Oliver Kieselbach
0a0c323f73
Three CmTraceTimeSkewRegression fires on 2026-09-01 (one tenant, sessions e797117b / c06d639d / d7c8032b, agent 2.0.1445, each exactly -60.0 min, residual 0.0, 85-88 % grid-conformant) all came from the same stale leg: those sessions are pre-provisioning, their Part 1 ran on 2026-08-20 under agent 2.0.1409 (before per-line anchoring) and left 23-26 IME samples at -60.00, while the Part 2 leg that completed that morning is clean at -0.16. The terminal reconcile scans the whole event partition, so the old leg supplied the majority of the IME samples and fired against a build the device had self-updated to minutes earlier. Real skew, 12 days old, already fixed - and >=821 pending pre-provisioning sessions with agent < 1412 are queued to repeat it. Event rows carry no agent version, so the split is drawn on ReceivedAt: ResolveEraStartUtc walks the batch stamps of BOTH sides back from the newest one and ends the era at the first gap > EraGapHours (2.0) - above any in-leg upload gap (self-metrics every few minutes, session_stalled at 60 min idle, maintenance sweep at 2 h), below every pre-provisioning handover. Median, grid residual, conformity AND the distinct-batch guard now all run on the same era-filtered sample set; the batch counters used to come from the full scan. SessionSkewScan carries ReceivedAt per sample and its 20k cap keeps the NEWEST samples (chunked trim) - keeping the head would have blinded the detector on exactly the sessions large enough to reach it. The ops event reports eraStartUtc plus the excluded per-side counts, so an inherited leg stays visible without being alarmed on. Tests: 3 new era facts, mutation-proven (EraGapHours = 100000 turns exactly those three red). The handover fact also asserts that the old leg judged on its own still fires, so it is the window that silences it, not a moved threshold. Backend 5334 green, Agent core 2805 green, solution builds with 0 warnings. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
AutopilotMonitor
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.