[JunyiXu-nv]

Dev Engineer Review

When iteration stats are disabled, get_iteration_stats returns an empty list without reading from the executor. When the background collector is unavailable, the handler runs one blocking stats read at a time on a dedicated metrics executor. It shields the read from scrape cancellation, returns [] for RPCError, and preserves completed results for a later scrape if the original scrape is cancelled. The executor shuts down with the application and cancels queued work.

Concurrent scrapes can receive an empty list while a read is in flight or awaiting consumption. Documentation recommends polling from a single client because each statistic goes to one caller. The reported throughput and event-loop results are author-reported; no independent benchmark or test run was performed in this review.

QA Engineer Review

The unit test file covers background-buffer and direct-queue reads, event-loop responsiveness, metrics-executor use, concurrent scraping, cancellation and completion races, executor errors, disabled stats, route behavior, and visual-gen stats. The test file is registered in tests/integration/test_lists/test-db/l0_cpu.yml. Manual-QA list status is not established. The author reported 11/11 tests passing against the release branch; broader CI results included failed and aborted pipelines without failure details. Coverage verdict: sufficient.

Per-File QA Perspective

• tensorrt_llm/serve/openai_server.py: Verify that disabled stats do not poll the executor, blocking reads stay off the event loop, and concurrent scrapes do not queue reads. Verify cancellation, RPCError, other read failures, and shutdown behavior.
• tests/unittest/llmapi/apps/test_openai_server_iteration_stats.py: Covers the stats-read paths and regressions listed above. The file is registered in the CPU CI test list.
• tests/integration/test_lists/test-db/l0_cpu.yml: Adds the iteration-stats unit test to the CPU CI list.
• docs/source/commands/trtllm-serve/trtllm-serve.rst: Documents that each statistic is returned to one caller and recommends a single polling client.

Description

Fixes https://nvbugs/6758245: turning enable_iter_perf_stats off made serving slower. A Kimi K3 benchmark on Rubin, scraping GET /metrics every 1-2 s, measured 16.3% lower output tokens/s with the stats off than with them on.

/metrics serves from the background collector's buffer only when both return_perf_metrics and enable_iter_perf_stats are on. In every other configuration it reads iteration stats through get_stats_async(2). Since #9980, the executor call behind that (proxy.aget_stats / rpc_proxy.aget_stats) is a blocking .remote() RPC, and the worker side polls until stats arrive or 2 s pass. The call runs on the server's event loop, so every scrape froze every streaming response for the length of the wait. With iteration stats off, no stats ever arrive, so each scrape froze it for the full 2 s.

• Stats off (commit by Bowen Fu, from [https://nvbugs/6758245][fix] Avoid metrics queue polling when iteration stats are disabled #19517): /metrics returns [] at once instead of waiting for stats that never come.
• Stats on without the collector:
  • Dedicated thread: the read (self.generator.get_stats(2)) runs on a dedicated one-thread ThreadPoolExecutor, so streaming continues while it waits. The default executor stays free for request handling (generate_async, token counting). LLM.get_stats returns the same parsed stats as the async path.
  • One read at a time: a scrape that arrives while a read is in flight gets [] at once instead of queueing, so scraping an idle server faster than one read per 2 s cannot build a backlog. Behavior change: the read drains the stats queue and hands everything to its own scrape. With two consumers polling /metrics at once (say a benchmark harness and Prometheus), one of them now regularly gets an empty list.
  • Cancelled scrapes: if a scrape goes away mid-read, the read still finishes, and the next scrape takes the stats it drained, so those iterations are not lost.
  • Shutdown: the metrics executor is shut down in lifespan after the generator.
• Docs: the /metrics section of trtllm-serve.rst now says that each statistic goes to only one caller, so the endpoint should be polled from a single client.
• RPC failures: on the default MPI proxy, get_stats raises the RPC errors that aget_stats used to swallow. The handler catches RPCError (for example RPCCancelled while the executor shuts down) and still returns [] rather than a 500.

This supersedes #19517 and carries its commit with its authorship.

tests/unittest/llmapi/apps/test_openai_server_iteration_stats.py was not on any CI list, so none of its tests had run in CI. It is now registered in l0_cpu.yml, with the cpu_only marker that the CPU stages select on.

Test Coverage

• tests/unittest/llmapi/apps/test_openai_server_iteration_stats.py (CPU-Generic-x86-1, CPU-Generic-arm-1):

  • test_metrics_endpoint_does_not_block_the_event_loop (new): a stats read that blocks for 0.5 s leaves the event loop running.
  • test_metrics_endpoint_reports_no_stats_when_executor_unreachable (new): an RPCCancelled from the stats read gives 200 with [].
  • The two tests from [https://nvbugs/6758245][fix] Avoid metrics queue polling when iteration stats are disabled #19517 cover the stats-off early return at handler and route level.
  • test_metrics_stats_read_runs_on_the_metrics_thread (new): the read runs on the server's metrics executor, not the default one.
  • test_sustained_scraping_keeps_one_stats_read_in_flight (new): while one read is held, four more scrapes return [] without reading; after it finishes, the next scrape reads again.
  • test_stats_read_for_a_cancelled_scrape_goes_to_the_next_scrape (new): a scrape cancelled mid-read leaves its stats for the next scrape.
  • None of these tests sleeps: the fake get_stats blocks on a threading.Event the test opens.
  • The existing tests cover the buffered and legacy paths.

• Measured on Blackwell (1x RTX PRO 4500 Blackwell) with trtllm-serve from the 1.2.0rc8 release container. That container's /metrics handler is the legacy path that main and release/1.3 still take without the background collector. The collector-buffer branch came later, and this configuration does not take it. Its proxy.aget_stats / proxy.get_stats are the same as on main and release/1.3. The "this PR" rows apply the first version of this change (reading on a worker thread) to its get_iteration_stats. Qwen3-0.6B, ISL 1024 / OSL 768, 32 streaming requests at concurrency 1, and a client that calls /metrics 1 s after each response:

  enable_iter_perf_stats	/metrics polling	handler	output tok/s	max ITL	ITLs > 0.5 s	/metrics p50
  off	none	-	392.2	9 ms	0	-
  off	1 s gap	before	303.6 (-22.6%)	2040 ms	16	4026 ms
  on	1 s gap	before	388.6	74 ms	0	2074 ms
  off	1 s gap	this PR	391.9	9 ms	0	1 ms
  on	1 s gap	this PR	389.0	21 ms	0	33 ms

  A repeat of all five runs matched within 0.1% output tok/s. With /metrics called 2 s after each response instead, stats off measured 379.5 tok/s with 10 ITLs over 0.5 s before this change, and 391.9 tok/s with none after it.

• Locally (no build), the shipped get_iteration_stats was run with a stats read that blocks for 0.5 s, mimicking the executor RPC:

  • On main, the event loop got 0 turns during the call, with stats on or off.
  • On this branch, it got 49 turns with stats on, and the stats-off call returned [] at once without calling the executor.

• This file's pytest suite now runs in CI. It passed in the CPU-Generic stages of the first release/1.3 pipeline ([Feature request] AutoAWQ support #345), as it had on main.

• Not yet run: a Kimi K3 rerun of the original Rubin repro.

PR Checklist

Please review the following before submitting your PR:

• PR description clearly explains what and why. If using CodeRabbit's summary, please make sure it makes sense.

• PR Follows TRT-LLM CODING GUIDELINES to the best of your knowledge.

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• If PR introduces API changes, an appropriate PR label is added - either api-compatible or api-breaking. For api-breaking, include BREAKING in the PR title.

• Any new dependencies have been scanned for license and vulnerabilities

• CODEOWNERS updated if ownership changes

• Documentation updated as needed

• Update tava architecture diagram if there is a significant design change in PR.

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• Please check this after reviewing the above items as appropriate for this PR.

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Walkthrough

The /metrics endpoint skips iteration-stat reads when statistics are disabled. Otherwise, it runs blocking reads through a dedicated executor. Concurrent scrapes do not start additional reads, and a later scrape can claim results from a read that continued after cancellation.

Changes

Iteration Stats Retrieval

Layer / File(s)	Summary
Server stats retrieval tensorrt_llm/serve/openai_server.py	The server skips reads when iteration stats are disabled and runs blocking reads through a dedicated executor. Concurrent scrapes receive empty results while a read is in flight. A later scrape can claim unclaimed results after cancellation. RPC errors produce an empty list.
Retrieval validation and documentation tests/unittest/llmapi/apps/test_openai_server_iteration_stats.py, tests/integration/test_lists/test-db/l0_cpu.yml, docs/source/commands/trtllm-serve/trtllm-serve.rst	Tests cover event-loop responsiveness, executor use, concurrent scrapes, cancellation, RPC errors, disabled stats, and /metrics responses. The CPU test list includes the module. The documentation states that concurrent pollers may receive an empty list.

Priority: ⬆️ High

Estimated code review effort: 3 (Moderate) | ~20 minutes

Change: Bug fix

Merge Risk: ⚪ Minimal · up to 260b0

The change stops /metrics polling from blocking the server event loop and returns promptly when iteration stats are disabled. Review concerns raised earlier have been addressed, and no merge-blocking risk is evident from the supplied context.

Pre-merge checks: 4 · 1

Failed checks: 1 warning

Check name	Status	Explanation	Resolution
Docstring Coverage		Docstring coverage is 27.27% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 22 functions across 2 files.	Write docstrings for the functions missing them to satisfy the coverage threshold.

Passed checks: 4 passed

Check name	Status	Explanation
Title check		The title clearly identifies the fix, the affected endpoint, and the event-loop blocking issue. It follows the required ticket and type format.
Description check		The description is complete and relevant. It explains the problem, solution, behavior changes, documentation updates, test coverage, benchmark results, and remaining validation work.
Linked Issues check		Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check		Check skipped because no linked issues were found for this pull request.

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🧹 Nitpick comments: 1

tensorrt_llm/serve/openai_server.py: 1

1767-1775: 🧹 Nitpick | 🔵 Trivial

Stats retrieval moves off the event loop. One residual risk remains.

asyncio.to_thread uses the default executor. Each /metrics poll blocks one worker thread for up to 2 s while it waits for stats. The default pool is bounded, so many concurrent scrapes can fill it. Other to_thread callers in this file, such as start_profile, stop_profile, and _live_tokens_per_block, then queue behind those scrapes. This is a narrow case. Normal scrape rates do not trigger it. A dedicated executor or a single-flight guard is optional hardening.

The RPCError handler and the early return for disabled stats are correct. The get_stats(2) contract matches LLM.get_stats.

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Review comment at @tensorrt_llm/serve/openai_server.py around lines 1767 - 1775:
Update the metrics stats retrieval around
`asyncio.to_thread(self.generator.get_stats, 2)` to avoid occupying the shared
default executor for each concurrent scrape; use a dedicated executor for
`get_stats` or a single-flight guard that shares an in-progress stats request.

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Review comments at @tensorrt_llm/serve/openai_server.py:
- Around line 1767-1775: Update the metrics stats retrieval around
`asyncio.to_thread(self.generator.get_stats, 2)` to avoid occupying the shared
default executor for each concurrent scrape; use a dedicated executor for
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[JunyiXu-nv]

@coderabbitai Agreed. Fixed in 87f116c. The default executor is not only used by the profiling endpoints: generate_async and the token counting on the request path go through asyncio.to_thread as well. A burst of scrapes that each wait the full 2 s could therefore delay request handling, which is the problem this PR exists to fix.

The stats read now runs on a one-thread ThreadPoolExecutor of its own (trtllm_metrics_stats), created next to the chat path's input-processing and media-load executors, which already exist for the same reason. Concurrent scrapes queue on that thread. They still never block the event loop, and they no longer take threads from the default executor.

I went with a dedicated executor rather than a single-flight guard. get_stats drains the stats queue, so sharing one in-flight read would hand the same batch to every waiting scrape. Queuing gives each scrape its own batch.

New test: test_metrics_stats_reads_stay_off_the_default_executor runs two concurrent scrapes and checks that both reads ran on the server's metrics thread. It fails on the previous head, where the reads ran on asyncio_* threads.

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tests/unittest/llmapi/apps/test_openai_server_iteration_stats.py: 1

191-193: 📐 Maintainability & Code Quality | 🔵 Trivial | ⚡ Quick win

Test the production metrics pool configuration.

This test supplies its own one-worker pool. If OpenAIServer.__init__ changes to use multiple metrics workers, the test still passes and misses the concurrency regression. Exercise the pool created by the production setup, or test that setup separately. Also assert that concurrent reads do not overlap. As per path instructions, flag “overly weak” assertions that miss the changed behavior.

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@tests/unittest/llmapi/apps/test_openai_server_iteration_stats.py around lines
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Update the test around `OpenAIServer.__init__` to use the metrics executor
created by production setup instead of replacing it with a one-worker
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Review comments at @tensorrt_llm/serve/openai_server.py:
- Around line 1779-1780: Bound concurrent legacy metrics reads around the
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Review comments at
@tests/unittest/llmapi/apps/test_openai_server_iteration_stats.py:
- Around line 191-193: Update the test around `OpenAIServer.__init__` to use the
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@JunyiXu-nv Thanks for the clarification. The dedicated single-thread executor addresses the default-executor contention concern.

I checked the implementation and the new test. The legacy stats read uses _metrics_stats_executor. The test checks that two concurrent reads return distinct batches and both run on the metrics thread. I did not run the tests.

Queuing is appropriate because get_stats drains the queue. A single-flight guard would share the same batch across waiting scrapes.

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Learnt from: JunyiXu-nv
URL: https://github.com/NVIDIA/TensorRT-LLM/pull/20429

Timestamp: 2026-10-19T05:56:16.377Z
Learning: In TensorRT-LLM, request-path generation through generate_async and token counting use asyncio.to_thread and therefore share the default executor. In tensorrt_llm/serve/openai_server.py, legacy iteration-stat reads must use the dedicated single-thread _metrics_stats_executor (thread prefix trtllm_metrics_stats) to avoid consuming default-executor threads. get_stats drains the stats queue, so concurrent scrapes queue for separate reads rather than sharing a single in-flight result.

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@coderabbitai Re the nitpick in review 5567447595 (test the production pool, assert reads don't overlap): with 61e000e the no-overlap guarantee no longer depends on the pool's worker count. get_iteration_stats starts at most one read, whatever executor it uses. test_sustained_scraping_keeps_one_stats_read_in_flight asserts that directly: a burst of five concurrent scrapes makes exactly one get_stats call. test_metrics_stats_read_runs_on_the_metrics_thread checks that the read runs on the server's own metrics executor rather than the default one.

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- Around line 1863-1867: Update the `_metrics_stats_read` handling so a
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[JunyiXu-nv]

@brnguyen2 Thanks for the review. All points are addressed. The inline ones are in 95e721c (replied in each thread).

• Description: updated to match the code:
  • the read runs on a dedicated one-thread executor with at most one read in flight;
  • behavior change: with two consumers polling at once, one of them regularly gets [], because the read hands everything it drains to its own scrape;
  • a scrape cancelled mid-read now leaves its stats for the next scrape instead of losing them;
  • the executor is shut down in lifespan.
• Docs: trtllm-serve.rst already said the stats are removed once retrieved. 1e78a58 adds that each statistic goes to only one caller, so the endpoint should be polled from a single client.
• Main branch: a cherry-pick of this PR into main will follow once it merges into release/1.3, as [https://nvbugs/6682814][fix] Cherry-pick #20230: Use node IPs for perf-sanity disagg servers and report unresolvable bind hosts #20556 did for [https://nvbugs/6682814][fix] Use node IPs for perf-sanity disagg servers and report unresolvable bind hosts #20230. I'll link it here.
• Measurement section: the sentence was complete but long and hard to read; I split it up. It now says the "this PR" rows measured the first version of the change, the worker-thread read.
• Pending validation: the description now says the Kimi K3 rerun of the original Rubin repro hasn't been done yet. This file's test suite now runs in CI; it passed in the CPU stages of the first release/1.3 pipeline.

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PR_Github #79051 [ run ] completed with state FAILURE. Commit: 260b0a3
/LLM/release-1.3/L0_MergeRequest_PR pipeline #374 completed with status: 'UNSTABLE'

CI Report

⚠️ Multi-GPU Label Required:
Multi-GPU tests require the ci: full pre-merge approved label on this PR. Either:

• Wait for the PR to be fully approved — the label is added automatically once approval is complete. Having unresolved open comments is fine, or
• If needed, ask a member of NVIDIA/trt-llm-ci-approvers to add the label manually.
  Then re-trigger CI with the same bot command (no rebase needed).

⚠️ Action Required:

• Please check the failed tests and fix your PR
• If you cannot view the failures, ask the CI triggerer to share details
• Once fixed, request an NVIDIA team member to trigger CI again

Link to invocation

[QiJune]

LGTM

[github-actions]

Automatically added "ci: full pre-merge approved" because this PR has satisfied the required GitHub review approvals. Unresolved review conversations and other required checks remain independent merge requirements.

[JunyiXu-nv]

/bot run --disable-fail-fast

[tensorrt-cicd]

PR_Github #79105 [ run ] triggered by Bot. Commit: 260b0a3 Link to invocation

[tensorrt-cicd]

PR_Github #79105 [ run ] completed with state FAILURE. Commit: 260b0a3
/LLM/release-1.3/L0_MergeRequest_PR pipeline #382 completed with status: 'FAILURE'

CI Report

⚠️ Action Required:

• Please check the failed tests and fix your PR
• If you cannot view the failures, ask the CI triggerer to share details
• Once fixed, request an NVIDIA team member to trigger CI again

CI Agent Failure Analysis

Link to invocation

[JunyiXu-nv]

/bot run --disable-fail-fast

[tensorrt-cicd]

PR_Github #79183 [ run ] triggered by Bot. Commit: 260b0a3 Link to invocation

[tensorrt-cicd]

PR_Github #79183 [ run ] completed with state SUCCESS. Commit: 260b0a3
/LLM/release-1.3/L0_MergeRequest_PR pipeline #394 completed with status: 'SUCCESS'

CI Report

Link to invocation

[JunyiXu-nv]

@brnguyen2 As promised, the cherry-pick of this fix to main is #20698.