Sys.Op. Active

Aegis // MLOps

Telemetry // Always-on

Monitor, Detect, Maintain

Models silently degrade. Production monitoring catches latency regressions, data drift, and concept shift before they reach users — and triggers the retraining loop.

Live Telemetry

Endpoint: fraud-detector-v4
p99 Latency
62ms
SLO < 80ms
Throughput
14.2k/s
SLO > 10k/s
Error Rate
0.04%
SLO < 0.1%
Drift Score
0.18
SLO < 0.20 ⚠

Four Layers of Monitoring

Infra · Data · Model · Business

Infrastructure

CPU, GPU, memory, network, replica health. Standard SRE telemetry — Prometheus + Grafana.

Data Quality

Schema violations, null spikes, range checks, and feature distribution drift versus training.

Model Quality

Prediction distributions, confidence calibration, and ground-truth accuracy when labels arrive.

Business KPIs

Click-through, conversion, fraud catch-rate. The metrics the model actually exists to move.

Maintenance Loop

Detect → Diagnose → Retrain → Promote
  1. Step 01DETECTDrift monitor fires on KL > 0.2
  2. Step 02DIAGNOSESlice analysis isolates affected segment
  3. Step 03RETRAINPipeline triggers on fresh window
  4. Step 04PROMOTEChampion/challenger eval gates rollout