Internal Plugins

Overview

Azure Quick Review (azqr) includes internal plugins - specialized built-in scanners that provide advanced analytics beyond standard best practice recommendations. Unlike YAML plugins (which add custom Resource Graph queries), internal plugins perform complex data analysis, API integrations, and multi-source data correlation.

Internal plugins are disabled by default and must be explicitly enabled using command-line flags.

Available Internal Plugins

1. AI Governance

Plugin Name: ai-gov
Command: azqr ai-gov
Flag: --plugin ai-gov
Version: 1.0.0

Monitors Azure OpenAI and Cognitive Services accounts for throttling (429 errors) to identify capacity constraints.

Key Features:

• Tracks 429 throttling errors by hour, model, and deployment
• Analyzes spillover configuration effectiveness
• Reports request counts by status code
• Identifies peak throttling periods

Use Cases:

• Capacity planning for OpenAI deployments
• Troubleshooting throttling issues
• Optimizing deployment spillover configuration
• Monitoring API usage patterns

Output Columns:

• Subscription, Resource Group, Account Name
• Kind (OpenAI, Cognitive Services)
• SKU and deployment details
• Model name and spillover settings
• Hourly throttling statistics (status code, request count)

Data Source: Azure Monitor Metrics API (last 24-48 hours)

2. Carbon Emissions

Plugin Name: carbon-emissions
Command: azqr carbon-emissions
Flag: --plugin carbon-emissions
Version: 1.0.0

Analyzes carbon emissions by Azure resource type to support sustainability reporting and optimization.

Key Features:

• Tracks emissions by resource type across subscriptions
• Calculates month-over-month change ratios
• Aggregates emissions from multiple subscriptions
• Supports sustainability compliance reporting

Use Cases:

• Sustainability reporting and compliance
• Identifying high-emission resource types
• Tracking carbon reduction progress
• Environmental impact analysis

Output Columns:

• Period From/To (reporting period)
• Resource Type
• Latest Month Emissions
• Previous Month Emissions
• Month-over-Month Change Ratio
• Monthly Change Value
• Unit (metric tons CO2 equivalent)

Data Source: Azure Carbon Optimization API

3. Zone Mapping

Plugin Name: zone-mapping
Command: azqr zone-mapping
Flag: --plugin zone-mapping
Version: 1.0.0

Retrieves logical-to-physical availability zone mappings for all Azure regions in each subscription.

Key Features:

• Maps logical zones (1, 2, 3) to physical zone identifiers
• Reveals subscription-specific zone mappings
• Helps ensure proper zone alignment across subscriptions
• Supports multi-subscription architecture planning

Use Cases:

• Multi-subscription architecture design
• DR planning with zone awareness
• Zone alignment for latency optimization
• Compliance and audit documentation

Output Columns:

• Subscription, Location, Display Name
• Logical Zone (1, 2, or 3)
• Physical Zone (e.g., eastus-az1, westeurope-az2)

Data Source: Azure Resource Manager Subscriptions API

📖 Full Documentation

4. Region Selection

Plugin Name: region-selection
Command: azqr region-selection
Flag: --plugin region-selection
Version: 0.2.0-beta

Scores and ranks Azure regions for workload migration or expansion. For each source region (where your resources currently live) × target region (candidate), the plugin computes a weighted 0–100 recommendation score across four dimensions.

Availability zone loss/gain applies a multiplicative adjustment to the final score.

Network Latency Details:

• Values are round-trip time (RTT) sourced from Microsoft’s published Azure Network Round-trip Latency Statistics (P50/median RTT in ms)
• Lookup order: exact measured region pair → reverse pair (RTT is treated as symmetric) → geographic cluster-pair average as a fallback estimate
• Estimated values (cluster-based, no direct measurement available) are shown as “X.X (est.)” in the Avg Latency (ms) column
• Pairs with no data or estimate available show “N/A” and are scored neutrally

Key Features:

• Qualitative Recommended (≥ 80), Neutral (60–79), Not Recommended (< 60) bands
• Score Quality flag notes when cost or latency data was unavailable
• Per-target-region Svc Avail Excel sheets with service and SKU availability per resource type
• CostComparison Excel sheet with per-meter retail pricing across all analysed regions
• Optional --target-regions flag to narrow analysis to specific candidates

Use Cases:

• Migration planning and DR site selection
• Regional expansion decisions
• Compliance with data-residency requirements

Output Columns (main sheet):

• Subscription, Source Region, Target Region
• Source Resource Type Count, Available/Unavailable Resource Types, Availability %
• Total SKUs Checked, Available/Unavailable/Restricted/Unknown SKUs, SKU Availability %
• Availability Zones, Avg Latency (ms), Avg Cost Difference %
• Recommendation Score, Score Quality, Recommendation
• Missing Resource Types, Unavailable SKUs (detail), Restricted SKUs (detail)

5. SQL Server EOL

Plugin Name: sql-eol
Command: azqr sql-eol
Flag: --plugin sql-eol
Version: 0.6.0-beta

Analyzes SQL Server End-of-Life (EOL) and Extended Security Update (ESU) status across Arc-enabled SQL Server instances and SQL Virtual Machines on Azure.

Key Features:

• Detects EOL status dynamically using current date (Expired, ESU Active, Upcoming ESU, Supported)
• Models ESU billing the way Microsoft meters it: once per host (OSE), per SQL Server version, at the highest edition present — multiple same-version components (Engine, SSIS, SSAS, SSRS, PBIRS) on one host share a single ESU charge
• Enforces Standard edition 24-core cap on ESU billing (per Microsoft ESU pricing docs; Enterprise and Web are uncapped)
• Passive HA/DR replicas excluded from ESU cost ($0 — covered under primary’s SA failover rights)
• Reports ESU subscription status (ESUEnabled) from the Arc machine’s WindowsAgent.SqlServer extension
• Estimates SQL Managed Instance migration savings with 2:1 consolidation model
• Covers both Arc-enabled SQL (on-prem, AWS, GCP) and Azure VM (SQL IaaS)

ESU Billing Model: ESU is metered once per OSE (Operating System Environment — a physical or virtual machine), per SQL Server version, at the highest edition installed for that version. All SQL Server service types (Engine, SSIS, SSAS, SSRS, Power BI Report Server) are ESU-eligible and roll into that single per-host+version charge. Free editions (Developer, Express, Evaluation) are never billed; passive HA/DR replicas are covered at $0 under the primary server’s Software Assurance.

Use Cases:

• ESU cost forecasting and budgeting (accurate host-level model, not overcounted per-instance)
• Identifying which Arc hosts already have ESU subscribed vs. unsubscribed
• Migration planning to Azure SQL Managed Instance
• Compliance reporting for end-of-support software
• License optimization across SQL estates

Output Columns:

• Subscription, Resource Group, Name, Location
• Arc Server Name (underlying Arc machine name; N/A (SQL VM) for Azure VMs)
• Cloud Type (Arc-enabled (On-Prem) / Arc-enabled (AWS) / Arc-enabled (GCP) / Azure VM (SQL IaaS))
• Service Type (Engine / SSIS / SSAS / SSRS / PBIRS for Arc; Engine for SQL VMs)
• SQL Version, Edition
• EOL Status (Expired / ESU Active / Upcoming ESU / Supported)
• ESU Applicable (Yes / No - free edition / No - passive HA/DR replica)
• ESU Enabled (Enabled / Not Enabled for Arc; Unknown (SQL VM) for Azure VMs)
• ESU Start Date, ESU End Date
• Migration Target Tier (General Purpose / N/A)
• Migration Recommendation (actionable text)
• vCores, Billable Cores
• ESU Monthly Cost/Core
• SQL License Type, SQL License Cost/Core/Month, SQL License Monthly Cost
• VM Cost/Core/Month, Est VM Compute Monthly Cost
• Est ESU Monthly Cost (charged once per host+version; $0 on secondary components)
• ESU Cost Basis (explains attribution: primary row, included, or N/A)
• Patch Ops Monthly Cost
• Current Monthly Cost (total current spend)
• Consolidation Ratio (2:1 default)
• Est SQL MI Monthly Cost, Est SQL MI Monthly Saving
• SQL MI Migration Verdict (Cost Savings / Break Even / Cost Increase)

6. VM v6/v7 Modernization Readiness

Plugin Name: vm-modernization
Command: azqr vm-modernization
Flag: --plugin vm-modernization
Version: 0.1.0

Reports Azure VM v6/v7 series modernization readiness, following the Discover → Assess → Plan phases from the VM v6/v7 modernization guidance: Discover-phase workload pattern, Assess-phase readiness signals, and a Plan-phase execution-method recommendation with a suggested target v6/v7 SKU.

Key Features:

• Classifies each VM’s workload pattern (compute pool, AVD pooled host pool, service-managed, certified ISV appliance, or customer-managed) from Azure Resource Graph signals
• Reports Assess-phase readiness signals: Hyper-V generation, disk controller type (SCSI vs. NVMe), series generation, and Azure Disk Encryption status
• Recommends a Plan-phase execution method (redeploy / no action / manual review) and flags the Temp Disk Dependency and SAP/ISV Certification Gate hard gates where applicable
• Suggests the best-matching v6/v7 target SKU using the internal/skus compatibility advisor
• Surfaces relevant upcoming retirements and price changes from an embedded lifecycle/pricing dataset
• Computes per-VM current, projected, and monthly cost impact directly from the Azure Retail Prices API — including pool-managed VMs, using each VM’s own current SKU
• Covers standalone VMs, Availability Set members, and VMSS Flex/Uniform members (including AKS node pools), plus Databricks-managed, AVD pooled, and standard Azure Red Hat OpenShift (ARO) cluster nodes
• Reports pool-level signals (Orchestration Mode, Pool Model VM Size, Pool Model Series Generation) for every VMSS-backed row
• Surfaces the full raw inventory signal set from the Assess article’s starter query (placement, OS/image, storage, licensing, networking, security), alongside the derived columns above

Scope:

• The Validate phase from the VM v6/v7 modernization guidance (post-migration scoring/verification) is out of scope for this plugin; it covers only the Discover, Assess, and Plan phases
• Standard ARO ownership is identified by matching each inventoried VM’s full resource-group ID to the cluster’s clusterProfile.resourceGroupId. Recognized nodes report A: Compute pool and ARO Cluster, without standalone redeploy or target-SKU recommendations; inventory, placement signals, and per-VM cost calculations remain available.
• ARO matching identifies cluster ownership, not individual MachineSets or control-plane/worker roles. Hosted-control-plane ARO and self-managed OpenShift are not covered by this lookup. Follow ARO support policy for node changes; worker-pool replacement guidance does not authorize changes to control-plane nodes.
• The scan identity needs read access to both the ARO cluster resource and its node resources within the scan’s subscription scope. ARO and AVD ownership use supplementary ARG lookups. Lookup failures are logged as warnings and do not stop inventory reporting. Missing permissions, incomplete ARG data, or failed enrichment can leave nodes without ARO classification, including the default customer-managed classification; generic migration advice is not authorization to modify an ARO node.

Use Cases:

• Discover-phase inventory: which VMs are customer-managed vs. pool-managed, and ready for per-VM modernization planning
• Assess-phase readiness triage: identifying Gen1-only VMs, SCSI-controller VMs needing the SCSI-to-NVMe migration path, and VMs already on v6/v7
• Plan-phase SKU selection: a starting v6/v7 target recommendation per VM, ranked by compatibility score
• Lifecycle/pricing awareness: surfacing upcoming retirements and price changes relevant to each VM’s current series
• Full-inventory export: an inventory result enriched by supplementary ownership lookups, covering every signal the Assess article’s manual checklist references (image, disk, network, security, licensing), for readers who want the complete picture rather than only the plugin’s own verdicts

Output Columns:

Derived readiness/plan columns:

• Subscription, Resource Group, Name, Location
• Current VM Size
• Workload Pattern (A: Compute pool / B: AVD pooled host pool / C: Service-managed compute (excluded) / E: Customer-managed VM (default) / G: Certified ISV appliance), Pool Membership (AKS Node Pool / ARO Cluster / VMSS / AVD Pooled Host Pool / Azure Databricks / Standalone / appliance vendor name)
• Hyper-V Generation, Disk Controller Type, Series Generation
• Azure Disk Encryption (Enabled / Disabled, aggregated across every attached disk)
• Temp Disk Dependency (Manual Review Required for patterns B, E, G; N/A (pool/platform-managed) for A, C), SAP/ISV Certification Gate (Manual Review Required for pattern G only; N/A (not an SAP or ISV-certified workload) for A, B, C, E)
• Recommended Execution Method
• Suggested Target SKU, Target SKU Compatibility Score
• Lifecycle/Pricing Notes
• Current Monthly Cost (USD), Projected Monthly Cost After Increase (USD), Monthly Cost Impact (USD)

Full raw inventory columns (mirrors the Assess article’s starter query):

• Membership Model (Standalone / Availability Set / VMSS Flex), Zone Placement (Zonal / Regional), Availability Zone
• VMSS Name, Availability Set Name, Platform Fault Domain
• VM Power State, Instance View Captured
• OS Type, OS Version, Computer Name
• Is Marketplace VM, Image Publisher, Image Offer, Image SKU, Image Version
• OS Disk Type, OS Disk Size (GB), Ephemeral OS Disk, Data Disk Count
• ADE OS Disk (VM Property)
• Hibernation Enabled, Ultra SSD Enabled, License Type
• NIC Count, Accelerated Networking, IP Forwarding
• Security Type, Secure Boot Enabled, vTPM Enabled

7. Service Health Availability

Plugin Name: service-health
Command: azqr service-health
Flag: --plugin service-health
Version: 0.1.0-beta

Analyzes Azure service health events to determine the percentage of time resources were unaffected by service issues over the last 90 days.

Key Features:

• Correlates resolved ServiceIssue events (and their impacted-resource associations) with the full resource inventory via Azure Resource Graph
• Computes an event-free percentage per resource, capped to the 90-day (2,160-hour) window to account for overlapping events, then averages within each (subscription, region, resource type) bucket
• Reports total distinct event counts and the number of affected resources per bucket
• Results are sorted worst-first (lowest event-free percentage first)
• Honors resource-type exclusion filters (--filters)

Use Cases:

• Reliability and SLA/availability reporting
• Identifying regions or resource types prone to service health issues
• Prioritizing resiliency investments based on historical impact

Output Columns:

• Subscription ID, Target Region, Target Resource Type
• Percentage Without Events, Events Count, Affected Resources

Data Source: Azure Resource Graph (servicehealthresources table, last 90 days)

Usage

Running Internal Plugins

Internal plugins can be executed in two ways:

1. Standalone Plugin Commands (Recommended for Fast Execution)

Run plugins as top-level commands for optimized execution. This mode skips resource and APRL scanning, executing only the specified plugin:

# Run OpenAI throttling plugin
azqr ai-gov

# Run carbon emissions plugin
azqr carbon-emissions

# Run zone mapping plugin
azqr zone-mapping

# Run region selection plugin
azqr region-selection

# Narrow region selection to specific target regions
azqr region-selection --target-regions=swedencentral,germanywestcentral

# Run SQL EOL plugin
azqr sql-eol

# Run VM v6/v7 modernization readiness plugin
azqr vm-modernization

# Run service health availability plugin
azqr service-health

# Run with specific subscriptions
azqr zone-mapping --subscription-id <sub-id>

# Run with custom output name
azqr ai-gov --output-name throttling-report

Benefits of Standalone Mode:

• ⚡ Faster execution - Skips resource scanning
• 📊 Cleaner reports - Contains only plugin results
• 🎯 Focused analysis - Dedicated to specific plugin output

2. Integrated with Full Scan

Run plugins alongside standard compliance scanning using the --plugin flag:

# Enable single plugin during scan
azqr scan --plugin ai-gov

# Enable multiple plugins during scan
azqr scan --plugin ai-gov --plugin carbon-emissions --plugin zone-mapping --plugin region-selection --plugin sql-eol --plugin vm-modernization --plugin service-health

# Combine with other scan options
azqr scan --subscription-id <sub-id> --plugin zone-mapping --output-name analysis

When to Use Scan Integration:

• Need both compliance recommendations and plugin analysis
• Want consolidated report with all data
• Running comprehensive assessments

Listing Available Plugins

View all registered plugins (internal and YAML):

azqr plugins list

Sample Output:

NAME                  VERSION    TYPE       DESCRIPTION
ai-gov     1.0.0      internal   Checks OpenAI/Cognitive Services accounts for...
carbon-emissions      1.0.0      internal   Analyzes carbon emissions by Azure resource type
zone-mapping          1.0.0      internal   Retrieves logical-to-physical availability zone mappings...
region-selection      0.2.0-beta internal   Analyzes optimal Azure region selection based on service availability...
sql-eol               0.6.0-beta internal   Analyzes SQL Server End-of-Life and Extended Security Update status
vm-modernization      0.1.0      internal   Reports Azure VM v6/v7 series modernization readiness
service-health        0.1.0-beta internal   Analyzes Azure service health events to determine...

Plugin Details

Get detailed information about a specific plugin:

azqr plugins info zone-mapping

Output Formats

Internal plugin results are included in all output formats:

Excel (Default)

Each internal plugin creates a dedicated worksheet in the Excel workbook:

• Zone Mapping sheet
• AI Gov sheet
• Carbon Emissions sheet
• Region Selection sheet (main scored table)
  • Svc Avail <region> sheets — one per target region with per-resource-type availability
  • CostComparison sheet — per-meter retail pricing across all analysed regions
• SQL EOL sheet
• VM Modernization sheet
  • VM Modernization - Notices sheet — account-wide lifecycle/pricing notices that apply regardless of VM family or region, omitted on Azure Government/Azure China
• Service Issues sheet

# Run plugins as standalone commands (fastest)
azqr ai-gov
azqr carbon-emissions
azqr zone-mapping
azqr region-selection

# Or run with full scan
azqr scan --plugin ai-gov --plugin carbon-emissions --plugin zone-mapping --plugin region-selection
# Generates: azqr_action_plan_YYYY_MM_DD_THHMMSS.xlsx

JSON

Plugin results are included in the pluginResults array:

# Run as standalone command
azqr zone-mapping --json

# Or run with full scan
azqr scan --plugin zone-mapping --json

JSON Structure:

{
  "recommendations": [...],
  "resources": [...],
  "pluginResults": [
    {
      "pluginName": "zone-mapping",
      "sheetName": "Zone Mapping",
      "description": "Retrieves logical-to-physical availability zone mappings for all Azure regions in each subscription",
      "table": [
        ["Subscription", "Location", "Display Name", "Logical Zone", "Physical Zone"],
        ["Production", "East US", "East US", "1", "eastus-az1"]
      ]
    }
  ]
}

CSV

Plugin results are exported to separate CSV files:

# Run as standalone command
azqr zone-mapping --csv

# Or run with full scan
azqr scan --plugin zone-mapping --csv
# Generates: 
#   <filename>.zone-mapping.csv
#   <filename>.recommendations.csv
#   <filename>.inventory.csv
#   ...

Permissions

Internal plugins may require additional permissions beyond standard Reader access:

Recommended: Assign Reader and Monitoring Reader roles at subscription or management group scope.

Performance Considerations

Internal plugins add processing time to scans:

• ai-gov: 1-3 minutes (depends on number of OpenAI accounts)
• carbon-emissions: 1-2 minutes (depends on subscription count)
• zone-mapping: <10 seconds (very fast, one API call per subscription)
• sql-eol: <30 seconds (single Azure Resource Graph query)
• vm-modernization: one main Azure Resource Graph query plus separate AVD and ARO ownership lookups, followed by batched/concurrent Azure Retail Prices API lookups across the estate’s unique VM SKU/region pairs. Latency depends on inventory size, ARG batching/pagination, and the number of distinct SKU/region pairs; each price batch request covers only 8 pairs.
• service-health: <30 seconds (single Azure Resource Graph query against 90 days of service health events)

Optimization Tips:

• Enable only needed plugins
• Use subscription/resource group filters to reduce scope