NERDIO GUIDE
Guide
Nerdio Manager for Enterprise
Introduction
Azure Virtual Desktop (AVD) cost monitoring is the practice of tracking, analyzing, and managing all expenses tied to your AVD environment.
For IT teams, effective monitoring is critical to prevent budget overruns, optimize resource allocation, and ensure you achieve the maximum return on investment (ROI) from your cloud desktop infrastructure.
What are the primary components that contribute to AVD costs?
To effectively manage your AVD budget, you first need to understand where the costs originate. Your total monthly bill is a sum of several distinct components, each influenced by your specific usage and configuration.
How does virtual machine compute usage affect AVD costs?
This is typically the largest portion of your AVD expense. It includes the cost of the session host virtual machines (VMs) that run user desktops and applications. Key factors that influence this cost are:
- VM Size and Series: The processing power, RAM, and type of VM (e.g., general-purpose, compute-optimized) you choose.
- Payment Model: Whether you use pay-as-you-go pricing or have committed to discounted 1-year or 3-year Azure Reserved Instances (RI).
- Usage Hours: The total time your VMs are running each month. VMs that are on but not in use still incur costs.
What storage costs are associated with an AVD deployment?
Every AVD environment relies on Azure storage, which generates its own set of costs. The primary storage components include:
- OS Disks: Each session host VM has an operating system disk, and the cost varies depending on whether you choose a Standard HDD, Standard SSD, or Premium SSD.
- User Profile Storage: To store user profiles and data, you will use a solution like Azure Files or Azure NetApp Files. The cost is determined by the storage tier (e.g., Premium, Transaction Optimized) and the amount of data stored.
How does networking contribute to the overall AVD expense?
Networking costs can be less predictable but are still a significant factor in your total AVD bill. You should monitor:
- Data Egress: This is the cost of data moving out of the Azure network. While data ingress (inbound) is generally free, you are billed for outbound data transfer, which is influenced by user activities like file downloads and streaming.
- Connectivity Services: If you use services like Azure VPN Gateway or ExpressRoute to connect your on-premises network to Azure, these will have their own fixed monthly costs.
Which licensing costs need to be factored into AVD?
While AVD itself doesn't have a separate licensing fee, access rights are included with many common Microsoft licenses. You need to ensure your users are covered by an eligible license, such as:
- Microsoft 365 E3/E5/A3/A5/Business Premium
- Windows 10/11 Enterprise E3/E5
- Windows 10/11 Education A3/A5
You must also account for the licensing of any third-party applications you install on your session host VMs.
Know the TCO
This step-by-step wizard tool gives you the total cost of ownership for AVD in your organization.
What native Microsoft Azure tools can be used to monitor AVD costs?
While several native Microsoft Azure cost management tools can help optimize your environment, their usefulness for monitoring AVD costs varies significantly. Each tool has a distinct purpose and, more importantly, a key limitation that can hinder true cost analysis for virtual desktops.
The table below outlines these differences to inform your management strategy.
| Tool | Primary Function | Key Limitation for AVD |
|---|---|---|
| Azure Cost Management | Financial Governance: Provides a high-level view of spending. Used for tracking costs, creating budgets, and analyzing historical spend across subscriptions and resource groups. | Lacks Granularity: It shows what you spent on resources, but struggles to differentiate why. It cannot easily distinguish between costs from active user sessions versus idle, powered-on VMs without complex tagging and manual analysis. |
| Azure Monitor | Operational Monitoring: Collects performance metrics and logs from your Azure resources, tracking the health, utilization (CPU, memory), and user session data needed to understand host pool activity. | Not a Cost Tool Out-of-the-Box: It provides the raw performance data but requires significant configuration (Log Analytics queries, custom workbooks) to translate that operational data into actionable financial insights. |
| Azure Advisor | Proactive Recommendations: Scans your environment and offers best-practice advice to optimize for cost, security, and performance. | Recommendations are Generic: It may suggest shutting down an "underutilized" VM without understanding it's a session host that needs to be available for users or is part of a dynamic host pool managed by scaling logic. |
How does Azure Cost Management + Billing help track AVD spending?
Azure Cost Management is your primary tool for a high-level overview of Azure spending. It allows you to analyze costs, create budgets, receive alerts when spending exceeds thresholds, and get recommendations for cost optimization. For AVD, you can use it to view the aggregated costs of the resource groups containing your session hosts, storage, and networking components, but it struggles to break down those costs to a per-user level without extensive, manual tagging discipline.
What role do Azure Monitor and Log Analytics play in detailed cost analysis?
Azure Monitor collects performance and usage telemetry from your AVD resources. When you feed this data into a Log Analytics workspace, you can perform deep analysis using the Kusto Query Language (KQL). This allows you to correlate resource consumption (like CPU or memory usage) with specific user sessions. However, translating this granular usage data into specific dollar amounts requires significant technical expertise to build and maintain the right queries.
How can Azure Advisor help identify cost-saving opportunities?
Azure Advisor acts as a personalized cloud consultant, analyzing your resource configuration and usage to provide recommendations. For AVD, it can be useful for identifying underutilized VMs that are candidates for resizing or for recommending the purchase of Reserved Instances to reduce compute costs. Its recommendations are based on general Azure best practices and are not always tailored to the dynamic, multi-session nature of AVD workloads.
What are the common limitations of using only native Azure tools for AVD cost management?
While native tools are essential, relying on them exclusively for AVD can lead to significant gaps in both visibility and control. These limitations often drive organizations to seek specialized solutions that address the unique challenges of virtual desktop environments.
- Difficulty in Allocating Costs: Native tools make it very difficult to determine the precise cost-per-user or cost-per-host-pool. Without this granular data, it's nearly impossible to perform accurate departmental chargebacks or understand the true TCO for different user groups.
- Reactive vs. Proactive Optimization: Most native tools are excellent for reporting on what you've already spent. They have limited capabilities for proactive, automated optimization, such as predictive scaling that adds and removes session hosts based on real-time user demand.
- Significant Management Overhead: Achieving meaningful AVD cost insights with native tools requires deep expertise across multiple Azure services. Building and maintaining the necessary KQL queries, tagging policies, and alert configurations is a time-consuming and ongoing effort.
- Lack of AVD-Specific Logic: Azure's general-purpose tools treat session hosts like any other server. They don't inherently understand AVD-specific concepts like drain mode, log-on storms, or the difference between an active and disconnected session, which are critical for intelligent scaling and cost control.
Which third-party tools are available to enhance AVD cost monitoring and optimization?
To overcome the limitations of native tools, a market of third-party cost management tools has emerged to provide deeper insights and automation for AVD. These tools generally fall into two categories: specialized AVD management platforms and general-purpose cloud cost management platforms.
What are specialized AVD management and automation platforms?
These platforms are purpose-built for deploying, managing, and optimizing Azure Virtual Desktop environments from a single console. Their primary strength is combining operational management with advanced, AVD-aware cost optimization features.
- Nerdio Manager for Enterprise: Focuses on advanced, predictive autoscaling, automated image management, and granular cost reporting, including per-user chargeback data. It is designed to automate both AVD deployment and ongoing FinOps management.
- Sepago Azure Monitor for AVD: Provides deep monitoring and analytics for AVD environments, with a focus on user experience metrics and host pool performance that can be used to inform cost decisions.
- Parallels RAS: Offers a centralized management console for VDI environments, including AVD, with features for resource optimization and automated session management.
While all three platforms enhance the native AVD experience, they approach cost management from fundamentally different angles. Sepago focuses on deep monitoring and visibility, Parallels RAS provides a comprehensive alternative infrastructure, and Nerdio integrates proactive optimization directly with management.
| Feature / Capability | Nerdio Manager for Enterprise | Sepago Azure Monitor for AVD | Parallels RAS |
|---|---|---|---|
| Primary Cost Strategy | Proactive Optimization: Focuses on preventing costs before they occur through advanced, automated scaling of both compute and storage. | Reactive Monitoring & Analysis: Excels at providing deep visibility into what has already happened. It helps you understand costs by analyzing historical performance and usage data. | Infrastructure Efficiency: Aims to reduce costs through its own brokering and load-balancing technology, presenting an alternative to the standard AVD architecture. |
| Compute Auto-Scaling | Advanced & Multi-Layered: Granular, schedule-based, and performance-driven (CPU, RAM, active sessions) auto-scaling. Includes predictive algorithms and host pre-staging to balance cost savings with user experience. | None (by design): It is a monitoring solution. It provides the detailed data needed to build your own scaling logic using other Azure tools, but does not perform the scaling itself. | Performance-Based: Offers robust, template-driven auto-scaling based on user sessions, CPU, and memory, but is generally less granular and predictive than Nerdio's engine. |
| Storage Cost Optimization | Unique & Integrated: Automatically shrinks FSLogix profile disks during off-peak hours and can auto-scale the underlying file server infrastructure (e.g., Azure Files) based on actual need. | None: It can monitor storage performance and capacity, but has no built-in capability to actively manage or shrink storage to reduce costs. | Limited: Manages user profiles within its ecosystem but lacks the specific, automated cost-saving features for FSLogix disks and underlying storage infrastructure that Nerdio provides. |
| Cost Visibility | Unified Financial & Operational View: Translates operational metrics into clear financial reports within the same interface. Provides showback/chargeback reporting and cost forecasting. | Deep Operational View: Offers highly detailed Log Analytics workbooks with rich performance data (session times, latency, host performance). Translating this to exact cost requires additional work. | Dashboard-Level View: Provides high-level reporting on resource usage within its own console. Less focused on granular Azure cost analysis compared to the other two. |
| Actionability | Act from Insight: Allows admins to immediately act on insights from the same console—adjusting scaling logic, resizing VMs, or changing storage configurations without leaving the interface. | Insight Only: Identifies potential issues or optimization opportunities, but requires the administrator to go to the Azure Portal or use scripts to take corrective action. | Act within Parallels Console: Actions are taken within the Parallels RAS console, which then orchestrates the changes on the underlying Azure infrastructure. |
What are general-purpose cloud cost management platforms?
These platforms are powerful, multi-cloud tools designed to give organizations a comprehensive view of their entire cloud spend across different providers like Azure, AWS, and GCP. While powerful, these multi-cloud platforms are not always the most cost-effective solution for the specific challenges of AVD, as they lack the granular, user-centric automation required for true optimization.
- CloudHealth by VMware: This is a robust platform that excels at financial governance, providing detailed cost reporting, budgeting, and showback/chargeback capabilities across an entire organization.
- AVD Limitation: Its primary limitation for AVD is that it provides recommendations based on VM metrics, lacking the user session context needed to make intelligent scaling decisions for session hosts.
- Flexera One: This platform focuses on comprehensive IT asset management, including cost optimization, by discovering and analyzing all cloud resources to provide savings recommendations.
- AVD Limitation: For AVD, its optimization engine is not purpose-built for session-based workloads, meaning its recommendations may not align with user logon patterns or FSLogix profile storage needs.
- Cloudability (from Apptio): Known for its strong financial analysis capabilities, Cloudability helps businesses translate cloud spending into business metrics, mapping costs to products, teams, and projects.
- AVD Limitation: Its key limitation for AVD is its inability to correlate infrastructure costs with specific user activity or session data, making it difficult to optimize host pools based on actual demand.
- Datadog Cloud Cost Management: An extension of its popular monitoring platform, this tool aims to connect cost data directly with performance metrics, helping teams understand the financial impact of their cloud usage and infrastructure.
- AVD Limitation: While excellent for performance monitoring, its limitation for AVD cost optimization is that it reports on VM usage but lacks the built-in automation to act on that data in a user-centric way, such as managing session host scaling or FSLogix storage.
How should an organization choose the right AVD cost monitoring tool?
With multiple options available, selecting the right tool requires a clear evaluation of your organization's specific needs and priorities. Asking the right questions upfront will help you find a solution that delivers tangible ROI.
What key features should you look for in an AVD cost tool?
Look for a solution that moves beyond simple reporting and offers true optimization. A strong platform should include:
- Automated and predictive autoscaling logic
- Granular per-user or per-department cost reporting and chargeback
- Automated management and optimization of Azure Reserved Instances
- Detection and cleanup of idle VMs and orphaned resources (e.g., disks, NICs)
- A unified management console for both operations and cost control
- Customizable dashboards and reports
What questions should you ask when evaluating a solution?
- Does this tool focus on cost reporting (telling me what I spent) or proactive cost optimization (actively reducing my spend)?
- How does the solution integrate with our existing Azure environment, security policies, and identity provider?
- What is the pricing model for the tool itself, and how can we calculate its projected ROI based on our environment?
- How much of our routine AVD management and scaling can be automated by this platform?
How does Nerdio Manager for Enterprise specifically address AVD cost challenges?
Specialized platforms like Nerdio Manager for Enterprise are designed to directly solve the cost management challenges inherent to AVD. It achieves this by combining granular cost visibility with powerful automation features that proactively optimize resource consumption.
- Advanced, Predictive Autoscaling: Instead of relying on simple schedules, Nerdio's autoscaler can add and remove session hosts based on real-time metrics like active sessions, CPU usage, and available RAM. This ensures you have just enough capacity to meet user demand without paying for idle resources.
- Granular Cost-Back and Chargeback: The platform automatically ingests cost data and allocates it to individual users or departments. This solves a primary limitation of native tools and makes it simple to generate showback or chargeback reports.
- Automated Reserved Instance Utilization: Nerdio can automatically use pre-paid Reserved Instances for your baseline capacity needs while seamlessly adding pay-as-you-go VMs to handle peak demand, maximizing your RI savings.
- Idle and Orphaned Resource Cleanup: The platform can identify and automatically decommission unused resources, such as the unattached disks and network interfaces left behind after VMs are deleted, preventing hidden cost accumulation.
Discover how you can save up to 70% on Microsoft Azure costs by creating more efficient, secure, and reliable operations. Watch this demo.
Optimize and save
See how you can optimize processes, improve security, increase reliability, and save up to 70% on Microsoft Azure costs.
Frequently Asked Questions
Related resources
Blog
Nerdio Manager for MSP
Lower the cost of switching: A fast, low-risk migration blueprint for MSPs
Blog
Nerdio Manager for Enterprise
5 ways that Nerdio delivers more than cost savings
About the author
