Savings

Savings is the main Optimize workspace for identifying opportunities to reduce cloud costs. Open it from Optimize > Savings in the left sidebar.

Use Savings when you need to:

• See your total potential annual savings across all cloud accounts.
• Review cost optimization recommendations by severity, category, or region.
• Prioritize which recommendations to act on first.
• Assign, dismiss, or snooze recommendations for your team.
• Track progress as recommendations move from open to applied.

Filters

Use the filter bar to narrow recommendations to the scope you care about.

Available filters:

• Data Source — Limit to one or more connected cloud accounts.
• Region — Focus on recommendations within specific cloud regions.
• Resource Type — Filter by resource type such as EC2 instance, RDS, S3 bucket, or disk volume.
• Service — Narrow by cloud service category.
• Severity — Show only recommendations at a given severity level: Low, Medium, High, or Critical.
• Status — Filter by lifecycle state: Open, Applied, Dismissed, or Snoozed.
• Scenario Tags — Filter by recommendation category tags such as Resize, Delete, Commitment, Quick Win, Requires Planning, Idle, Oversized, Outdated, and others.

Filters apply across the summary, charts, and table simultaneously, so every view stays in sync with your selected scope.

Summary

The summary rail at the top of the page shows the total potential annual savings across all recommendations matching your current filters.

Two breakdown charts help you understand where savings opportunities are concentrated:

• Savings by Category — Breaks down potential savings by recommendation type, so you can identify which categories offer the most impact.
• Savings by Region — Breaks down potential savings by cloud region, helping you prioritize geographic areas with the highest opportunity.

Use the summary to orient your prioritization before diving into the table.

Recommendations Table

The recommendations table lists every recommendation matching your current filters. Each row shows:

• Title — A description of the specific optimization opportunity.
• Cloud Provider — The provider associated with the affected resource.
• Service — The cloud service the resource belongs to.
• Resource Type — The type of cloud resource flagged.
• Potential Savings — Estimated monthly and annual savings from acting on the recommendation.
• Severity — The priority level of the recommendation.
• Status — The current lifecycle state of the recommendation.

The table defaults to sorting by annual savings descending, so the highest-impact opportunities appear first. You can change the sort column and direction to suit your workflow.

Managing Recommendations

Status Updates

Use the Status control on any recommendation to move it through its lifecycle:

• Open — The recommendation is active and awaiting action.
• Applied — The recommended change has been implemented.
• Dismissed — The recommendation is not applicable or will not be acted on. Dismissed recommendations can be reopened.
• Snoozed — The recommendation is temporarily hidden until a date you specify. It returns to Open automatically after the snooze period.

Assignee

Assign any recommendation to a team member using the Assignee control. This is useful for routing recommendations to the right owner for follow-up.

Bulk Actions

Use the Bulk Actions toolbar to update multiple recommendations at once. Select recommendations using the row checkboxes, then apply a status change or assignee update across all selected items in a single action.

Recommendation Detail

Open any recommendation to see the full detail view. The detail page includes:

• Financial Impact — Current monthly cost, target monthly cost, estimated monthly savings, estimated annual savings, and savings percentage.
• Resource Information — Details about the specific cloud resource flagged, including its name, type, region, and cloud account.
• Overview — A description of the recommendation and the criteria used to identify the opportunity.
• Evidence — The underlying metrics and usage data that support the recommendation, such as CPU utilization trends or storage access patterns.
• Comments — A discussion thread for your team to coordinate on the recommendation. Add comments to document decisions or leave context for assignees.