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[TRTLLM-14510][feat] BREAKING: serve: default num_serve_frontends to 8 with single-frontend fallback - #19379
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| Layer / File(s) | Summary |
|---|---|
Frontend resolution and validation tensorrt_llm/commands/serve.py |
The CLI default is eight frontends. The serving command resolves the effective count after applying configuration overrides. For listed incompatible configurations, an implicit count falls back to one. Explicit values remain subject to configuration validation. |
Documentation and behavior coverage docs/source/commands/trtllm-serve/trtllm-serve.rst, tests/unittest/api_stability/references/trtllm_serve_cli.yaml, tests/unittest/llmapi/test_serve_num_frontends_default.py, tests/unittest/llmapi/apps/openai_server.py, tests/integration/test_lists/test-db/l0_cpu.yml |
Documentation and the CLI reference describe the default and constraints. CPU tests cover count resolution and launch behavior. The remote OpenAI test server adds a single-frontend option unless an explicit count is detected. |
Priority:
Estimated code review effort: 3 (Moderate) | ~20 minutes
Change: Feature
Sequence Diagram(s)
sequenceDiagram
participant CLI
participant ServeCommand
participant Configuration
participant launch_server
CLI->>ServeCommand: Provide frontend options
ServeCommand->>Configuration: Apply CLI and configuration overrides
ServeCommand->>ServeCommand: Resolve effective frontend count
ServeCommand->>launch_server: Pass resolved frontend count
Possibly related PRs
- NVIDIA/TensorRT-LLM#19394: Changes runtime behavior for multiple frontends, including launcher-owned routing and shared metrics handling.
Merge Risk: 
cb2ae
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Resolve the duplicate-registration risk before merging. Default deployments also expose frontend-local /metrics results rather than server-wide results; users who need server-wide metrics can explicitly select one frontend while that behavior is addressed.
Pre-merge checks: 
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Check name Status Explanation 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. Description check The description clearly explains the motivation, implementation, fallback behavior, limitations, documentation updates, and verification results. It does not include explicit "Test Coverage" or "PR Ch… Title check The title clearly identifies the breaking change: num_serve_frontendsdefaults to 8 with single-frontend fallback. This matches the main pull request objective.Full details: Description check
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Explanation
The description clearly explains the motivation, implementation, fallback behavior, limitations, documentation updates, and verification results. It does not include explicit "Test Coverage" or "PR Checklist" sections, but the required testing information is provided in the Verification section.
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In `@tensorrt_llm/commands/serve.py`:
- Line 1562: Add a CPU CLI regression test in
test_serve_num_frontends_default.py that loads num_serve_frontends: 8 from YAML,
invokes the --grpc path, and asserts the --num_serve_frontends must be 1 error;
retain existing YAML merge and default-fallback coverage.
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Two things need resolving before this can be the default.
CI test helpers don't pin the old default. tests/unittest/llmapi/apps/openai_server.py:54 launches trtllm-serve on a fixed free port with no --num_serve_frontends, so every suite built on RemoteOpenAIServer now runs 8 frontends. That includes L0 pre-merge cases whose semantics this PR's own description says change with >1 frontend: test_openai_responses (l0_h100) exercises previous_response_id, which multi-frontend mode force-disables, and test_openai_prometheus (l0_a10) reads series that become per-frontend. Please pin --num_serve_frontends 1 in the helper (or in those suites) and add explicit coverage for the 8-frontend path, and budget for 8 Python processes × tokenizer per served model on CI hosts.
Tracking + status. The label is api-breaking and the title is [None] — a default flip that changes process topology for every trtllm-serve user warrants a JIRA. Separately, --num_serve_frontends is still declared status="prototype" and the docs call it that; making a prototype the default path for all users is worth an explicit decision — either promote the status or hold the default.
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Inline comments:
Review comments at @tensorrt_llm/commands/serve.py:
- Around line 544-545: Update the validation in launch_server so an explicit
multi-frontend count is rejected when it conflicts with metadata-server or
disaggregated-cluster configuration, before any frontend children are spawned;
do not return early for requested before these checks. Add CLI tests covering
both explicit conflicts, including their error behavior.
Review comments at @tests/unittest/llmapi/apps/openai_server.py:
- Around line 33-36: Update the argument parsing that checks `--config` and
`--extra_llm_api_options` to recognize both separate-value and equals-form
options, extract the path in either form, and check the loaded YAML for
`num_serve_frontends` so `RemoteOpenAIServer` does not append a conflicting
default.
- Around line 79-80: Update the `_picks_num_frontends` check to determine the
effective `num_serve_frontends` value using the same config precedence as the
server constructor, while preserving explicit CLI and `--set` values. Add a test
where `cli_args` and `extra_config` specify different configs, verifying the
single-frontend flag is added when the effective config omits the setting.
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docs/source/commands/trtllm-serve/trtllm-serve.rsttensorrt_llm/commands/serve.pytests/integration/test_lists/test-db/l0_cpu.ymltests/unittest/api_stability/references/trtllm_serve_cli.yamltests/unittest/llmapi/apps/openai_server.pytests/unittest/llmapi/test_serve_num_frontends_default.py
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PR_Github #81385 [ run ] triggered by Bot. Commit: |
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…tend fallback Make the plain `trtllm-serve` subcommand run 8 HTTP frontend processes against one executor by default (`--num_serve_frontends`, added in NVIDIA#16523). At high concurrency a single serving process is host-bound on its asyncio loop; several SO_REUSEPORT frontends remove that ceiling. - The LlmArgs field default stays 1: a bare LLM() has no HTTP frontends to fan out to and only trtllm-serve can spawn them, so trtllm-bench / eval / Python users do not pay for the multi-frontend IPC topology. Because 8 != 1 the CLI value survives get_llm_args's default filter; a YAML `num_serve_frontends: 1` still overrides the untyped CLI default. - When the count comes from the default and the configuration can only run one frontend (--port 0 / --report_addr, orchestrator_type, enable_resource_governor, --enable_sleep_mode) or serves gRPC, log why and run 1 frontend instead of failing at startup. An explicit --num_serve_frontends > 1 keeps the loud error. - api_stability reference, new CPU tests (l0_cpu), docs section. Signed-off-by: Lance Liao <108499334+lancelly@users.noreply.github.com>
… default The default and its fallback are covered by the api_stability CLI gate and the e2e runs; keep the PR to the behaviour change. Signed-off-by: Lance Liao <108499334+lancelly@users.noreply.github.com>
- Fall back to one frontend by default with --metadata_server_config_file or a disagg cluster: every frontend registers the server under its own process identity (llm_id, DisaggClusterWorker id), which would list one server once per frontend. - Restore tests/unittest/llmapi/test_serve_num_frontends_default.py (l0_cpu): every fallback reason, explicit counts reaching the guard that rejects them, CLI / YAML / --set precedence down to the arguments launch_server receives, and a YAML count with --grpc being rejected. - RemoteOpenAIServer keeps test servers at one frontend unless the test picks the count (flag, --set, extra_config or YAML). Signed-off-by: Lance Liao <108499334+lancelly@users.noreply.github.com>
Drop tests that restate main's behavior or are already covered by test_llm_args.py and test_grpc_optional.py, merge the CLI cases into one table, and shorten comments. No behavior change. Signed-off-by: Lance Liao <108499334+lancelly@users.noreply.github.com>
…t with SO_REUSEPORT Every frontend binds the serving port with SO_REUSEPORT, which lets any socket of the same user that also sets it join the port. With several frontends by default, a second trtllm-serve started on a busy port would silently share the first server's traffic instead of failing. The launcher now probes the port with a plain bind (any listener makes it fail; TIME_WAIT leftovers do not) and holds an abstract Unix socket named after the port while it serves, which also covers a second launcher that starts before the first one listens. Signed-off-by: Lance Liao <108499334+lancelly@users.noreply.github.com>
… state With NVIDIA#19394 merged, /metrics, /kv_cache_events, profiling and the Anthropic batches API are answered by the launcher for the whole server, and /prometheus/metrics covers every frontend. /perf_metrics no longer exists (per-request perf metrics go to per-process files). Signed-off-by: Lance Liao <108499334+lancelly@users.noreply.github.com>
…erver or disagg cluster The default fell back to one frontend with --metadata_server_config_file or a disagg cluster because every frontend registered the server under its own identity. With NVIDIA#19394 merged, only the launcher registers, so that fallback is no longer needed. Signed-off-by: Lance Liao <108499334+lancelly@users.noreply.github.com>
Shorten the port-guard docstring, the default's comment and the --num_serve_frontends help (the fallback list lives in the docs), and drop the disagg-cluster CLI case, which no longer differs from the default. No behavior change. Signed-off-by: Lance Liao <108499334+lancelly@users.noreply.github.com>
Write default=8 on the --num_serve_frontends option, as the neighboring options do, instead of a module constant. The tests use the literal; the api_stability reference already pins 8. Signed-off-by: Lance Liao <108499334+lancelly@users.noreply.github.com>
The option becomes the default path for every trtllm-serve user, so it should not stay a prototype. The LlmArgs field, which the LLM API keeps at 1, stays prototype. Signed-off-by: Lance Liao <108499334+lancelly@users.noreply.github.com>
Requests, streams, /metrics and /prometheus/metrics through 8 frontends on one Qwen3-0.6B engine, each on its own connection: every request finishes, the launcher drains the stats once, and every scrape counts the requests of all frontends. Runs in the single-GPU B200 pre-merge list (review: explicit coverage for the multi-frontend path). Signed-off-by: Lance Liao <108499334+lancelly@users.noreply.github.com>
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PR_Github #81396 [ run ] triggered by Bot. Commit: |
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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. |
Description
Follow-up to #16523 (
num_serve_frontends): make the plaintrtllm-servesubcommand run 8 HTTP frontend processes by default instead of 1.Motivation
At high concurrency a
trtllm-serveworker is host-bound on its single serving process: one asyncio event loop performs every requestjson.loads+ pydantic validation and every SSE chunk write. #16523 measuredgen_preprocessingp50 54 ms @ c512 → 109 ms @ c1024 → 1520 ms @ c2048 on a DSv4 disagg GEN worker while decode step time stayed flat; running several frontends behind oneSO_REUSEPORTport removes that ceiling. The knob has been the production setting in our agentic disagg configs (8 on CTX, 4 on GEN) since then; this PR makes users get the benefit without knowing the flag.What changes
--num_serve_frontends(serve subcommand) default1 → 8(DEFAULT_NUM_SERVE_FRONTENDSincommands/serve.py).LlmArgs.num_serve_frontendsfield default stays 1. A bareLLM()has no HTTP frontends to fan out to and onlytrtllm-servecan spawn them; keeping the field at 1 meanstrtllm-bench,trtllm-evaland PythonLLM()users do not pay for 8 result lanes / the multi-frontend IPC topology. Because8 != 1, the CLI value survivesget_llm_args's default filter and reaches the executor;num_serve_frontends: 1in the--configYAML still overrides it (YAML wins over an untyped CLI default).--grpc,--port 0/--report_addr,orchestrator_type(rpc/ray),enable_resource_governor—trtllm-servenow logs why and runs 1 frontend instead of failing at startup. An explicit--num_serve_frontends N>1with such a config still raises, as before (_resolve_default_num_serve_frontends). The--grpcguard now checks the resolved value so the fallback applies there too.--num_serve_frontends 1).tests/unittest/api_stability/references/trtllm_serve_cli.yaml:serve.num_serve_frontends.default: 8(the gate fails on the stock reference withdefault drift: code=8 vs yaml=1, verified).docs/source/commands/trtllm-serve/trtllm-serve.rst(default, opt-out, fallback rules, per-frontend state caveats).Behaviour users must know (limitations inherited from #16523, now on by default)
store/previous_response_id) is disabled with >1 frontend (per-process in-memory store). Opt out with--num_serve_frontends 1./metrics,/perf_metrics,/healthand/prometheus/metricsare answered by whichever frontend accepted the connection. Withreturn_perf_metricson, every frontend runs its own iteration-stats collector loop, so the engine's iteration stats are drained per frontend (each sees ~1/K of them) and both the JSON/metricsbuffer and the iteration-derived Prometheus series (KV-cache gauges,trtllm_num_requests_completed_total, iteration latency) reflect only the answering frontend's share; request-level Prometheus series (trtllm_request_success_total, TTFT/E2E histograms) live in per-process registries becausePROMETHEUS_MULTIPROC_DIRis created inOpenAIServer.__init__, after the children are spawned. A scraper therefore sees one frontend's share per scrape and counters appear to reset between scrapes. Withoutreturn_perf_metrics,/metricsdrains the engine queue on demand over RPC and the answering frontend returns everything queued, as today. Cross-frontend aggregation (shared multiproc dir set before spawning + gaugemultiprocess_mode, or a single collector in the launcher) is follow-up work;--num_serve_frontends 1restores today's numbers.disaggregated_mpi_worker,disaggregatedfleets),mm_embedding_serveand VisualGen are unaffected (the knob is ignored or absent on those entry points).Verification
pre-commit runpasses on all changed files.Container
gb300-917ad7b3e9(1.3.0rc26 + this patch applied tocommands/serve.py), 1× GB300, Qwen3-0.6B, launched the way this cluster runs production (srun --mpi=pmix … trtllm-llmapi-launch trtllm-serve …):trtllm-serve <model> --config metrics.yaml… --num_serve_frontends 1 --config metrics.yaml… --config rpc.yaml(orchestrator_type: rpc, no flag)… --num_serve_frontends 8 --config rpc.yamlValueError: num_serve_frontends > 1 requires the default (classic IPC) executor pathThe fallback case logs
num_serve_frontends defaults to 8, but orchestrator_type='rpc' supports a single serving frontend only; running 1 frontend. Pass --num_serve_frontends explicitly to override.and its/prometheus/metricscounters are complete (16/16) like the opt-out case.BaseLlmArgs.model_fields["num_serve_frontends"].default= 1,--helprenders the new text.api_stability/test_serve_cli.pypasses with the updated reference and fails on the stock one with[serve] option --num_serve_frontends field default drift: code=8 vs yaml=1. The fallback resolver was additionally exercised by a throwaway CPU test (every condition → 1, explicit request → unchanged + ValueError) that is not part of the PR.nvidia-smi --query-compute-appslists only the worker (58.7 GiB incl. KV cache) and the launcher (748 MiB) in both cases.GET /metricsreturned[0,1,0,0,0,0,18,19,0,…]iteration stats over 16 polls;GET /prometheus/metricsshowed 5 distincttrtllm_request_success_totalvalues (6 / 7 / 8 / 10) across 32 scrapes, versus a constant 32/32 with one frontend — the per-frontend sampling described above.trtllm-serveprocesses left.