litellm/tests/e2e/coverage_registry/logging.yaml
yucheng-berri 6a213de9f4
test(e2e): otel trace completeness on /v1/messages (#33133)
* test(e2e): OTEL trace completeness on /v1/messages

Extends the LIT-3787 trace-completeness suite to the Anthropic-native route:
one successful non-streaming /v1/messages call must land at the destination as
ONE connected trace (root SERVER span + auth/db/cost children + gen-AI CLIENT
span, no dangling parents). Adds the raw /v1/messages sender to the logging
suite client.

* test(e2e): reuse the shared AnthropicMessagesBody per review

Drops the duplicate /v1/messages request model in favor of the one models.py
already provides (budget_client uses the same one), passes max_tokens at the
call site to match the sibling chat test, notes in the docstring why the
gen-AI span is named chat on this surface, and adopts the hardened read-back
signature

* test(e2e): author the messages trace test docstring

* test(e2e): declare the messages surface on the covers marker

* test(e2e): otel trace completeness on /v1/responses (#33134)

* test(e2e): OTEL trace completeness on /v1/responses

Extends the LIT-3787 trace-completeness suite to the OpenAI Responses API
route: one successful non-streaming /v1/responses call must land at the
destination as ONE connected trace. Adds the raw /v1/responses sender, a
CHEAP_OPENAI_MODEL config constant, and registers responses in the otel
registry cell's exercised_on.

* test(e2e): author the responses trace test docstring

* test(e2e): declare the responses and chat surfaces on the covers markers
2026-07-13 20:19:06 -07:00

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YAML

# Logging integration delivery (behavior features). Grounded in litellm/integrations/.
- {id: logging.langfuse.success.logs_spend, module: logging, tier: P0, event: success, assertions: [logs_spend], exercised_on: [chat_completions, messages, embeddings], source: "integrations/langfuse/langfuse.py", rationale: "Primary tracing backend; cost accuracy"}
- {id: logging.langfuse.failure.logs_spend, module: logging, tier: P0, event: failure, assertions: [logs_spend], exercised_on: [chat_completions, messages], source: "integrations/langfuse/langfuse.py", rationale: "Failure path must still track spend"}
- {id: logging.langfuse.stream.logs_spend, module: logging, tier: P0, event: stream, assertions: [logs_spend], exercised_on: [chat_completions, messages], source: "integrations/langfuse/langfuse.py", rationale: "Streaming token counts aggregate"}
- {id: logging.s3.success.writes_object, module: logging, tier: P0, event: success, assertions: [writes_object], exercised_on: [chat_completions, messages, embeddings], source: "integrations/s3_v2.py", rationale: "Primary audit trail; batch flush no-drop"}
- {id: logging.s3.failure.writes_object, module: logging, tier: P0, event: failure, assertions: [writes_object], exercised_on: [chat_completions, messages], source: "integrations/s3_v2.py", rationale: "Failed calls persisted for compliance"}
- {id: logging.gcs_bucket.success.writes_object, module: logging, tier: P0, event: success, assertions: [writes_object], exercised_on: [chat_completions, messages, embeddings], source: "integrations/gcs_bucket/gcs_bucket.py", rationale: "GCS parallel to S3"}
- {id: logging.datadog.success.exports_metric, module: logging, tier: P0, event: success, assertions: [exports_metric], exercised_on: [chat_completions, messages, embeddings], source: "integrations/datadog/datadog.py", rationale: "Powers dashboards/alerts; cardinality regressions common"}
- {id: logging.datadog.failure.exports_metric, module: logging, tier: P0, event: failure, assertions: [exports_metric], exercised_on: [chat_completions], source: "integrations/datadog/datadog.py", rationale: "Failure metrics for alerting/SLO"}
- {id: logging.prometheus.success.exports_metric, module: logging, tier: P0, event: success, assertions: [exports_metric], exercised_on: [chat_completions, messages, embeddings], source: "integrations/prometheus.py", rationale: "Standard OSS metrics; per-key cardinality (existing e2e)"}
- {id: logging.otel.success.exports_metric, module: logging, tier: P0, event: success, assertions: [exports_metric], exercised_on: [chat_completions, messages, responses, embeddings], source: "integrations/otel/logger.py", rationale: "OTEL spans on every call path"}
- {id: logging.otel.failure.exports_metric, module: logging, tier: P0, event: failure, assertions: [exports_metric], exercised_on: [chat_completions, messages], source: "integrations/otel/logger.py", rationale: "Error spans for observability continuity"}
- {id: logging.braintrust.success.logs_spend, module: logging, tier: P1, event: success, assertions: [logs_spend], exercised_on: [chat_completions, messages], source: "integrations/braintrust_logging.py", rationale: "Evals platform spend"}
- {id: logging.langsmith.success.logs_spend, module: logging, tier: P1, event: success, assertions: [logs_spend], exercised_on: [chat_completions, messages], source: "integrations/langsmith.py", rationale: "LangChain ecosystem"}
- {id: logging.arize.success.logs_spend, module: logging, tier: P1, event: success, assertions: [logs_spend], exercised_on: [chat_completions, embeddings], source: "integrations/arize/arize.py", rationale: "ML-ops observability"}
- {id: logging.mlflow.success.logs_spend, module: logging, tier: P1, event: success, assertions: [logs_spend], exercised_on: [chat_completions], source: "integrations/mlflow.py", rationale: "Experiment tracking cost/run"}
- {id: logging.opik.success.logs_spend, module: logging, tier: P1, event: success, assertions: [logs_spend], exercised_on: [chat_completions], source: "integrations/opik/opik.py", rationale: "Eval platform spend/case"}
- {id: logging.openmeter.success.exports_metric, module: logging, tier: P1, event: success, assertions: [exports_metric], exercised_on: [chat_completions, messages, embeddings], source: "integrations/openmeter.py", rationale: "Usage metering for billing"}
- {id: logging.literal_ai.success.logs_spend, module: logging, tier: P1, event: success, assertions: [logs_spend], exercised_on: [chat_completions, messages], source: "integrations/literal_ai.py", rationale: "Tracing platform spend"}
- {id: logging.posthog.success.exports_metric, module: logging, tier: P1, event: success, assertions: [exports_metric], exercised_on: [chat_completions, messages], source: "integrations/posthog.py", rationale: "Product analytics batching"}
- {id: logging.azure_storage.success.writes_object, module: logging, tier: P1, event: success, assertions: [writes_object], exercised_on: [chat_completions, messages], source: "integrations/azure_storage/azure_storage.py", rationale: "Azure blob for enterprise"}
- {id: logging.cloudzero.success.logs_spend, module: logging, tier: P1, event: success, assertions: [logs_spend], exercised_on: [chat_completions], source: "integrations/cloudzero/cloudzero.py", rationale: "Cost ops correlation"}
- {id: logging.focus.success.writes_object, module: logging, tier: P1, event: success, assertions: [writes_object], exercised_on: [chat_completions, messages], source: "integrations/focus/focus_logger.py", rationale: "Cost mgmt multi-destination export"}
- {id: logging.niche_integrations.success.logs_spend, module: logging, tier: P2, event: success, assertions: [logs_spend], exercised_on: [chat_completions], source: grammar, rationale: "SMOKE cohort: athina/galileo/deepeval/langtrace/weave/lunary/humanloop/traceloop/helicone/argilla/newrelic/sqs/supabase/dynamodb/agentops/lago/etc"}
- {id: logging.niche_integrations.failure.logs_spend, module: logging, tier: P2, event: failure, assertions: [logs_spend], exercised_on: [chat_completions], source: grammar, rationale: "SMOKE niche failure path"}