Three root causes for "no metrics" on the training dashboard:
1. Dashboard template variables ($model, $fold) sourced from
foxhunt_training_current_epoch which isn't emitted until the first
epoch completes. Switch to foxhunt_training_step which fires from
step 500 onward.
2. train.sh pod template missing Prometheus annotations
(prometheus.io/scrape, port, path). Also add the
app.kubernetes.io/component label to the eval manifest so
evaluation pods are discoverable too.
3. DQN and PPO trainers only called set_epoch() at the END of each
epoch. Move the call to the TOP of the epoch loop so the gauge
exists from the first training iteration.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Remove phantom foxhunt_training_total_epochs reference (never registered)
and replace with foxhunt_training_step from the recent metrics commit.
Add full coverage for all 52 Tier-1 Prometheus metrics across 5 new rows:
RL diagnostics (Q-overestimation, PPO entropy/KL/advantage), training
health (NaN/grad explosion/feature errors, checkpoint ops, data load
latency), epoch returns, supervised eval (accuracy/precision/recall/F1),
and hyperopt details (mode, trial epoch, failed trials).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Adds a `source` template variable to the training dashboard that controls
which Prometheus job labels are queried:
- Live: only `training-pods` (running pods scraped directly)
- CI History: only `.*_baseline.*` (completed CI runs via pushgateway)
- All: both sources combined
All 37 panel queries now use `job=~"$source"` for consistent filtering.
Active Workers panel stays hardcoded to `job="training-pods"` since it
only makes sense for live pods. Template variable queries (model/fold
dropdowns) also respect the source selector.
Default is "Live" — dashboard shows only the currently running training
session with no pushgateway stale data contamination.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Stat panels (Active Workers, Current Epoch, Trial Progress, Elapsed, Best
Objective) showed conflicting values from pushgateway stale gauges overlapping
with live training pod metrics. Scoped all stat/gauge panels and template
variable queries to job="training-pods" so the dashboard reflects only the
currently running training session. Time-series panels remain unfiltered via
$model template variable scoping — dropdown only lists live models, so
historical pushgateway data is naturally excluded without explicit filtering.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Remove cuda from default features in ml-core, ml-dqn, ml-ppo, ml
- Propagate cuda feature from ml → ml-core/ml-dqn/ml-ppo
- CI compile-training already uses --features ml/cuda explicitly
- Fix MaxDD log format: {:.1}% → {:.3}% (was rounding 0.033% to 0.0%)
- Suppress unused_labels/unused_variables warnings for cfg(cuda) code
- Add CALLBACK_ENDPOINT env to ml-training-service deployment
- Fix Grafana active_workers query to use sum() with fallback
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Remove all hardcoded Y-axis min/max bounds (41 removals) — dynamic scaling
- Eliminate Hyperopt section: merge into Training Status + Run Summary
- Deduplicate trial progress (3 panels → 1 gauge + 1 stat)
- Combine ML Jobs + Errors into single panel
- Add Current Trial and Hyperopt Elapsed to status bar
- Add Best Objective Δ (deriv) trend indicator
- Smooth line interpolation + gradient fills on all timeseries
- Stacked area for Action Distribution, gradient fill for Replay Buffer
- Shared crosshair tooltips, consistent threshold colors
- Status bar: stat panels with sparklines, trial before epoch
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add clamp_max() to PromQL queries and hard Y-axis limits to prevent
early-epoch degenerate values from blowing up panel scaling (Sharpe
showing 12 instead of 1.3, Profit Factor at 30k).
Run Summary: clamp_max on Best Val Loss (5), Sharpe (5), Profit Factor (20)
Training Quality: clamp_max on Epoch Sharpe (5), Sortino (10), PF (20)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Replace stat panels with timeseries using smooth line interpolation,
gradient fill, and multi-tooltip. Layout changed from 6x1 to 3x2 grid.
Legends show model/fold only when multiple series exist.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add 6 stat panels showing overall training run metrics: Best Val Loss,
Best Sharpe, Best Win Rate, Min Max Drawdown, Total Epochs, and Best
Profit Factor. Placed between Training Status and Training Curves rows.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Remove duplicate annotated-pods and gitlab-annotated-pods scrape jobs
(all targets already covered by dedicated jobs)
- Drop Argo controller from foxhunt-services job (dedicated HTTPS job exists)
- Resolve datasource variable placeholders to actual UIDs in dashboard JSON
- Add Ingress rule to Prometheus netpol allowing Grafana on port 9090
Targets: 49 → 18 (zero duplicates)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
