monitoring: scrape KEDA operator metrics#726
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Stack from [ghstack](https://github.com/ezyang/ghstack/tree/0.15.0) (oldest at bottom): * pytorch#727 * pytorch#728 * pytorch#726 * pytorch#725 * __->__ pytorch#724 Same min per arch as staging (amd64 2 / arm64 4). Max sized from 14-day docker-build concurrency: amd64 128 (peak 105 + headroom), arm64 16 (peak 8, likely capped by the old fixed pool).
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Stack from [ghstack](https://github.com/ezyang/ghstack/tree/0.15.0) (oldest at bottom): * pytorch#727 * pytorch#728 * pytorch#726 * __->__ pytorch#725 Burst 8 parallel buildctl builds per arch (each holds a maxconn=1 slot ~10m via sleep). With amd64_min=2 they serialize ~43m > timeout 30m and fail unless KEDA scales the pool up; one wave ~18m when it does.
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Stack from ghstack (oldest at bottom):
Enable the KEDA operator's Prometheus endpoint (prometheus.operator.enabled)
and add a ServiceMonitor scraping keda_* (scaler/scaledobject values, errors,
activity, latency) at 60s. Lets us see what KEDA reads and when it errors /
falls back.