Oliver Kieselbach e7ea431ccf feat(esp): recovery story for terminally reported ESP failures (session 4910a5a5)
DeviceSetup/Apps failed, the user pressed "Try again" ~23 min later, apps
recovered to 10/10 and DeviceSetup resolved - yet the advisory_completion
window un-defanged the stale failure and failed the live enrollment,
because the advisory variant was exempt from all re-arm/rebase guards.

Engine fix (DecisionCore):
- New facts EspAdvisoryFailureResolvedUtc + EspAdvisoryFailureCategory
  (state-borne; deadline payload would be lost on re-arm/rebase).
- TryResolveAdvisoryOnCategoryRecovery in both ProvisioningComplete
  handlers: category match sets the fact + emits
  esp_failure_advisory_resolved.
- Guards now (!hasAdvisoryAnchor || advisoryResolved): enforcement-progress
  re-arm, hello-never-observed promote and the reboot rebase apply again
  once the failure demonstrably un-happened; unresolved advisories keep
  the legacy un-defang exactly.
- Truthful terminal reason esp_recovered_without_completion_evidence
  (+ failureRecovered=true, LastFailureTrigger=DeadlineFired so the
  likely-stuck app promotion stays off).

Story events (agent tracker):
- esp_failure_retry_detected: failed subcategory leaves "failed" after the
  terminal fire - consistent with the user pressing "Try again".
- esp_failure_recovered: previously failed category reaches success.
- EspFailureDetectedEventArgs.LikelyCulpritApps (never-started first,
  cap 3) rides the EspTerminalFailure payload so esp_failure_advisory /
  enrollment_failed name the culprit app directly.

Surfacing: MCP resource-catalog, web timeline badges (Recovered /
User retry pills, culprit chip on advisory), gather-rule autocomplete,
ANALYZE-ESP-006 "ESP Failure Recovered After User Retry".

Tests: AdvisoryRecoveryTests (13, incl. the 527/611/635/671 field-ordinal
replay that no longer fails the session), EspFailureRecoveryStoryTests (5),
snapshot-builder guards 18 -> 20. All suites green (DecisionCore 493,
V2.Core 2018, Backend 3201, web vitest 589, MCP 449 incl. drift).

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-07-23 17:03:44 +02:00
2026-03-26 07:02:33 +01:00
2026-07-20 20:52:56 +02:00

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.

Private Preview

Autopilot Monitor is currently running as a Private Preview. Visit autopilotmonitor.com to request access and learn more.

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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