Oliver Kieselbach
55c898bb9c
Insights expansion PR2 (tasks/insights-expansion-spec.md §F1 "Data & compute
changes"):
- SessionTimeBreakdowns table (PK=TenantId, RK=SessionId): span/reboot/
blocking-app JSON columns, QualityFlags, AttributionVersion,
EspAppsOccupancySeconds kept tri-state (absent column = unknown, never 0).
Written once at the terminal single-writer seam (TableSessionRepository,
next to the counter reconcile + EspBlocking resolution; Succeeded/Failed
only — Incomplete deliberately stores no duration). Deleted with its
session: new deletion-manifest step 16 (PkRkExact; tombstone moves to 19)
plus tenant-offboarding partition wipe — no separate age sweep.
- Self-healing 30d maintenance sweep instead of a one-off backfill (rides
the existing 2h tick + manual parity): backfills pre-deploy sessions,
heals inline-compute misses, folds late-terminating sessions into their
StartedAt-date aggregates, and enforces AttributionVersion purity — a
stale-version breakdown whose events aged out counts as missing rather
than mixing algorithm semantics (truthfulness rule 8). Skips sessions
with a deletion cascade in flight.
- TimeAttributionAggregates table (PK=TenantId or "global",
RK="{date}|{class}"): per enrollment class (whiteglove /
device_preparation / self_deploying / user_driven — never mixed),
median/p75/p90 per segment over the fixed six-segment stack (incl.
unattributed; absent segment = honest 0), clean/flagged/missing counts
disclosed (rule 7), rows written below the n>=20 UI gate on purpose
(the UI needs the n — rule 4). 180d retention alongside UsageMetrics.
- What-if bound: WhatIfSavingSeconds implements the spec formula
max(0, cpEnd - cpEndWithoutX) including the idle gap before X (the ESP
waits for X to start, too); sole-interval fallback = own start. Per-app
aggregate rows gate at >=5 sessions, top 20 by median interval, carry
median/p75 of interval and saving ("up to" wording is the consumer
contract).
Backend 3381/3381 (13 new tests: entity round-trips incl. tri-state,
aggregation bucketing/disclosure/gates, what-if vectors, class precedence,
manifest step-count pins 17/19), solution build clean, web untouched.
Co-Authored-By: Claude Fable 5 <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.
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.