with platform-dependent code to reflect the platform they are for. This fixes issues where the wrong file would be used on a given platform.
  • Enables endpoint profiling for stack v2, DD_PROFILING_STACK_V2_ENABLED is set.
  • Fixes endpoint profiling when using libdatadog exporter, either with DD_PROFILING_EXPORT_LIBDD_ENABLED or DD_PROFILING_TIMELINE_ENABLED.
  • Enables code provenance when using libdatadog exporter, DD_PROFILING_EXPORT_LIBDD_ENABLED, DD_PROFILING_STACK_V2_ENABLED, or DD_PROFILING_TIMELINE_ENABLED.
  • Fixes an issue where the flamegraph was upside down for stack v2 when enabling DD_PROFILING_STACK_V2_ENABLED.

• Tracing

  • 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.
  • 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.
  • Removes a reference cycle that caused unnecessary garbage collection for top-level spans.

---

v2.13.0: 2.13.0

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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.

v2.12.3

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Bug Fixes

• Code Security

  • This fix resolves an issue where exploit prevention was not properly blocking requests with custom redirection actions.
  • Ensure the Initializer object is always reset and freed before the Python runtime.

• 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.
  • 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.
  • 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.

• Profiling

  • 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.
  • Improves the error message when the native exporter fails to load and stops profiling from starting if ddtrace is also being injected.
  • Enables endpoint profiling for stack v2, DD_PROFILING_STACK_V2_ENABLED is set.
  • Fixes endpoint profiling when using libdatadog exporter, either with DD_PROFILING_EXPORT_LIBDD_ENABLED or DD_PROFILING_TIMELINE_ENABLED.
  • Enables code provenance when using libdatadog exporter, 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, DD_PROFILING_STACK_V2_ENABLED.

• Tracing

  • 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.
  • 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.
  • Fixes circular imports raised when psycopg automatic instrumentation is enabled.
  • Removes a reference cycle that caused unnecessary garbage collection for top-level spans.
  • Fixed 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.

---

v2.12.2: 2.12.2

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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.

v2.12.1: 2.12.1

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Bug Fixes

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

v2.12.0

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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.

---

v2.11.6

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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.

---

v2.11.5

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Bug Fixes

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

---

v2.11.4

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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.

---

v2.11.3: 2.11.3

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Bug Fixes

• ASM: Improves internal stability for the new fingerprinting feature.

v2.11.2: 2.11.2

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New Features

• 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

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

v2.11.1

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Bug Fixes

• tracing(django): This fix resolves a bug where ddtrace was exhausting a Django stream response before returning it to user.
• Fixed an issue with some module imports with native specs that don't support attribute assignments, resulting in a TypeError exception at runtime.
• internal: Fix Already mutably borrowed error by reverting back to pure-python rate limiter.
• This fix resolves an issue where ddtrace package files were published with incorrect file attributes.
• profiling: Fixes an issue where the profiler could erroneously try to load protobuf in autoinjected environments, where it is not available.
• Fixes an issue where crashtracking environment variables for Python were inconsistent with those used by other runtimes.
• profiling: Fixes endpoing profiling for stack v2, that is when DD_PROFILING_STACK_V2_ENABLED set.

---

v2.11.0

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New Features

• ASM: This update introduces new Auto User Events support.

  ASM’s [Account TakeOver (ATO) detection](https://docs.datadoghq.com/security/account_takeover_protection) is now automatically monitoring [all compatible user authentication frameworks](https://docs.datadoghq.com/security/application_security/enabling/compatibility/) to detect attempted or leaked user credentials during an ATO campaign.

  To do so, the monitoring of the user activity is extended to now collect all forms of user IDs, including non-numerical forms such as usernames or emails. This is configurable with 3 different working modes: identification to send the user IDs in clear text; anonymization to send anonymized user IDs; or disabled to completely turn off any type of user ID collection (which leads to the disablement of the ATO detection).

  The default collection mode being used is identification and this is configurable in your remote service configuration settings in the [service catalog]( https://app.datadog.com/security/appsec/inventory/services?tab=capabilities) (clicking on a service), or with the service environment variable DD_APPSEC_AUTO_USER_INSTRUMENTATION_MODE.

  You can read more [here](https://docs.datadoghq.com/security/account_takeover_protection).

  New local configuration environment variables include:

  • `DD_APPSEC_AUTOMATED_USER_EVENTS_TRACKING_ENABLED`: Can be set to "true"/"1" (default if missing) or "false"/"0" (default if set to any other value). If set to false, the feature is completely disabled. If enabled, the feature is active.
  • `DD_APPSEC_AUTO_USER_INSTRUMENTATION_MODE`: Can be set to "identification" (default if missing), "anonymization", or "disabled" (default if the environment variable is set to any other value). The values can be modified via remote configuration if the feature is active. If set to "disabled", user events are not collected. Otherwise, user events are collected, using either plain text user_id (in identification mode) or hashed user_id (in anonymization mode).

  Additionally, an optional argument for the public API track_user_login_success_event and `track_user_login_failure_event`: login_events_mode="auto". This allows manual instrumentation to follow remote configuration settings, enabling or disabling manual instrumentation with a single remote action on the Datadog UI.

  Also prevents non numerical user ids to be reported by default without user instrumentation in Django.

• Anthropic: Adds support for tracing message calls using tools.

• LLM Observability: Adds support for tracing Anthropic messages using tool calls.

• botocore: Adds support for overriding the default service name in botocore by either setting the environment variable DD_BOTOCORE_SERVICE or configuring it via ddtrace.config.botocore["service"].

• azure: Removes the restrictions on the tracer to only run the mini-agent on the consumption plan. The mini-agent now runs regardless of the hosting plan

• ASM: Adds Threat Monitoring support for gRPC.

• Code Security: add propagation for GRPC server sources.

• LLM Observability: This introduces improved support for capturing tool call responses from the OpenAI and Anthropic integrations.

• LLM Observability: This introduces the agentless mode configuration for LLM Observability. To enable agentless mode, set the environment variable DD_LLMOBS_AGENTLESS_ENABLED=1, or use the enable option LLMObs.enable(agentless_enabled=True).

• LLM Observability: Function decorators now support tracing asynchronous functions.

• LLM Observability: This introduces automatic input/output annotation for task/tool/workflow/agent/retrieval spans traced by function decorators. Note that manual annotations for input/output values will override automatic annotations.

• LLM Observability: The OpenAI integration now submits embedding spans to LLM Observability.

• LLM Observability: All OpenAI model parameters specified in a completion/chat completion request are now captured.

• LLM Observability: This changes OpenAI-generated LLM Observability span names from openai.request to openai.createCompletion, openai.createChatCompletion, and openai.createEmbedding for completions, chat completions, and embeddings spans, respectively.

• LLM Observability: This introduces the agent proxy mode for LLM Observability. By default, LLM Observability spans will be sent to the Datadog agent and then forwarded to LLM Observability. To continue submitting data directly to LLM Observability without the Datadog agent, set DD_LLMOBS_AGENTLESS_ENABLED=1 or set programmatically using LLMObs.enable(agentless_enabled=True).

• LLM Observability: The Langchain integration now submits embedding spans to LLM Observability.

• LLM Observability: The LLMObs.annotate() method now replaces non-JSON serializable values with a placeholder string [Unserializable object: <string representation of object>] instead of rejecting the annotation entirely.

• pylibmc: adds traces for memcached add command

• ASM: This introduces fingerprinting with libddwaf 1.19.1

• Database Monitoring: Adds Database Monitoring (DBM) trace propagation for postgres databases used through Django.

• langchain: Tags tool calls on chat completions.

• LLM Observability: Adds retry logic to the agentless span writer to mitigate potential networking issues, like timeouts or dropped connections.

• ASM: This introduces Command Injection support for Exploit Prevention on os.system only.

• ASM: This introduces suspicious attacker blocking with libddwaf 1.19.1

Upgrade Notes

• ASM: This upgrade prevents the WAF from being invoked for exploit prevention if the corresponding rules are not enabled via remote configuration.

Deprecation Notes

• ASM: The environment variable DD_APPSEC_AUTOMATED_USER_EVENTS_TRACKING is deprecated and will be removed in the next major release. Instead of DD_APPSEC_AUTOMATED_USER_EVENTS_TRACKING, you should use DD_APPSEC_AUTO_USER_INSTRUMENTATION_MODE. The "safe" and "extended" modes are deprecated and have been replaced by "anonymization" and "identification", respectively.
• botocore: All methods in botocore/patch.py except patch() and unpatch() are deprecated and will be removed in version 3.0.0.
• consul: All methods in consul/patch.py except patch() and unpatch() are deprecated and will be removed in version 3.0.0.
• psycopg: All methods in psycopg/patch.py except patch() and unpatch() are deprecated and will be removed in version 3.0.0.
• pylibmc: All methods in pylibmc/patch.py except patch() and unpatch() are deprecated and will be removed in version 3.0.0.
• pymemcache: All methods in pymemcache/patch.py except patch() and unpatch() are deprecated and will be removed in version 3.0.0.
• pymongo: All methods in pymongo/patch.py except patch() and unpatch() are deprecated and will be removed in version 3.0.0.
• pymysql: All methods in pymysql/patch.py except patch() and unpatch() are deprecated and will be removed in version 3.0.0.
• pynamodb: All methods in pynamodb/patch.py except patch() and unpatch() are deprecated and will be removed in version 3.0.0.
• pyodbc: All methods in pyodbc/patch.py except patch() and unpatch() are deprecated and will be removed in version 3.0.0.
• pyramid: All methods in pyramid/patch.py except patch() and unpatch() are deprecated and will be removed in version 3.0.0.
• exception replay: The DD_EXCEPTION_DEBUGGING_ENABLED environment variable has been deprecated in favor of DD_EXCEPTION_REPLAY_ENABLED. The old environment variable will be removed in a future major release.
• ASM: This removes the partial auto instrumentation of flask login. It was giving only partial and possibly confusing picture of the login activity. We recommend customers to switch to [manual instrumentation](https://docs.datadoghq.com/security/application_security/threats/add-user-info/?tab=loginsuccess&code-lang=python#adding-business-logic-information-login-success-login-failure-any-business-logic-to-traces).

Bug Fixes

• 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.

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

• Code Security: add encodings.idna to the IAST patching denylist to avoid problems with gevent.

• Code Security: add the boto package to the IAST patching denylist.

• Code Security: fix two small memory leaks with Python 3.11 and 3.12.

• CI Visibility: Fixes an issue where the pytest plugin would crash if the git binary was absent

• CI Visibility: fixes incorrect URL for telemetry intake in EU that was causing missing telemetry data and SSL error log messages.

• celery: changes error.message span tag to no longer include the traceback that is already included in the error.stack span tag.

• CI Visibility: fixes source file information that would be incorrect in certain decorated / wrapped scenarios and forces paths to be relative to the repository root, if present.

• futures: Fixes inconsistent behavior with concurrent.futures.ThreadPoolExecutor context propagation by passing the current trace context instead of the currently active span to tasks. This prevents edge cases of disconnected spans when the task executes after the parent span has finished.

• kafka: Fixes ArgumentError raised when injecting span context into non-existent Kafka message headers.

• botocore: Fixes Botocore Kinesis span parenting to use active trace context if a propagated child context is not found instead of empty context.

• langchain: This fix resolves an issue where the wrong langchain class name was being used to check for Pinecone vectorstore instances.

• LLM Observability: This resolves a typing hint error in the ddtrace.llmobs.utils.Documents helper class constructor where type hints did not accept input dictionaries with integer or float values.

• LLM Observability: This fix resolves an issue where the OpenAI, Anthropic, and AWS Bedrock integrations were always setting temperature and max_tokens parameters to LLM invocations. The OpenAI integration in particular was setting the wrong temperature default values. These parameters are now only set if provided in the request.

• opentelemetry: Resolves circular imports raised by the OpenTelemetry API when the ddcontextvars_context entrypoint is loaded. This resolves an incompatibility introduced in opentelemetry-api==1.25.0.

• opentelemetry: Resolves an issue where the get_tracer function would raise a TypeError when called with the attribute argument. This resolves an incompatibility introduced in opentelemetry-api==1.26.0.

• psycopg: Ensures traced async cursors return an asynchronous iterator object.

• redis: This fix resolves an issue in the redis exception handling where an UnboundLocalError was raised instead of the expected BaseException.

• ASM: This fix resolves an issue where the requests integration would not propagate when apm is opted out (i.e. in ASM Standalone).

• profiling: Fixes an issue where task information coming from echion was encoded improperly, which could segfault the application.

• tracing: fixes a potential crash where using partial flushes and tracer.configure() could result in an IndexError

• tracer: This fix resolves an issue where the tracer was not starting properly on a read-only file system.

• internal: fixes an issue where some pathlib functions return OSError on Windows.

• ASM: This fix resolves an issue where the WAF could be disabled if the ASM_DD rule file was not found in Remote Config.

• flask: Fix scenarios when using flask-like frameworks would cause a crash because of patching issues on startup.

• Code Security: Logs warning instead of throwing an exception in the native module if IAST is not enabled by env var.

• Code Security: fix potential infinite loop with path traversal when the analyze quota has been exceeded.

• wsgi: Ensures the status of wsgi Spans are not set to error when a StopIteration exception is raised marked the span as an error. With this change, StopIteration exceptions in this context will be ignored.

• langchain: tag non-dict inputs to LCEL chains appropriately. Non-dict inputs are stringified, and dict inputs are tagged by key-value pairs.

• tracing: Updates DD_HEADER_TAGS and DD_TAGS to support the following formats: key1,key2,key3, key1:val,key2:val,key3:val3, key1:val key2:val key3:val3, and key1 key2 key3. Key value pairs that do not match an expected format will be logged and ignored by the tracer.

• loguru: This fix avoids copying attributes from a log record's "extras" field to the record's top level if those attributes were not added by the Datadog integration.

• opentelemetry: Resolves an edge case where distributed tracing headers could be generated before a sampling decision is made, resulting in dropped spans in downstream services.

• profiling: captures lock usages with with context managers, e.g. with lock:

• profiling: propagates runtime_id tag to libdatadog exporter. It is a unique string identifier for the profiled process. For example, Thread Timeline visualization uses it to distinguish different processes.

• profiling: show lock init location in Lock Name and hide profiler internal frames from Stack Frame in Timeline Details tab.

• ASM: This fix resolves an issue where ASM one click feature could fail to deactivate ASM.

• redis: This fix resolves an issue in redis utils where a variable may not be declared within a try/catch

Other Changes

• LLM Observability: the SDK allowed users to submit an unsupported numerical evaluation metric type. All evaluation metric types submitted with numerical type will now be automatically converted to a score type. As an alternative to using the numerical type, use `score instead.
• LLM Observability: LLMObs.submit_evaluation() requires a Datadog API key to send custom evaluations to LLM Observability. If an API key is not set using either DD_API_KEY or LLMObs.enable(api_key="<api-key>"), this method will log a warning and return None.

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v2.10.7

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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)
• openai: Fixes a bug where asyncio.TimeoutErrors were not being propagated correctly from canceled OpenAI API requests.
• profiling: Fixes endpoing profiling for stack v2 when DD_PROFILING_STACK_V2_ENABLED is set.

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v2.10.6

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Bug Fixes

• tracing(django): Resolves a bug where ddtrace was exhausting a Django stream response before returning it to user.
• internal: Fixes Already mutably borrowed error by reverting back to pure-python rate limiter.

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v2.10.5: 2.10.5

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Bug Fixes

• internal: Fix for Already mutably borrowed error when rate limiter is accessed across threads.
• Code Security: add null pointer checks when creating new objects ids.
• profiling: turns on the new native exporter when DD_PROFILING_TIMELINE_ENABLED is set.

v2.10.4

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Bug Fixes

• SSI: Fixes incorrect file permissions on lib-injection images.
• profiling: Shows lock init location in Lock Name and hides profiler internal frames from Stack Frame in Timeline Details tab.

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v2.10.3

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Bug Fixes

• ASM: This fix resolves an issue where the WAF could be disabled if the ASM_DD rule file was not found in Remote Config.
• CI Visibility: Fixes an issue where the pytest plugin would crash if the git binary was absent
• CI Visibility: Fixes incorrect URL for telemetry intake in EU that was causing missing telemetry data and SSL error log messages.
• Code Security: Add encodings.idna to the IAST patching denylist to avoid problems with gevent.
• internal: Fixes an issue where some pathlib functions return OSError on Windows.
• opentelemetry: Resolves an edge case where distributed tracing headers could be generated before a sampling decision is made, resulting in dropped spans in downstream services.

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v2.10.2

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Bug Fixes

• lib-injection: This fix resolves an issue with docker layer caching and the final lib-injection image size.
• psycopg: Ensures traced async cursors return an asynchronous iterator object.
• tracer: This fix resolves an issue where the tracer was not starting properly on a read-only file system.
• Code Security: fix potential infinite loop with path traversal when the analyze quota has been exceeded.
• profiling: captures lock usages with with context managers, e.g. with lock:
• profiling: propagates runtime_id tag to libdatadog exporter. It is a unique string identifier for the profiled process. For example, Thread Timeline visualization uses it to distinguish different processes.

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v2.10.1

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Bug Fixes

• langchain: This fix resolves an issue where the wrong langchain class name was being used to check for Pinecone vectorstore instances.
• opentelemetry: Resolves circular imports raised by the OpenTelemetry API when the ddcontextvars_context entrypoint is loaded. This resolves an incompatibility introduced in opentelemetry-api==1.25.0.
• opentelemetry: Resolves an issue where the get_tracer function would raise a TypeError when called with the attribute argument. This resolves an incompatibility introduced in opentelemetry-api==1.26.0.
• ASM: This fix resolves an issue where ASM one click feature could fail to deactivate ASM.

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v2.10.0

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New Features

• botocore: Adds support for overriding the default service name in botocore by either setting the environment variable DD_BOTOCORE_SERVICE or configuring it via ddtrace.config.botocore["service"].

• Database Monitoring: Adds Database Monitoring (DBM) trace propagation for postgres databases used through Django.

• Anthropic: Adds support for tracing message calls using tools.

• LLM Observability: Adds support for tracing Anthropic messages using tool calls.

• azure: Removes the restrictions on the tracer to only run the mini-agent on the consumption plan. The mini-agent now runs regardless of the hosting plan

• Anthropic: Adds support for tracing synchronous and asynchronous message streaming.

• LLM Observability: Adds support for tracing synchronous and asynchronous message streaming.

• SSI: Introduces generic safeguards for automatic instrumentation when using single step install in the form of early exit conditions. Early exit from instrumentation is triggered if a version of software in the environment is not explicitly supported by ddtrace. The Python runtime itself and many Python packages are checked for explicit support on the basis of their version.

• langchain: Introduces support for langchain==0.2.0 by conditionally patching the langchain-community module if available, which is an optional dependency for langchain>=0.2.0. See the langchain integration docs for more details.

• LLM Observability: Adds support to automatically submit Anthropic chat messages to LLM Observability.

• tracer: This introduces the tracer flare functionality. Currently the tracer flare includes the tracer logs and tracer configurations.

• Code Security: Expands SSRF vulnerability support for Code Security and Exploit Prevention for the modules urllib3, http.client, webbrowser and urllib.request.

• ASM: This introduces full support for exploit prevention in the python tracer.

  • LFI (via standard API open)
  • SSRF (via standard API urllib or third party requests)

  with monitoring and blocking feature, telemetry and span metrics reports.

• ASM: This introduces SQL injection support for exploit prevention.

• anthropic: This introduces tracing support for anthropic chat messages.
  See the docs for more information.

• ASM: This introduces "Standalone ASM", a feature that disables APM in the tracer but keeps ASM enabled. In order to enable it, set the environment variables DD_APPSEC_ENABLED=1 and DD_EXPERIMENTAL_APPSEC_STANDALONE_ENABLED=1.

• LLM Observability: This introduces the LLM Observability SDK, which enhances the observability of Python-based LLM applications. See the LLM Observability Overview or the SDK documentation for more information about this feature.

• opentelemetry: Adds support for span events.

• tracing: Ensures the following OpenTelemetry environment variables are mapped to an equivalent Datadog configuration (datadog environment variables taking precedence in cases where both are configured):

  OTEL_SERVICE_NAME -> DD_SERVICE
  OTEL_LOG_LEVEL -> DD_TRACE_DEBUG
  OTEL_PROPAGATORS -> DD_TRACE_PROPAGATION_STYLE
  OTEL_TRACES_SAMPLER -> DD_TRACE_SAMPLE_RATE
  OTEL_TRACES_EXPORTER -> DD_TRACE_ENABLED
  OTEL_METRICS_EXPORTER -> DD_RUNTIME_METRICS_ENABLED
  OTEL_LOGS_EXPORTER -> none
  OTEL_RESOURCE_ATTRIBUTES -> DD_TAGS
  OTEL_SDK_DISABLED -> DD_TRACE_OTEL_ENABLED
  

• otel: Adds support for generating Datadog trace metrics using OpenTelemetry instrumentations

Known Issues

• Code Security: Security tracing for the builtins.open function is experimental and may not be stable. This aspect is not replaced by default.
• grpc: Tracing for the grpc.aio clients and servers is experimental and may not be stable. This integration is now disabled by default.

Deprecation Notes

• Removes the deprecated sqlparse dependency.
• LLM Observability: DD_LLMOBS_APP_NAME is deprecated and will be removed in the next major version of ddtrace. As an alternative to DD_LLMOBS_APP_NAME, you can use DD_LLMOBS_ML_APP instead. See the SDK setup documentation for more details on how to configure the LLM Observability SDK.

Bug Fixes

• Code Security: Logs warning instead of throwing an exception in the native module if IAST is not enabled by env var.

• redis: This fix resolves an issue in redis utils where a variable may not be declared within a try/catch

• Code Security: Adds the boto package to the IAST patching denylist.

• celery: Changes error.message span tag to

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