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Cost Recommendations

The Cost Recommendations page surfaces Azure cost optimization opportunities, highlighting and prioritizing savings recommendations to bring clarity to cloud spend. This page provides comprehensive tools to analyze, manage, and act on cost optimization opportunities.

The Cost Recommendations page displays optimization opportunities with detailed savings calculations, resource-level insights, and actionable tasks.

For MSP (Managed Service Provider) users, the page includes two tabs:

  • Calculated — Recommendations generated automatically by vBox’s cost analysis engine
  • Advanced — Additional recommendations and optimization strategies

The summary widget at the top of the page provides a high-level overview of potential savings:

MetricDescription
Total SavingsCombined potential savings from all recommendations
Non-Optimized SpentCurrent cost of resources that could be optimized
Optimized SpentProjected cost after applying recommendations
Recommendation CountTotal number of optimization opportunities
Cost Reduction %Percentage reduction in costs if all recommendations are applied

Toggle Options:

  • Monthly/Annually — Switch between monthly and annualized savings projections
  • View Forecast — Link to detailed savings forecast analysis

If AI features are enabled (FEATURE_AI and FEATURE_AI_COST_SUMMARY), an AI Summary button appears that generates an intelligent summary of your cost optimization opportunities.

The main grid displays all cost optimization recommendations with comprehensive details:

ColumnDescription
IconVisual indicator of recommendation category or type
Category/RecommendationsThe optimization category and recommendation name
Unhealthy ResourcesCount of resources affected (e.g., “5 of 10”)
Current CostCurrent monthly cost of resources in this recommendation
Optimized CostProjected monthly cost after optimization
SavingsAbsolute savings amount
Savings/Cost%Savings as percentage of current cost
Savings/Total%Savings as percentage of total potential savings
TasksNumber of tasks created for this recommendation

Default Sort: Recommendations are sorted by Savings in descending order by default, showing the highest-impact opportunities first.

You can group recommendations by different dimensions to analyze patterns:

  • Category (default)
  • Region
  • Subscription
  • Resource Group
  • Resource Type
  • Tags
  • No Grouping

The page includes comprehensive action and filtering capabilities:

View Controls:

  • Show Muted Toggle — Show or hide recommendations that have been muted
  • Search — Filter recommendations by name, category, or other attributes

Recommendation Actions:

  • Mute/Unmute — Temporarily hide recommendations from view
  • Export — Export recommendations to Excel or as Optimization Results format
  • Import — Import optimization results (requires CAN_IMPORT_OPTIMIZATIONS feature flag)
  • Share Report — Send recommendation report via email
  • Download Report — Download a formatted report document

Clicking on a recommendation opens the detailed view, which includes:

Displays the calculation methodology for the savings estimate, showing how the recommendation’s potential savings were calculated.

  • Description — Detailed explanation of the optimization opportunity
  • Strategy — Recommended approach to achieve the savings

The details page organizes affected resources into tabs:

  • Unhealthy — Resources that need optimization
  • Muted — Resources that have been muted from this recommendation
  • Tasks — Tasks created for implementing this recommendation
  • Create Task — Generate a task for implementing the recommendation (requires TASKS feature flag)
  • Change Strategy — Modify the optimization strategy for this recommendation
  1. Start with High-Impact — Focus on recommendations with the highest savings first
  2. Review Resource Details — Drill into individual recommendations to understand affected resources
  3. Create Tasks — Use the task creation feature to track implementation progress
  4. Group by Dimension — Use grouping options to identify patterns across subscriptions, regions, or resource types
  5. Export for Analysis — Export recommendations for deeper analysis or reporting to stakeholders
  6. Monitor Muted Items — Periodically review muted recommendations to see if they become relevant