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AutoMonOPEARLY ACCESS
Capabilities Matrix

Autonomous Cloud Ops, Built for Scale

Explore the comprehensive feature set of AutoMonOP. From local edge agents to multi-cloud orchestration and AI-driven incident management.

Predictive AIOps & Anomaly Detection

AutoMonOP computes real-time EWMA (Exponentially Weighted Moving Average) and Z-Scores over memory usage, API latency, and CPU spikes. The predictive engine spots linear resource exhaustion trends up to 48 hours in advance, allowing engineering teams to act proactively before alerts become outages.

  • ✓ Multi-window variance detection (5m, 1h, 24h)
  • ✓ Automated risk confidence scoring
  • ✓ Integrated trajectory charts and sparklines
// Predictive Trajectory Calculation
EWMA_α = 0.35 | Z_SCORE = +2.84σ
⚠ PREDICTION: Memory pool saturation in 14h 22m
✔ AUTO-REMEDIATION: Scale Railway replica +1

Autonomous Claws & AI Agents

Claws are specialized autonomous background agents running inside AutoMonOP. They execute periodic audit scans, verify DNS propagation, trigger database cleanup runbooks, and interface with AutoMono Lisa or LLM providers to resolve operational tasks without human intervention.

  • ✓ Configurable trigger intervals and timeout budgets
  • ✓ Safe dry-run and approval gate modes
  • ✓ Full audit trail chained in Postgres
// Active Claws Registry
• claw-db-vacuum: ACTIVE (last run 4m ago)
• claw-ssl-check: HEALTHY (cert valid 82 days)
• claw-cache-evict: IDLE (memory normal)

Real-Time Incident War Room

When incidents trigger, AutoMonOP spins up a dedicated War Room powered by live WebSockets. All operators and responders receive instantaneous timeline updates, correlated telemetry streams, and runbook suggestions in real time.

  • ✓ Low-latency WebSockets with keep-alive heartbeat
  • ✓ PagerDuty & On-Call schedule synchronization
  • ✓ Post-mortem export with correlated metric timelines
// Live War Room WebSocket Stream
WS /api/v1/incidents/ws CONNECTED
[23:19:04] Incident #INC-104: Edge proxy degraded
[23:19:12] On-call engineer assigned: @frankfurt-ops

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