Voidly Atlas now exposes 30+ live ML endpoints — forecast (7d, multi-horizon, TFT, zero-shot, region, platform, domain, ASN-GNN, duration, trajectory, hourly), classifier (v3.3 + feature-importance + robustness), anomaly (DBSCAN, IsolationForest, per-domain HDBSCAN drift), per-measurement classifier, plus the sentinel transparency family (accuracy, feature-importance, global heatmap, calibration-drift, prediction-track-record). For a journalist who just wants to know “is the model live and working right now?” that's 30+ separate curl commands.

This dashboard collapses them into a single answer.

What it measures

Every day at 04:00 UTC a cron on Vultr runs scripts/build-serving-reliability.py. For each endpoint it:

• fires 10 probes over a ~2-minute window directly at 127.0.0.1:5002 (forecast_api.py upstream)
• computes HTTP availability (% probes returning 2xx)
• computes p50 + p95 latency over the successful probes (note: noisy at n=10 — intentional)
• parses the JSON body and runs a top-level-keys superset check against the expected schema
• computes model staleness from the most recent of either a declared trained_at field in the sidecar or the sidecar file mtime
• records whether the response surfaces an honest_caveats field (Voidly's standard for ML transparency)
• for forecast/sentinel groups, pulls the latest global calibration drift from forecast_calibration_refit.json

Promote criteria

• ≥ 25 endpoints probed successfully (one of the published summary numbers)
• The dashboard is honest about endpoints that 500'd or timed out — failures are not hidden, they're surfaced in summary.worst_availability and per-endpoint errors dict.

Honest caveats

• 10-probe sample window is small. p95 latency at n=10 is dominated by tail noise. Treat it as a smoke signal, not a contract.
• Doesn't measure tail-of-distribution failures. A daily snapshot misses 5-minute blips during peak load.
• Probes hit localhost upstream. CF gateway / DNS / TLS issues are not detected here — that's a separate health check.
• Schema check is a fingerprint, not a full JSON-schema validation. We confirm the expected top-level keys are present (case-insensitive), not their nested shape.
• MCP server endpoints are excluded. They run on a separate Node.js runtime and have their own publish process.

Live at

GET /v1/atlas/serving-reliability — full sidecar JSON
GET /v1/atlas/serving-reliability?group=forecast — filter by group
GET /v1/atlas/serving-reliability/info — metadata + caveats