Recommendations¶
Optimization Recommendations is your centralized catalog of savings opportunities across compute, storage, database, networking, and AI workloads — backed by usage evidence, risk ratings, and step-by-step implementation guidance.
When to use it¶
- You want to find and prioritize cost-saving actions across your cloud accounts.
- You need to review a recommendation before implementing it in production.
- You want to dismiss, track, or route a recommendation to the right team.
Open Recommendations¶
Go to Optimization > Recommendations from product navigation.
Review and act on recommendations¶
1. Apply filters¶
Filter the list by: Provider, Account, Region, Service, Environment, Recommendation Type, Confidence, Risk, or State (open, dismissed, approved).
2. Understand the summary¶
The top of the page shows total recommendations, potential monthly savings, and a breakdown by category.
3. Select a recommendation¶
Each recommendation detail shows:
| Field | What it means |
|---|---|
| Resource | The specific cloud resource (name, ID, account, region) |
| Current configuration | What the resource is today (instance type, size, tier) |
| Target configuration | The recommended change |
| Monthly savings | Projected cost reduction |
| Confidence | How much usage evidence supports the recommendation |
| Risk | Operational impact if the recommendation is applied |
| Evidence | Usage trend graph (CPU, memory, I/O, etc.) |
| Implementation guidance | Steps to apply the change |
4. Take action¶
Depending on available actions and your permissions:
- Approve — mark the recommendation as accepted and route to implementation
- Dismiss — remove from the active list (record the reason)
- Route — send to a Jira ticket, ServiceNow request, or workflow
Recommendation types¶
Recommendations can cover: compute rightsizing, idle resource cleanup, storage tiering or deletion, database cleanup, log retention reduction, network cost optimization, resource scheduling, commitment purchases, and service-specific opportunities.
Best practices¶
- Prioritize by savings × confidence × risk — not savings alone. A high-savings recommendation with Low confidence or High risk needs more investigation.
- Check environment before acting — confirm production status and resource owner before making a change.
- Compare current and target config — don't rely solely on the savings estimate.
- Document dismissals — record why a recommendation was dismissed so you can revisit it later.
- Review after infrastructure changes — new deployments and billing corrections generate new recommendations.
Troubleshooting¶
If no recommendations appear, see Missing recommendations and anomalies.