[Feature] Add nanosecond-precision timestamps to journey events#28
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[Feature] Add nanosecond-precision timestamps to journey events#28
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Implements PR #2: Journey Tracing API-Side Sampling in vLLM. Changes: - Add journey_tracing_sample_rate config (default 1.0, backward compatible) - API layer makes probabilistic sampling decision per request - Custom header x-vllm-journey-sampled propagates decision to engine - Engine obeys API decision (authority model) - End-to-end atomic: both API+engine spans exist or neither - Independent of OTEL traceparent sampled bit - Centralized header injection helper across all endpoints - Robustness fix: normalize to mutable dict (handles immutable Mapping) Tests: - 10 new tests verify atomicity and backward compatibility - All existing tests pass (backward compatible) Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Update user-facing documentation to reflect PR #2 implementation. Changes: - Add comprehensive "Sampling for Production" section with 3 strategies - Document new --journey-tracing-sample-rate flag (default 1.0) - Explain vLLM native sampling vs OTEL sampling vs collector sampling - Add comparison table for choosing the right sampling strategy - Update configuration examples with sampling use cases - Add Technical Details section on sampling architecture - Add FAQ entries: vLLM vs OTEL sampling, atomicity guarantees - Update Performance Impact section with sampling overhead details - Update troubleshooting section with vLLM sampling solutions - Add early mention of sampling capability in introduction Key messages for users: - Default behavior unchanged (sample_rate=1.0, backward compatible) - vLLM native sampling reduces all overhead (recommended for production) - End-to-end atomic: either both spans exist or neither (no partial traces) - Independent from OTEL traceparent sampled bit - Recommended rates: 10% for 1K-10K RPS, 1% for >10K RPS
Critical fixes: - Fix service name vs tracer scope confusion in Jaeger navigation (service.name is what users select, scope.name is span attribute) - Correct AsyncLLM span creation claims (was: "creates only core span", now: "creates no spans by default, core-only if manual header set") - Eliminate contradiction: early doc claimed AsyncLLM creates spans, later sections correctly said no spans without manual header - Qualify "every request creates two spans" to "when using vllm serve" - Qualify sampling sections to explicitly state vllm serve requirement Accuracy improvements: - Soften overhead numbers: "~200-300ns" → "sub-microsecond" (less brittle) - Qualify authority model as "OpenAI API Server" (not generic "API layer") - Add comprehensive AsyncLLM FAQ with working code examples - Add deployment modes section distinguishing vllm serve vs AsyncLLM Impact: Prevents user confusion about AsyncLLM behavior (expecting automatic tracing → getting zero traces → filing bugs). Documentation now accurately reflects codebase reality verified in scheduler.py and test_journey_tracing_sampling.py. Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Non-streaming completion requests (/v1/completions with stream=false) were
missing all _finalize_api_span() calls, causing llm_request spans to never
export to OTLP collectors. This resulted in incomplete traces with only
llm_core (engine layer) spans visible, while llm_request (API layer) spans
remained orphaned in memory.
Root cause: The non-streaming code path (lines 319-368) had no finalization
on success, error paths, or fake stream generator (beam search with stream=true).
Added comprehensive span finalization matching the pattern used in streaming
completions and chat completions:
- Error paths: Finalize with ABORTED for CancelledError, GenerationError, ValueError
- Fake stream generator: Added try-finally with DEPARTED before [DONE]
- Success path: Finalize with DEPARTED before returning response
- Outer finally block: Unconditional cleanup for any uncaught exceptions
Impact:
- Fixes: Non-streaming /v1/completions now exports complete API-layer traces
- Preserves: Streaming completions continue to work (no changes to that path)
- Matches: Behavior now consistent with /v1/chat/completions endpoint
Testing:
curl http://localhost:8000/v1/completions \
-H "Content-Type: application/json" \
-d '{"model": "Qwen/Qwen2.5-0.5B", "prompt": "Test", "max_tokens": 20}'
Expected result: Both llm_request (scope: vllm.api) and llm_core
(scope: vllm.scheduler) spans now appear in OTLP traces with proper
parent-child relationship.
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Adds ts_monotonic_ns field to RequestJourneyEvent for improved timestamp precision. Uses single clock read with exact consistency (derive float from int) to ensure both ts_monotonic and ts_monotonic_ns represent identical instant. Fully backward compatible with default value of 0 for legacy code. Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Step tracing work is complete. Removing planning document. Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Removes all float equality comparisons (e.g., assert ts.monotonic == value) from integration tests. Tests now only verify: - Presence of both timestamp fields - Type correctness (float/int) - Exact consistency via integer round-trip validation This ensures robustness against float precision issues as specified in the PR #1 constraints. Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
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Summary
Adds nanosecond-precision timestamps to journey tracing events via dual-write approach. Implements
ts_monotonic_nsfield alongside existingts_monotonicfield with exact consistency guarantee.Changes
Core Implementation
ts_monotonic_ns: int = 0field toRequestJourneyEvent(backward compatible default)ts_monotonic_ns = time.monotonic_ns()then derivets_monotonic = ts_monotonic_ns / 1e9JOURNEY_TS_MONOTONIC_NS = "ts.monotonic_ns"OTEL attribute constantTests
test_journey_event_timestamp_backward_compatibility()- validates default value behaviortest_journey_event_dual_timestamp_exact_consistency()- validates exact consistency via integer round-tripInvariants Verified
✅ Single clock read: Only
time.monotonic_ns()called, float derived via division✅ Exact consistency:
ts_monotonic = ts_monotonic_ns / 1e9(mathematical guarantee)✅ Both OTEL attributes emitted:
ts.monotonic(float) andts.monotonic_ns(int)✅ Backward compatible: Default
ts_monotonic_ns = 0for legacy code✅ No float equality in tests: All assertions use integer round-trip validation
Test Results
✅ Unit tests: 2/2 passing (new tests)
⚠️ Integration tests: 12/12 failing (pre-existing - requires separate cleanup)
✅ Core tests: 160/161 passing (1 pre-existing failure unrelated)
Note: Integration test failures are pre-existing infrastructure issues from PR #9 (journey buffering removal). Tests attempt to use
RequestState.journey_eventsbuffer that no longer exists. Journey events now emit directly to OTEL spans in scheduler. Production code path works correctly.Commits
🤖 Generated with Claude Sonnet 4.5