Oliver Kieselbach
db7ca6ed87
Session 080edee9 fired only ANALYZE-ENRL-001 ("Enrollment Failed") with a
generic explanation, even though we already had all the data to point at
the specific failed app (Microsoft Apps for Enterprise) and the specific
HRESULT (0x87D1041C - Intune detection rule mismatch). Three coordinated
rule changes close that enrichment gap:
ANALYZE-APP-001 (Win32 App Detection Script Failure):
Switch from a regex on the `message` field (which never matched the
agent's "Install status unconfirmed - ESP timed out" wording) to a
direct check on `dataField: detectionResult, operator: equals,
value: NotDetected`. The rule engine already supports nested DataJson
fields on `event_type` conditions, so this is the right shape and the
rule now fires whenever the IME reported a detection-rule mismatch.
ANALYZE-APP-013 (App Detection Failure During ESP - 0x87D1041C, new):
Matches the canonical `failureType: esp_apps_detection_failure` tag
emitted by the V2 agent's new classifier. Severity=critical, baseConf=90.
Pulls failed appName + HRESULT into the explanation via the existing
`{{token}}` interpolator, and ships a three-step remediation plan:
(1) validate the detection rule against an installed reference device,
(2) investigate post-install async tasks (the install may complete only
after ESP's detection probe runs), (3) cross-check the per-app event's
detectionResult + bytesDownloaded + hresultFromWin32.
ANALYZE-ENRL-001 (Enrollment Failed):
Add optional conditions that capture {reason, failedSubcategory, errorCode,
failedApp.appName} into MatchedConditions so the explanation can resolve
`{{reason}}` / `{{failedSubcategory}}` / `{{errorCode}}` / `{{appName}}`
via the existing `interpolateRuleTemplate` engine. Remediation text now
cross-references ANALYZE-APP-* rules for the actionable root cause.
dist regenerated via `node rules/scripts/combine.js` (25 -> 26 rules).
Backend embeds dist/analyze-rules.json as a resource; next deploy picks up
the new content automatically.
Coverage: 2058/2058 backend tests pass.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Autopilot Monitor
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 documentation is available at autopilotmonitor.com/docs
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.