Oliver Kieselbach 72136f0273 backend+mcp+web: evaluateOn interim triggers for analyze rules
Implements docs/rules/analyze-rule-triggers.md (spec approved today):

- AnalyzeRule.EvaluateOn (absent = [enrollment_end], today's behavior bit-for-bit)
  with the shared AnalyzeRuleTriggers grammar/matching helpers; grammar enforced
  in tenant rule CRUD and the analyze-rule JSON schema.
- RuleEngine: AnalyzeRunContext (Terminal/Interim/Reanalyze), interim rule filter,
  KO suppression on interim runs, and RuleResult update-semantics replacing the
  permanent dedupe freeze — interim rows refresh, the terminal pass finalizes or
  resolves them (ResolvedAt, kept for audit), Reanalyze preserves lifecycle markers.
- Notification dedupe moves onto RuleResult.NotifiedAt (one send per session+rule,
  stamped after a successful send; survives the manual reanalyze rebuild).
- Handler: whiteglove_sealed / interim_trigger reasons — notify + SignalR yes,
  IssuesDetected + rule stats terminal-only (Rule Regression Radar baselines clean).
- Ingest: InterimTriggerRegistry (per-tenant 5-min TTL cache, fail-soft) gates the
  interim_trigger enqueue (batch eventType intersection) and the whiteglove_sealed
  enqueue on the first genuine WhiteGlove seal.
- Storage: EvaluateOnJson on AnalyzeRules; FirstDetectedAt/LastEvaluatedAt/
  IsInterim/ResolvedAt/NotifiedAt on RuleResults (nullable — legacy rows read as
  final).
- MCP: three authoring lints (terminal-precondition trap, unknown/high-frequency
  on_event types, KO-on-interim), authoring guide + baked schema updated;
  get_session_summary marks interim and excludes resolved findings.
- Web: preliminary badge on interim findings, resolved findings behind a toggle,
  issue counts exclude resolved (analysis section + diagnosis flow).
- ANALYZE-ID-004 v1.1.0: first interim-enabled rule (on_event:hybrid_login_pending),
  threshold raised to 75 so only repeated overdue-login signals fire mid-run.

Suites: Backend 4152, MCP 548, Web 762 + tsc + lint clean.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-08-14 15:53:02 +02:00
2026-08-06 13:53:56 +02:00
2026-07-29 16:00:17 +02:00
2026-03-26 07:02:33 +01:00

AutopilotMonitor

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Advanced monitoring and troubleshooting solution for Windows Autopilot deployments. Gain full visibility into every enrollment session with a detailed event timeline, fleet health dashboards, and session reporting. Define custom analysis rules to automatically detect issues and gather rules to collect targeted evidence. Retrieve diagnostics packages on demand, configure agent settings like auto-reboot behavior and automatic timezone adjustment — all managed centrally from the web dashboard.

Availability

Autopilot Monitor is publicly available — the Community plan is free. Sign in with your work account at autopilotmonitor.com; new organizations complete a short activation step after first sign-in.

Overview

Autopilot Monitor provides real-time tracking, intelligent diagnostics, and automated troubleshooting for Windows Autopilot enrollment processes. It consists of:

  • Bootstrap Script — PowerShell script deployed via Intune that starts monitoring early in the enrollment process
  • Monitoring Agent — Lightweight .NET application that collects telemetry and evidence during enrollment
  • Backend API — Azure Functions-based ingestion and processing pipeline
  • Web Dashboard — Next.js application for real-time monitoring and fleet analytics

Architecture

For detailed information about the system architecture, components, and data flow, see Architecture Documentation.

Documentation

Full admin documentation is available at docs.autopilotmonitor.com

License

This project uses a split licensing model:

  • MIT License — Agent (src/Agent/) and Shared library (src/Shared/) — unrestricted use on end-user devices
  • AGPL-3.0 — Backend (src/Backend/), Web Dashboard (src/Web/), and MCP Server (src/McpServer/) — server-side components remain open source

See LICENSE for full details.

S
Description
Windows Autopilot & Intune enrollment monitoring: live session timelines, fleet health, diagnostics, and an MCP server for AI-assisted troubleshooting.
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