[Bug]: engine:status re-runs the readiness probe under the engine lock on every call; a slow engine /health starves the model-list sweep and, polled ~1/s, leaked a TP=4 head to death
@kjlubick đang làm issue này rồi.
Từ ngày 18/9/2026.
Đánh giá
Issue này chưa được đánh giá.
Mô tả
Area
Engine or model management
User problem
Every engine:status call re-runs the engine's readiness probe while holding that engine's lifecycle lock, and several PAIR components poll status independently. On an engine whose readiness endpoint is cheap that is invisible. On an engine whose /health does real work it has two consequences we hit in production this week on a 4-node tensor-parallel SGLang head (DGX Spark, GB10):
- Model-list starvation. The broker's advertiser (every 5 s), the loaded-model watcher (every 5 s) and the desktop's remote status poll (every 10 s) each call
engine:status.StatusAtPorttakesst.opMu, thenreconcilePresencerunsprobe(ready)andprobe(identity)with no caching. SGLang's/healthperforms a short generation and takes ~1.0 s on this build, so the mutex was held essentially 100% of the time andModelsResult's sweep (which needsStatusfirst) never got in.GET :14322/v1/modelson that node hung for 40 s+ indefinitely; peers piled up hundreds of CLOSE-WAIT sockets; the desktop loggedremote engine status ... unavailableevery 10 s. A standalone engine-manager with no broker traffic answered in 16 ms. Restarting engine-manager did not help. - The probe load itself leaked memory. The head's container log shows 72,144
GET /healthand 69,817GET /get_model_infoover a 20 h run, ~1/s each, with zero user requests for the final 30 min. The head's MemAvailable declined monotonically from 8.7 GB (00:20) to 2.5 GB (16:20) while the three worker ranks stayed flat, then earlyoom SIGTERMed the scheduler at 16:28 and the TP group died. After the crash the head returned to its idle baseline, so the growth was inside the front-end processes only rank 0 runs. Pointing the probes at/get_model_info(~1 ms, no generation) dropped/healthtraffic from ~3,500/h to the container's own healthcheck and the model list answers in 13 ms.
SGLang itself is not in develop yet (it lives in #50 and in my fork), but the mechanism is upstream code and applies to any engine whose readiness endpoint is not free; llama.cpp's /health under load and /v1/models on busy servers are candidates.
Where
services/nvpair-engine-manager/status.go:StatusAtPort→st.opMu.Lock()→reconcilePresence(context.Background(), ...)→e.probe(ctx, ready, port)thene.probe(ctx, identity, port)on every call.services/nvpair-engine-manager/models.go:ModelsResultcallse.Status(name)per engine before the 5 s action budget starts; the lock wait is unbounded.- Pollers:
nvpair-ui-broker/advertiser.go(autoAdvertiseInterval = 5 * time.Second),nvpair-engine-manager/loadedwatch.go(defaultLoadedPollSeconds = 5), the desktop's remote-get-installed loop.
Proposed fix
- Do not re-run the readiness probe for an engine that is already adopted and healthy with a live health loop; trust the health loop's last result, or cache presence for a few seconds.
- Do not take
opMufor the read-only status path; snapshot state, probe outside the lock. - Treat the manifest's
identityendpoint as the default readiness/health probe and require an explicit opt-in for anything that generates.
Workaround for operators
A per-engine manifest override (engines/sglang.json) pointing runtime.ready.http and runtime.health.http at /get_model_info, plus the advertiser change in https://github.com/jlacroix82/Personal-AI-Router/commit/c5b9be7 (on feat/vllm-sglang).
Environment
PAIR 0.1.1 services (engine-manager 0.21.0 / broker 0.42.2 as built from feat/vllm-sglang at ff26f5b), Linux arm64, DGX Spark x4 per TP group, SGLang lmsysorg/sglang:dev-dsv41 serving DeepSeek-V4.1-Flash. Related: #37 (probe connection reuse), #50 (SGLang engine), #24 (external backends).
- Ngôn ngữ chính
- Go
- Star
- 1.4k
- Fork
- 250
- Merge trung bình
- 23 giờ 27 phút
- Pull request đã merge (30 ngày)
- 1
Hướng dẫn đóng góp
Bắt đầu từ đâu
- Đọc hết issue, rồi đọc hướng dẫn đóng góp của dự án.
- Bình luận trên issue rằng bạn sẽ nhận — tránh hai người làm cùng một việc.
- Fork repository và làm thay đổi trên một nhánh.
- Mở pull request có tham chiếu số hiệu của issue.
Issue khác của NVIDIA/Personal-AI-Router
-
bug
Độ khó 4/5 3-5 ngày Mức phù hợp với người mới 55/100
NVIDIA/Personal-AI-Router#94 · 1 bình luận ·
-
Độ khó 3/5 1-2 ngày Mức phù hợp với người mới 74/100
NVIDIA/Personal-AI-Router#92 · 1 bình luận ·
-
NVIDIA/Personal-AI-Router#91 · 1 người được giao ·
-
[Feature]: Support for Tailscale mesh network endpoints (CGNAT IPs and MagicDNS domain names) Đang mởenhancement
Độ khó 4/5 3-5 ngày Mức phù hợp với người mới 45/100
NVIDIA/Personal-AI-Router#85 · 1 bình luận ·
-
enhancement
Độ khó 4/5 3-5 ngày Mức phù hợp với người mới 52/100
NVIDIA/Personal-AI-Router#77 · 1 bình luận ·
Tất cả issue của NVIDIA/Personal-AI-Router
Issue tương tự
-
optimization optimization:agents-md-curator
Độ khó 2/5 1-3 giờ Mức phù hợp với người mới 86/100
githubnext/gh-aw-cao#13143 ·
-
Độ khó 2/5 1-3 giờ Mức phù hợp với người mới 84/100
blinklabs-io/bursa#904 ·
-
Độ khó 2/5 1-3 giờ Mức phù hợp với người mới 84/100
yanet-platform/ipfw-go#129 ·
-
bug confmap/provider/googlesecretmanagerprovider needs triage
Độ khó 2/5 1-3 giờ Mức phù hợp với người mới 72/100
open-telemetry/opentelemetry-collector-contrib#51273 · 2 bình luận ·
-
bug: AI Gateway client filter lists "Unknown" twice when NULL and literal Unknown clients coexist Đang mởbug
Độ khó 2/5 1-3 giờ Mức phù hợp với người mới 90/100