4.8.6

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

Bug Fixes

• LLM Observability: Users auto instrumenting Langchain and using Bedrock inference profiles would have their spans' be associated with the inference profile's ARN instead of the underlying LLM model. We now resolve the correct underlying model if users pass base_model_id to their ChatBedrockConverse instantiation. #18151

Full Changelog: v4.8.5...v4.8.6

4.9.0rc2

Estimated end-of-life date, accurate to within three months: 10-2027
See the support level definitions for more information.

Upgrade Notes

• AI Guard: ddtrace.appsec.ai_guard.AIGuardAbortError now derives from ddtrace.internal._exceptions.DDBlockException (a BaseException subclass) instead of Exception. This brings AI Guard block decisions in line with how ASM blocks are surfaced and prevents a generic except Exception: in user code from silently swallowing a block.

• settings: Legacy environment variable names registered as aliases in the configuration registry now also work when set via local or fleet stable config files, not just shell environment variables. #17958

Deprecation Notes

• Tracing: DD_TRACE_INFERRED_SPANS_ENABLED is deprecated and will be removed in 5.0.0. Use DD_TRACE_INFERRED_PROXY_SERVICES_ENABLED instead. The old environment variable continues to work but emits a DDTraceDeprecationWarning when set.

New Features

• aws_durable_execution_sdk_python: Add tracing support for the aws-durable-execution-sdk-python library. Instruments @durable_execution workflows and DurableContext operations (step, invoke, wait, wait_for_condition, wait_for_callback, create_callback, map, parallel, run_in_child_context) to generate spans.

• LLM Observability: Adds step spans to the Claude Agent SDK integration. Each inference cycle is now represented by a step container span with an llm child span for the model call and tool child spans for any tool invocations.

• tracing: Adds a centralized supported-configurations.json registry of all supported DD_* and OTEL_* environment variables, following the same schema used by other Datadog tracing libraries. Accesses to unregistered environment variables now produce a debug log to help identify typos or unsupported configuration options.

• AI Guard: Copies anomaly-detection attributes from the local root (service-entry) span onto every ai_guard span: ai_guard.http.useragent, ai_guard.http.client_ip, ai_guard.network.client.ip, ai_guard.usr.id and ai_guard.usr.session_id.

• ai_guard: add AI Guard evaluation support to the OpenAI SDK chat completions instrumentation. Both non-streaming and streaming requests and non-streaming responses are evaluated through the configured AI Guard client, and evaluation is automatically skipped when a framework integration (LangChain, Strands Agents) is already evaluating the same call.

• code origin for spans: The code origin for spans feature has been enabled by default.

• code origin: attach code origin information to the first span generated by a function wrapped with tracer.wrap.

• openfeature: This introduces a configurable initialization timeout for DataDogProvider. The timeout controls how long initialize() waits for configuration before returning, and defaults to 30 seconds. Set it via the DD_EXPERIMENTAL_FLAGGING_PROVIDER_INITIALIZATION_TIMEOUT_MS environment variable or the init_timeout constructor parameter.

• CI Visibility: This introduces Jenkins custom parent ID propagation, which enables Datadog to correlate tests run from Jenkins with their Jenkins jobs and pipelines.

• LLM Observability: Adds an optional cost_tags argument to LLMObs.annotate() and LLMObs.annotation_context(). Pass a list of tag keys (already set via tags or annotated previously on the same span) to have them attached to the cost and token metrics generated from LLM and embedding spans, which can help breaking down spend by team, project, org, or any custom dimension.

• LLM Observability: Adds support for an optional version (string) field on each tool definition dictionary passed to LLMObs.annotate() via the tool_definitions parameter.

• profiling: Add DD_PROFILING_LOCK_EXCLUDE_MODULES config to skip lock profiling for framework-internal locks. Excluded locks remain native with zero profiling overhead. Set it to a comma-separated list of module prefixes (e.g., django.db,sqlalchemy.pool,urllib3).

• LLM Observability: Bedrock Agent orchestration step events (model invocations, tool/action group calls, knowledge base lookups, guardrails, rationales) are now emitted as APM child spans of the Bedrock Agent <agent_id> span when LLM Observability is enabled, with the same LLMObs payload shape as before.

Bug Fixes

• ai_guard: This fix resolves a conflict between ddtrace.auto and strands when imported in the same file, which left Strands hooks silently disabled. The Strands integration now loads lazily on first attribute access so its event class identities match those the agent dispatches.

• appsec: Adds telemetry metrics instrum.user_auth.missing_user_login and instrum.user_auth.missing_user_id when Django auth events cannot resolve the expected identity fields, enabling detection of misconfigured user model field mappings.

• AAP: This fix resolves an issue where the usr.session_id tag was missing from the entry span of authenticated follow-up Django requests when automatic user instrumentation was enabled. They now also carry usr.session_id, matching other authenticated user-tagging paths.

• azure_cosmos: This change removes the http.status_code tags from Azure CosmosDB spans and replaces them with the use of the db.response.status_code metric. For customers using ddtrace v4.8.0 and relying on the http.status_code tag of cosmosdb.query spans, this is a breaking change.

• CI Visibility: Fixes an issue in the pytest plugin where a malformed log call emitted a --- Logging error --- traceback to stderr during Attempt to Fix retries, polluting pytest output and contributing to spurious test failures.

• CI Visibility: Fixes an IndexError in retry bookkeeping that occurred when a test's teardown phase failed. The error produced --- Logging error --- tracebacks in stderr, which could pollute test output and cause spurious test failures during retries. #17863

• CI Visibility: Fixes a regression where setting DD_TEST_MANAGEMENT_ENABLED=0 was not honored by the new pytest plugin, causing Test Management features such as quarantining, disabling tests, and Attempt to Fix to remain enabled.

• datastreams: Demotes the retry limit exceeded submitting pathway stats log from ERROR to WARNING and removes the multi-line traceback from the record. This message fires when the processor cannot reach the agent within its 1-second timeout; the dropped 10 seconds of DSM data is auto-recovered on the next flush.

• LLM Observability: Fixes a concurrency bug in the Bedrock Agent integration where concurrent invoke_agent calls could orphan or cross-attribute spans due to shared class-level state. Per-invocation state is now used.

• LLM Observability: This fix resolves an issue where text wrapped in Bedrock Converse guardContent content blocks was rendered as [Unsupported content type: guardContent] in traces, dropping the user's input.

• CI Visibility: Fixes an issue where tests marked as attempt-to-fix could have failures hidden when they were also quarantined or disabled.

• django: Stop tagging async view and middleware spans as errored on routine ASGI cancellations (e.g. client disconnects on streaming responses), a regression introduced in 4.8.0rc4. Cancellation still propagates; the span just finishes without error.type='asyncio.exceptions.CancelledError'.

• django: Fixes DD_DJANGO_DATABASE_SERVICE and DD_DJANGO_DATABASE_SERVICE_NAME, which were previously generated as DD_DJANGO-DATABASE_SERVICE and DD_DJANGO-DATABASE_SERVICE_NAME. The hyphenated names were invalid POSIX identifiers and unusable from most shells. Hyphens in integration names are now normalized to underscores when building env var names. The old hyphenated names are preserved as aliases for backward compatibility. #17952

• telemetry: tolerate malformed installed distribution metadata so a single bad dist-info entry no longer floods stderr with repeated tracebacks.

• profiling: Fixes an issue where the lock profiler silently stopped capturing lock events when running under ddtrace-run with gevent installed.

• LLM Observability: The OpenAI integration now preserves assistant message content when tool_calls are present on the same message. #17760

• openfeature: This fix resolves an issue where DataDogProvider.initialize() returned before configuration was received, causing the OpenFeature SDK to mark the provider as ready to serve evaluations too early and flag evaluations to silently return default values. The provider now waits for configuration before returning.

• openfeature: Fixes targeting key handling in the OpenFeature provider. None targeting key is now correctly passed to the native evaluator instead of being coerced to empty string. Flags that don't require a targeting key (static, rule-based) now evaluate successfully without one, matching the Datadog provider spec. Additionally, the Rust binding now correctly maps TargetingKeyMissing errors from libdatadog instead of returning a generic error code.

• tracing: Fixes an issue where the svc.auto process tag produced garbled values such as python_-m_unittest when a process was launched with the full command as a single sys.argv[0] string (e.g. from a Docker ENTRYPOINT, a process manager, or a subprocess call with an unsplit command). The correct module or script nam...

4.8.5

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

Deprecation Notes

• Tracing: DD_TRACE_INFERRED_SPANS_ENABLED is deprecated and will be removed in 5.0.0. Use DD_TRACE_INFERRED_PROXY_SERVICES_ENABLED instead. The old environment variable continues to work but emits a DDTraceDeprecationWarning when set.

Bug Fixes

• LLM Observability: This fix resolves an issue where text wrapped in Bedrock Converse guardContent content blocks was rendered as [Unsupported content type: guardContent] in traces, dropping the user's input.

• LLM Observability: The OpenAI integration now preserves assistant message content when tool_calls are present on the same message. #17760

• starlette: This fix resolves an issue where passing middleware=None caused application startup to fail when Starlette tracing was enabled.

• LLM Observability: Resolves an issue in the Claude Agent SDK integration where unnecessary LLM spans were being created and affecting the trace structure. The handler now only opens a new LLM span after a UserMessage that actually contained tool results, so messages without tool results no longer overwrite the in-flight LLM span.

4.8.4

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

Bug Fixes

• telemetry: This change resolves an issue where malformed installed distribution metadata caused a single bad dist-info entry to flood stderr with repeated tracebacks.

Full Changelog: v4.8.3...v4.8.4

4.8.3

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

Bug Fixes

• azure_cosmos: This change removes the http.status_code tags from Azure CosmosDB spans and replaces them with the use of the db.response.status_code metric. For customers using ddtrace v4.8.0 and relying on the http.status_code tag of cosmosdb.query spans, this is a breaking change.

4.7.2

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

Bug Fixes

• CI Visibility: This fix resolves an issue where a failure response from the /search_commits endpoint caused the git metadata upload to fall back to sending the full 30-day commit history instead of aborting. This fallback could trigger cascading write load on the backend. The upload now aborts when search_commits fails, matching the behavior when the /packfile upload itself fails.

• ai_guard: This fix resolves a conflict between ddtrace.auto and strands when imported in the same file, which left Strands hooks silently disabled. The Strands integration now loads lazily on first attribute access so its event class identities match those the agent dispatches.

• AAP: This fix resolves an issue where Application and API Protection (AAP) was incorrectly reported as an enabled product in internal telemetry for all services by default. Previously, registering remote configuration listeners caused AAP to be reported as activated even when it was not actually enabled. This had no impact on customers as it only affected internal telemetry data. AAP is now only reported as activated when it is explicitly enabled or enabled through remote configuration.

• iast: A crash has been fixed.

• profiling: A crash that could happen in child processes after fork has been fixed.

• tracing: This fix resolves a memory leak where reference cycles through a span's properties were invisible to Python's cyclic garbage collector and accumulated proportionally to traced call volume.

• internal: A crash has been fixed.

• LLM Observability: Fixes incorrect span hierarchy in LLMObs traces when using the ddtrace SDK alongside OTel-based instrumentation (e.g. Strands Agents). OTel gen_ai spans (e.g. invoke_agent) were incorrectly appearing as siblings of their SDK parent span (e.g. call_agent) rather than being nested under it.

• profiling: A rare crash occurring when profiling asyncio code with many tasks or deep call stacks has been fixed.

• profiling: A bug in Lock Profiling that could cause crashes when trying to access attributes of custom Lock subclasses (e.g. in Ray) has been fixed.

• profiling: A race condition which could make asyncio code raise exceptions at exit has been fixed.

• serverless: AWS Lambda functions now appear under their function name as the service when DD_SERVICE is not explicitly configured. Service remapping rules configured in Datadog will
  now apply correctly to Lambda spans.

4.8.2

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

Bug Fixes

• ai_guard
  • This fix resolves a conflict between ddtrace.auto and strands when imported in the same file, which left Strands hooks silently disabled. The Strands integration now loads lazily on first attribute access so its event class identities match those the agent dispatches.
• tracing
  • Limits parsing of the W3C tracestate header during tracecontext extraction to 32 list-members and 512 UTF-8 bytes, consistent with the W3C Trace Context specification (https://www.w3.org/TR/trace-context/). Extra list-members and trailing whole entries that would exceed the byte budget are ignored, so unusually large headers no longer expand unbounded work during extraction. The Datadog dd= list-member is preferred: it is kept when present (including when it appears late in the header or alone exceeds the byte cap), and other vendors are dropped first. List-members longer than DD_TRACE_TRACESTATE_ITEM_MAX_CHARS (128) characters are removed first when trimming by list-member count or byte budget, so shorter vendor entries are kept when possible.
  • tracing: Parsing incoming baggage HTTP headers now respects DD_TRACE_BAGGAGE_MAX_ITEMS [default 64] and DD_TRACE_BAGGAGE_MAX_BYTES [default 8192], consistent with baggage injection. Previously, extraction could retain every comma-separated entry regardless of those limits. The tracer drops excess pairs and records truncation telemetry when limits apply.

4.8.1

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

Bug Fixes

• django: Stop tagging async view and middleware spans as errored on routine ASGI cancellations (e.g. client disconnects on streaming responses), a regression introduced in 4.8.0rc4. Cancellation still propagates; the span just finishes without error.type='asyncio.exceptions.CancelledError'.

• tracing: This fix resolves a memory leak where reference cycles through a span's properties were invisible to Python's cyclic garbage collector and accumulated proportionally to traced call volume.

4.8.0

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

Upgrade Notes

• claude_agent_sdk: Tool span resource names have changed from the tool name (e.g. Read, Bash) to claude_agent_sdk.tool. The specific tool name is still available in the span name (e.g. claude_agent_sdk.tool.Read). Users relying on tool resource names should update them accordingly.

• ray: Adds DD_TRACE_RAY_SUBMISSION_SPANS_ENABLED (default: False) configuration to control Ray submission tracing. Set DD_TRACE_RAY_SUBMISSION_SPANS_ENABLED=true to trace task.submit and actor_method.submit spans. Leave it unset to trace only execution spans. See Ray integration documentation for more details.

• ray: ray.job.submit spans are removed. Ray job submission outcome is now reported on the existing ray.job span through ray.job.submit_status.

Deprecation Notes

• Tracing: DD_TRACE_INFERRED_PROXY_SERVICES_ENABLED is deprecated and will be removed in 5.0.0. Use DD_TRACE_INFERRED_SPANS_ENABLED instead. The old environment variable continues to work but emits a DDTraceDeprecationWarning when set.

• tracing: The pin parameter in ddtrace.contrib.dbapi.TracedConnection, ddtrace.contrib.dbapi.TracedCursor, and ddtrace.contrib.dbapi_async.TracedAsyncConnection is deprecated and will be removed in version 5.0.0. To manage configuration of DB tracing please use integration configuration and environment variables.

• LLM Observability: Removes support for the RAGAS integration. As an alternative, if you have RAGAS evaluations, you can manually submit these evaluation results. See LLM Observability external evaluation documentation for more information.

New Features

• AI Guard: Add DD_AI_GUARD_BLOCK environment variable. Defaults to True, which means the blocking behavior configured in the Datadog AI Guard UI (in-app) will be honored. Set to False to force monitor-only mode locally: evaluations are still performed but AIGuardAbortError is never raised, regardless of the in-app blocking setting.

• AI Guard response objects now include a dict field tag_probs with the probabilities for each tag.

• CI Visibility: Adds Bazel offline execution support with two modes: manifest mode (DD_TEST_OPTIMIZATION_MANIFEST_FILE), which reads settings and test data from pre-fetched cache files without network access; and payload-files mode (DD_TEST_OPTIMIZATION_PAYLOADS_IN_FILES), which writes test event, coverage, and telemetry payloads as JSON files instead of sending HTTP requests. Both modes can be used independently or together.

• LLM Observability: Captures individual LLM spans for each Claude model turn within a Claude Agent SDK session. Each LLM span captures the input messages, output messages, model name, and token usage metrics (for claude_agent_sdk >= 0.1.49).

• AAP: This adds Application Security support for FastAPI and Starlette applications using mounted sub-applications (via app.mount()). WAF evaluation, path parameter extraction, API endpoint discovery, and http.route reporting now correctly account for mount prefixes in sub-application routing.

• google_cloud_pubsub: This adds tracing for Google Cloud Pub/Sub admin operations on topic, subscription, snapshot, and schema management methods.

• google_cloud_pubsub: Adds support for Google Cloud Pub/Sub push subscriptions. When a push subscription delivers a message via HTTP, the integration now creates an inferred gcp.pubsub.receive span that captures subscription and message metadata. Use DD_GOOGLE_CLOUD_PUBSUB_PROPAGATION_AS_SPAN_LINKS to control whether the inferred span becomes a child of the producer trace or starts a new trace with the producer context attached as a span link (default: False).

• LLM Observability: Add ExperimentRun.as_dataframe() to convert experiment run results into a pandas.DataFrame with a two-level MultiIndex on columns. Each top-level group (input, output, expected_output, evaluations, metadata, error, span_id, trace_id) maps to the first index level. Dict-valued fields are flattened one level deep; scalar fields use an empty string as the sub-column name. Each evaluator gets its own column containing the full evaluation result dict. Requires pandas to be installed (pip install pandas).

• LLM Observability: Adds an eval_scope parameter to LLMObs.submit_evaluation() (one of "span" (default) or "trace"). Use eval_scope="trace" to associate an evaluation with an entire trace by passing the root span context.

• LLM Observability: Adds LLMObs.get_spans() to retrieve span events from the Datadog platform API (GET /api/v2/llm-obs/v1/spans/events). Supports filtering by trace ID, span ID, span kind, span name, ML app, tags, and time range. Results are auto-paginated. Requires DD_API_KEY and DD_APP_KEY.

• profiling: Profiles generated from fork-based servers now include a process_type tag with the value main or worker.

• tracing: Support for making the default span name for @tracer.wrap include the class name has been added. For now, this is opt-in and can be enabled by setting DD_TRACE_WRAP_SPAN_NAME_INCLUDE_CLASS=true. The new naming will become the default in the next major release.

• llmobs: Adds support for enabling and disabling LLMObs via Remote Configuration.

• mysql: This introduces tracing support for mysql.connector.aio.connect in the MySQL integration.

• profiling: Thread sub-sampling is now supported. This allows to set a maximum number of threads to capture stacks for at each sampling interval. This can be used to reduce the CPU overhead of the Stack Profiler.

• llama_index: Adds APM tracing and LLM Observability support for llama-index-core>=0.11.0. Traces LLM calls, query engines, retrievers, embeddings, and agents. See the llama_index documentation for more information.

• ASM: Adds a LiteLLM proxy guardrail integration for Datadog AI Guard. The ddtrace.appsec.ai_guard.integrations.litellm.DatadogAIGuardGuardrail class can be registered as a custom guardrail in the LiteLLM proxy to evaluate requests and responses against AI Guard security policies. Requires the LiteLLM proxy guardrails API v2 available since litellm>=1.46.1.

• azure_cosmos: Add tracing support for Azure CosmosDB. This integration traces CRUD operations on CosmosDB databases, containers, and items.

• LLM Observability: Introduces a decorator tag to LLM Observability spans that are traced by a function decorator.

• CI Visibility: adds automatic log correlation and submission so that test logs appear alongside their corresponding test run in Datadog. Set DD_AGENTLESS_LOG_SUBMISSION_ENABLED=true for agentless setups, or DD_LOGS_INJECTION=true when using the Datadog Agent.

• tracing: Adds support for exporting traces in OTLP HTTP/JSON format via libdatadog. Set OTEL_TRACES_EXPORTER=otlp to send spans to an OTLP endpoint instead of the Datadog Agent.

• LLM Observability: Experiments accept a pydantic_evals ReportEvaluator as a summary evaluator when its evaluate return annotation is exactly ScalarResult. The scalar value is recorded as the summary evaluation. Report evaluators that declare a broader analysis return type (for example the full ReportAnalysis union) are not accepted as summary evaluators; use a class-based or function summary evaluator instead. Examples and further documentation can found in our documentation [here](https://docs.datadoghq.com/llm_observability/guide/evaluation_developer_guide).

  Example:

  from pydantic_evals.evaluators import ReportEvaluator
  from pydantic_evals.evaluators import ReportEvaluatorContext
  from pydantic_evals.reporting.analyses import ScalarResult
  
  from ddtrace.llmobs import LLMObs
  
  dataset = LLMObs.create_dataset(
      dataset_name="<DATASET_NAME>",
      description="<DATASET_DESCRIPTION>",
      records=[RECORD_1, RECORD_2, RECORD_3, ...]
  )
  
  class TotalCasesEvaluator(ReportEvaluator):
      def evaluate(self, ctx: ReportEvaluatorContext) -> ScalarResult:
          return ScalarResult(
              title='Total Cases',
              value=len(ctx.report.cases),
              unit='cases',
          )
  
  def my_task(input_data, config):
      return input_data["output"]
  
  equals_expected = EqualsExpected()
  summary_evaluator = TotalCasesEvaluator()
  
  experiment = LLMObs.experiment(
      name="<EXPERIMENT_NAME>",
      task=my_task, 
      dataset=dataset,
      evaluators=[equals_expected],
      summary_evaluators=[summary_evaluator],
      description="<EXPERIMENT_DESCRIPTION>."
  )
  
  result = experiment.run()
  

Bug Fixes

• CI visibility: This fix resolves issues where CI provider metadata could omit pull request base branch and head commit details or report incorrect pull request values for some providers.

• AAP: This fix resolves an issue where Application and API Protection (AAP) was incorrectly reported as an enabled product in internal telemetry for all services by default. Previously, registering remote configuration listeners caused AAP to be reported as activated even when it was not actually enabled. This had no impact on customers as it only affected internal telemetry data. AAP is now only reported as activated when it is explicitly enabled or enabled through remote configuration.

• asgi: Fixed an issue caused network.client.ip and ht...

4.9.0rc1

Estimated end-of-life date, accurate to within three months: 10-2027
See the support level definitions for more information.

Upgrade Notes

• ray: Adds DD_TRACE_RAY_IGNORED_ACTORS configuration to exclude specific Ray actor methods from instrumentation. Set DD_TRACE_RAY_IGNORED_ACTORS='{"ActorA": ["method1"], "ActorB": "*"}' to leave matching methods or actors uninstrumented while continuing to trace other Ray actor methods. Matching is based on actor class name only.

New Features

• AI Guard: When DD_AI_GUARD_ENABLED=true is set and an ai_guard span is created during a request, the tracer now populates http.client_ip and network.client.ip on the service-entry (local root) span, mirroring the behavior used for Application Security. If AI Guard does not run during the request, no client IP tags are added. DD_TRACE_CLIENT_IP_ENABLED is ignored once AI Guard reports, and DD_TRACE_CLIENT_IP_HEADER continues to override header resolution.

Bug Fixes

• CI Visibility: Fixes code coverage instrumentation on Python 3.13, 3.14, and 3.15. Resolves lost per-test line data caused by: sys.monitoring callbacks running in a snapshot context where ContextVar changes are not visible (Python 3.14+); empty modules emitting no LINE events (Python 3.13+); and ProcessPoolExecutor child coverage not being propagated to the parent context. Also fixes a stale-data bug where child process executable lines could inflate coverage denominators after stop_coverage() was called before join().

• django: API endpoint discovery now supports Django sub-applications mounted with django.urls.include(...). Endpoints are reported with their full URL path including the parent prefix — for example, a view served at /api/users/ is now reported as /api/users/ instead of losing the /api/ prefix.

• django: API endpoint discovery now reports the correct HTTP methods for views decorated with @require_http_methods combined with another decorator such as @csrf_exempt; the declared methods are reported instead of a generic wildcard entry.

• LLM Observability: This fix resolves an issue where running an experiment with a dataset whose records had null metadata caused the summary evaluator to crash with a TypeError while preparing evaluator inputs.

• LLM Observability: Changes the default model_name and model_provider of LLM and embedding spans from custom to unknown if not provided or empty. This applies to both auto-instrumented spans and manual instrumentation via LLMObs.llm() / LLMObs.embedding() and the @llm / @embedding decorators.

• profiling: A crash that could happen in child processes after fork has been fixed.

• profiling: A rare crash caused by the memory allocation profiler has been fixed.

• RemoteConfig: Fixed an issue where deleted remote configurations were not applied, causing stale settings to persist.

• wsgi: This fix resolves an issue where the http.url tag on inbound request spans contained the WSGI mount prefix twice (for example /admin/admin/users instead of /admin/users) when the application was served behind werkzeug.middleware.dispatcher.DispatcherMiddleware or any other in-process mount that preserves the original request URI in RAW_URI / REQUEST_URI while also setting SCRIPT_NAME.

• profiling: A rare crash happening on systems with small stack sizes when profiling asyncio code has been fixed.