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AVD · /// End-to-End Monitoring

Know your AVD users are happy. Before the Azure invoice arrives.

LoadGen runs the same scenario engine in continuous mode — synthetic AVD sessions every minute, real-user DEM via SessionSight, and uptime checks across FSLogix, connection-broker, and AAD — all on one timeline. SLA-grade evidence for Azure spend defence.

See AVD UX from your users’ perspectiveTalk to an engineer

Synthetic + real-user DEMFSLogix + AAD telemetry€899 / Agent / month

Live cockpit — KPI freshness, session health, time-range scrub.

The Problem

Azure portal green. AVD users angry.

AVD monitoring is split across tools: Azure Monitor shows compute health, Microsoft DEX shows session metrics, your APM shows app health. None of them log in as a user and click — which is where AVD sessions actually break.

Three Microsoft tools, three blind spots.

Azure Monitor reports compute health. Microsoft DEX reports session metrics. Cloud PC Insights reports W365 health. None of them run a synthetic AVD user end-to-end with FSLogix capture.

FSLogix profile-load drift hides.

A 200 OK on the connection broker isn’t a working session. FSLogix profile-load time, AAD auth latency, and host-pool density drift are the components that actually break first under measured load.

No evidence-grade SLA proof.

Finance wants per-region availability + p95 login latency to defend the Azure budget. Hand-curated dashboard screenshots don’t survive a quarterly review.

Why LoadGen for AVD monitoring

One timeline. Synthetic + real-user + uptime.

The same ARM-native scenario that drives your AVD capacity tests runs continuously as a synthetic user. SessionSight captures the real-user side. Uptime checks watch the dependencies. One platform, one cockpit, one audit trail.

AVD-native synthetic users

Real ARM-discovered AVD sessions, FSLogix profile-load captured, AAD authentication measured — fired every minute. Not HTTP samplers pretending to be AVD clients.

SessionSight DEM on the same timeline

Heatmaps, replay, visitor journeys correlated against synthetic checks and AVD infrastructure counters. One scrub bar, one root-cause path.

Evidence-grade SLA reporting

Every synthetic check, real-user session, and uptime event lands in a queryable history. SLA reports generate on demand for Azure-spend defence — not in a quarterly spreadsheet sprint.

Guided setup

An AVD monitoring profile, captured in 10 steps.

The same wizard that powers /products/monitoring. ARM discovery captured once, replayed every synthetic check, every minute — across every region you deploy Core agents.

  • 10 named steps — Name · Target · Agents · Workload · Datasource · Schedule · SUT · Alerting · Summary.
  • AVD target-environment selection inline — Subscription / Resource Group / Host Pool from ARM.
  • Same scenario captured here is reusable for AVD load testing — one engine, two operational modes.
  • Synthetic sessions fire on schedule; results land in the live cockpit with FSLogix + AAD telemetry.

10-step monitoring profile wizard — autoplay, pause on hover.

Capability

What ships with End-to-End Monitoring for AVD.

Continuous synthetic AVD sessions

The same .lgs workload that drives AVD load tests runs as a synthetic user — every minute, every region, every persona. Per-step latency, AVD-specific p95, FSLogix profile-load.

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SessionSight Digital Experience

Click heatmaps, scroll maps, rage-click detection, DOM-fidelity replay across desktop / tablet / mobile — filtered by country, browser, OS, device, UTM.

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Severity-aware alerting

Email, Webhook, SMS, WhatsApp — with maintenance windows and on-call routing. Alert on FSLogix profile-load drift, AAD auth latency, host-pool density.

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Uptime + Azure dependency tracking

HTTP, REST, SQL, Azure Function, Azure App Service checks against AVD broker dependencies — incident management built in.

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Analytics & AI

AI-flagged FSLogix profile-load drift, AAD auth-latency anomalies, login-time regressions across every synthetic execution.

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LoadGen Insight + RBAC

Machine groups, data-health matrix, per-customer dashboards. Seven built-in roles plus custom permission trees — multi-tenant from day one.

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Real-user DEM

SessionSight catches what synthetic checks can’t.

Synthetic monitoring tells you the application responded. SessionSight tells you the AVD user actually clicked. Heatmaps + rage-click detection on the same timeline as your synthetic AVD probes.

  • Click, scroll, and rage-click heatmaps with intensity bands across desktop / tablet / mobile.
  • Desktop / tablet / mobile viewport switching with separate calibrated thresholds.
  • Deep-filter by country, browser, OS, device, UTM — production support workflow.
  • Correlated against synthetic check + Azure uptime events on a single scrub bar.

SessionSight heatmaps — click, scroll, rage-click modes.

Outcomes

What evidence-grade AVD monitoring looks like.

Monitoring sessions captured

Before

—

After

250 M+

platform total
Platforms unified

Before

Multi-vendor

After

6 in one

one platform
Per-Agent / month

Before

Quote on req.

After

€899

transparent
Annual subscription savings

Before

0

After

2 months free

on annual

See it in action

Three AVD monitoring surfaces on one platform.

Live cockpit

KPIs, sessions table, time-range scrub.

DEM heatmaps

Click, scroll, rage-click overlays.

Session replay

Image + DOM playback with event log.

What AVD teams monitor with this

Three AVD monitoring jobs.

SLA validation for AVD

Generate evidence-grade SLA reports on demand. Per-region availability, per-app response time, AVD p95 login latency — straight from the same data your alerts fire on.

See use case

Proactive UX detection

Catch FSLogix profile-load drift, AAD auth latency drift, and login-time regressions before users open a ticket. Alert on the lead indicator — not the helpdesk queue.

See use case

Multi-tenant AVD monitoring

One platform, per-customer dashboards, per-tenant RBAC. The shape MSPs use to deliver Monitoring-as-a-Service to an AVD-heavy customer book.

See use case

See AVD monitoring on your own subscription.

We’ll wire a synthetic AVD user against your Host Pool, layer real-user DEM via SessionSight, and walk you through SLA reporting — on a call.

Request an AVD monitoring demoSee SessionSight DEM

Questions

Frequently asked.

How is this different from Microsoft DEX / Cloud PC Insights / AVD Insights?

Azure-native tools report AVD infrastructure state and aggregate session metrics. LoadGen runs an actual AVD user end-to-end, every minute, across ARM-discovered Host Pools, FSLogix profile-load, AAD auth, and per-step interaction — and correlates that synthetic timeline with real-user DEM (SessionSight) and uptime against Azure dependencies. Microsoft tools show infrastructure; LoadGen shows experience.

Can a single Agent monitor multiple AVD host pools?

Yes — one Core agent typically covers one AVD subscription or host-pool stack. Scaling is per-environment, not per-user. Multi-region deployments use Core agents in each Azure region, with all results unified in the cockpit.

How does AVD monitoring correlate with FSLogix and connection-broker health?

SUT Monitoring binds FSLogix profile-load time, AAD authentication latency, and connection-broker counters to every synthetic check. Infrastructure health and measured user experience share one timeline — no separate dashboard hop.

What does AVD end-to-end monitoring cost?

€899 per Agent per month, with annual subscriptions including two months free. One Agent typically covers one AVD subscription or host-pool stack. SessionSight DEM and Service Levels are quoted separately.

How fast can we set up a synthetic AVD user?

The 10-step monitoring wizard captures the ARM-discovered AVD configuration once — Subscription / Resource Group / Host Pool inline. From then on the synthetic session fires every minute without additional setup.

What proof of SLA compliance can we hand to an auditor?

Every synthetic execution, real-user session, and uptime event is captured in queryable history. LoadGen Insight surfaces per-region availability, per-Host-Pool density, and p95 login latency; the underlying data exports to PDF / JSON for evidence-grade responses.

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