feat(telemetry): add OTel standard logs as third signal#239
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Wire up a LoggerProvider alongside the existing metrics and traces so
stdlib logging calls automatically flow through OTel with the shared
resource attributes (service.name, region, subaccount, etc.).
- setup_log_provider() in _provider.py mirrors _setup_meter_provider():
LoggerProvider + BatchLogRecordProcessor + OTLP exporter (grpc/http)
- LoggingHandler from opentelemetry-instrumentation-logging installed on
root logger so all existing logging.getLogger() calls are captured
- auto_instrument() calls setup_log_provider() alongside trace setup,
keeping the one-call contract for apps
- user-guide.md: new Logging section with usage examples, structured
fields, level filtering, and trace correlation notes
- unit tests: mock-level coverage for exporter protocol, provider setup,
handler installation, and auto_instrument wiring
- e2e tests: real in-memory pipeline verifying body, severity, resource
attributes, extra={} fields, and trace/span correlation
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Summary
LoggerProvideralongside existing metrics and traces using the shared resource attributes (service.name, region, subaccount, etc.)auto_instrument()now sets up all three OTel signals — no app boilerplate changes neededLoggingHandlerfromopentelemetry-instrumentation-logging(not the deprecated SDK one) installed on the root stdlib loggerChanges
_provider.py:setup_log_provider()+_create_log_exporter()— mirrors_setup_meter_provider()pattern, same grpc/http protocol switchauto_instrument.py: onesetup_log_provider()call wired in after trace setupuser-guide.md: new Logging section covering usage,extra={}structured fields, level filtering, trace correlationTests
_create_log_exporter,setup_log_provider, andauto_instrumentwiringextra={}fields, and trace/span correlation — all run in CI without any external dependenciesApp usage
No changes needed. After
auto_instrument(), all existinglogging.getLogger(...)calls ship logs to the OTel backend automatically: