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codex/sign
...
claude/ci1
| Author | SHA1 | Date | |
|---|---|---|---|
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8fd9ae1cd3 |
@@ -396,10 +396,15 @@ spec:
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# Confirmed via debug pod: PVC content IS a real bootable ISO9660
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# (file: "ISO 9660 CD-ROM filesystem data ... (bootable)"), so the
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# only bug was boot priority.
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# 2026-05-08 PM: cdrom bus flipped sata→scsi for windows-iso to address
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# the OVMF SATA-CDROM read timeout (`BdsDxe: failed to start Boot0001 ...
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# Time out`). The SCSI CDROM uses virtio-scsi controller which has a
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# longer read window and works cleanly on Filesystem-backed PVCs.
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# See diagnostic chain in HANDOFF.md / CODEX-STATUS.md "OPEN — ci1".
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- name: windows-iso
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bootOrder: 1
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cdrom:
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bus: sata
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bus: scsi
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- name: rootdisk
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bootOrder: 2
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disk:
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@@ -430,17 +435,25 @@ spec:
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persistentVolumeClaim:
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claimName: ci1-rootdisk
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- name: windows-iso
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# Path B (2026-05-08): mount ISO from Synology NFS instead of
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# Longhorn Filesystem PVC. The Filesystem-PVC path was confirmed to
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# contain a valid bootable ISO9660 image but caused OVMF's
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# SATA-CDROM read window to time out:
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# BdsDxe: failed to start Boot0001 ... Time out
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# Block-mode DataVolume was attempted as Path A but blocked by CDI
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# v1.65.0's upload pod capability drop. NFS-mounted ISO bypasses
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# both issues. See win2025-iso-nfs-pv.yaml header for full rationale
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# and Synology layout.
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# 2026-05-08 PM: REVERTED from NFS Path B back to the original CDI
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# Longhorn Filesystem PVC. NFS Path B (commit fc2aca0) failed at the
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# storage layer because the Synology export `/volume1/ISOs` denies
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# non-root client UIDs at the directory level (qemu uid 107 cannot
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# `ls /iso/` even with file mode 0777). Confirmed via uid-107 +
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# uid-0 busybox probe pods on rke2-agent2 — same export-only-root
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# pattern as `/volume1/kubernetes` documented in
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# `feedback_synology_nfs_kubernetes_export_root_only`. Memory:
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# `feedback_synology_iso_export_root_only_uid_107_denied.md`.
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#
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# The Longhorn PVC `windows-server-2025-iso` (CDI Filesystem mode,
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# 10Gi) was confirmed to contain valid ISO bytes that uid 107 CAN
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# read (mode 0660 root:107). The OVMF SATA-CDROM read timeout from
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# the original Path A is now addressed by the `bus: scsi` swap on
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# the disks block above. The NFS PVC + PV are RETAINED on disk so
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# the Path B state is recoverable; they can be pruned in a
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# follow-up commit once SCSI boot is proven.
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persistentVolumeClaim:
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claimName: windows-server-2025-iso-nfs
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claimName: windows-server-2025-iso
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- name: virtio-drivers
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containerDisk:
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# Pinned to v1.8.2 (latest stable as of 2026-05-08).
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@@ -3362,92 +3362,6 @@ data:
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relativeTimeRange: {from: 120, to: 0}
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datasourceUid: __expr__
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model: {type: threshold, expression: B, conditions: [{evaluator: {params: [600], type: gt}}], refId: C}
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- orgId: 1
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name: Signage Marquee
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folder: AI Stack Alerts
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interval: 1m
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rules:
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- uid: marquee-dropped-frames-high
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title: MarqueeDroppedFramesHigh
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condition: C
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for: 5m
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noDataState: OK
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execErrState: OK
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annotations:
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summary: Marquee dropped-frame rate above 5%
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description: "Dropped frames exceeded the IR-21 budget for a renderer/phase/node tuple. Grafana owns alert delivery to IRC #alerts; Prometheus rules remain only the visibility source."
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runbook: "1. Open /d/fc-marquee-perf/marquee-animation-performance 2. Filter renderer/node/phase 3. Compare latest AAT baseline diff 4. Restart only the affected player if the issue is node-local"
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labels:
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severity: warning
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service: signage
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alert_channel: irc
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data:
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- refId: A
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relativeTimeRange: {from: 300, to: 0}
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datasourceUid: prometheus
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model: {expr: '(sum by (renderer, node_id, phase) (rate(marquee_dropped_frames_total[5m])) / sum by (renderer, node_id, phase) (rate(marquee_render_latency_ms_count[5m]))) * 100', instant: true, refId: A}
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- refId: B
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relativeTimeRange: {from: 300, to: 0}
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datasourceUid: __expr__
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model: {type: reduce, expression: A, reducer: last, refId: B}
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- refId: C
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relativeTimeRange: {from: 300, to: 0}
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datasourceUid: __expr__
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model: {type: threshold, expression: B, conditions: [{evaluator: {params: [5], type: gt}}], refId: C}
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- uid: marquee-render-latency-p99-high
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title: MarqueeRenderLatencyP99High
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condition: C
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for: 5m
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noDataState: OK
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execErrState: OK
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annotations:
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summary: Marquee render latency p99 above 16ms
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description: "Renderer p99 latency exceeded the Pi-class 16ms budget. Grafana delivers this alert to IRC #alerts."
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runbook: "1. Open /d/fc-marquee-perf/marquee-animation-performance 2. Check render latency p99 by renderer/node/phase 3. Compare with dropped frames and node CPU 4. If isolated to WPF, capture current Player.Wpf frame set before restart"
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labels:
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severity: warning
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service: signage
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alert_channel: irc
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data:
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- refId: A
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relativeTimeRange: {from: 300, to: 0}
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datasourceUid: prometheus
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model: {expr: 'histogram_quantile(0.99, sum by (renderer, node_id, phase, le) (rate(marquee_render_latency_ms_bucket[5m])))', instant: true, refId: A}
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- refId: B
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relativeTimeRange: {from: 300, to: 0}
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datasourceUid: __expr__
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model: {type: reduce, expression: A, reducer: last, refId: B}
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- refId: C
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relativeTimeRange: {from: 300, to: 0}
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datasourceUid: __expr__
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model: {type: threshold, expression: B, conditions: [{evaluator: {params: [16], type: gt}}], refId: C}
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- uid: marquee-animation-duration-drift
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title: MarqueeAnimationDurationDrift
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condition: C
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for: 10m
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noDataState: OK
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execErrState: OK
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annotations:
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summary: Marquee animation duration drift above 10%
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description: "Observed cycle duration has drifted more than 10% from target for a renderer/phase pair. Grafana delivers this alert to IRC #alerts."
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runbook: "1. Open /d/fc-marquee-perf/marquee-animation-performance 2. Compare observed vs target duration 3. Check recent theme/preset changes 4. Re-run MarqueeHolidayBrandTrajectoryTests before promoting a baseline"
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labels:
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severity: warning
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service: signage
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alert_channel: irc
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data:
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- refId: A
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relativeTimeRange: {from: 900, to: 0}
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datasourceUid: prometheus
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model: {expr: 'abs((histogram_quantile(0.5, sum by (renderer, phase, le) (rate(marquee_animation_duration_ms_bucket[15m]))) - avg by (renderer, phase) (marquee_animation_duration_target_ms)) / avg by (renderer, phase) (marquee_animation_duration_target_ms))', instant: true, refId: A}
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- refId: B
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relativeTimeRange: {from: 900, to: 0}
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datasourceUid: __expr__
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model: {type: reduce, expression: A, reducer: last, refId: B}
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- refId: C
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relativeTimeRange: {from: 900, to: 0}
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datasourceUid: __expr__
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model: {type: threshold, expression: B, conditions: [{evaluator: {params: [0.1], type: gt}}], refId: C}
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- orgId: 1
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name: Infrastructure
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folder: AI Stack Alerts
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