What is Cloud Rightsizing?
Key takeaways
Cloud rightsizing is matching cloud resources to actual workload requirements
30-35% of cloud spend is typically wasted on over-provisioned resources
Rightsizing adjusts instance types, storage, and configurations based on utilization data
Part of FinOps practices for cloud cost optimization
CerteroX Cloud Management delivers 38% average savings through rightsizing and optimization
Certero is a FinOps Foundation member
What is Cloud Rightsizing?
Cloud rightsizing is the process of analyzing cloud resource utilization and adjusting allocations to match actual workload needs. When resources are "right-sized," you're not paying for capacity you don't use.
The challenge: organizations often provision cloud resources based on peak demand estimates or vendor recommendations—resulting in instances that run at 10-30% utilization while billing for 100%.
Why rightsizing matters
The waste problem
Studies consistently show 30-35% of cloud spend is wasted:
Over-provisioned virtual machines
Idle resources still billing
Previous-generation instance types
Storage allocated but unused
The compounding effect
Cloud waste compounds because:
Over-provisioned resources are copied to new environments
"This is how we've always done it" becomes default sizing
No one is accountable for optimization
The bill arrives 30 days after the waste occurs
The opportunity
Rightsizing is often the highest-impact, lowest-effort optimization:
Doesn't require architecture changes
Can be automated with proper tooling
Delivers immediate, measurable savings
Improves application performance when done correctly
Types of rightsizing
1. Vertical rightsizing
Adjusting instance size within the same family:
Downsize: m5.xlarge → m5.large (when underutilized)
Upsize: m5.large → m5.xlarge (when constrained)
2. Horizontal rightsizing
Adjusting the number of instances:
Reduce: 10 instances → 6 instances (when over-provisioned)
Increase: 6 instances → 10 instances (when needed)
3. Instance family changes
Moving to more appropriate instance types:
General purpose → Memory optimized (for memory-intensive workloads)
Previous generation → Current generation (for better price/performance)
4. Storage rightsizing
Optimizing storage configurations:
Reduce volume sizes
Change storage tiers (SSD → HDD where appropriate)
Delete orphaned volumes
5. Database rightsizing
Optimizing managed database resources:
Right-size RDS instances
Adjust Aurora capacity
Optimize reserved capacity
Rightsizing process
Step 1: Collect utilization data
Monitor actual resource usage over time:
CPU utilization
Memory consumption
Network throughput
Storage IOPS
Application metrics
Minimum observation period: 7-14 days (to capture weekly patterns)
Step 2: Analyze patterns
Identify:
Consistently underutilized resources (candidates for downsizing)
Resources at capacity (may need upsizing)
Idle resources (candidates for termination)
Peak vs. average utilization (sizing strategy)
Step 3: Generate recommendations
Based on analysis, create rightsizing recommendations:
Current configuration
Recommended configuration
Estimated savings
Risk assessment
Step 4: Validate and implement
Before making changes:
Verify recommendations with application owners
Test in non-production environments
Implement with rollback capability
Monitor post-change performance
Step 5: Continuous optimization
Rightsizing isn't one-time:
Workloads change over time
New instance types become available
Pricing changes affect optimal configurations
Build rightsizing into regular operations
Rightsizing vs. other optimization methods
Method | What It Does | Best For |
|---|
Method | What It Does | Best For |
|---|---|---|
Rightsizing | Match resources to workload | Over-provisioned resources |
Reserved Instances | Commit for discount | Steady-state workloads |
Savings Plans | Flexible commitments | Consistent compute usage |
Spot Instances | Use spare capacity | Fault-tolerant workloads |
Power Scheduling | Turn off when not needed | Non-production environments |
Key insight: Rightsize first, then commit. Buying reserved instances for over-provisioned resources locks in waste.
How CerteroX helps with cloud rightsizing
CerteroX Cloud Management delivers comprehensive cloud cost management including AI-powered rightsizing recommendations.
Capabilities
Multi-cloud visibility: AWS, Azure, GCP, Oracle Cloud, Kubernetes
Utilization analysis: Continuous monitoring of resource usage
AI-powered recommendations: Intelligent rightsizing suggestions
Impact modeling: See savings before making changes
Implementation tracking: Monitor optimization results
Results
Organizations using CerteroX Cloud Management achieve 38% average cloud savings through rightsizing and other FinOps practices.
FinOps Foundation member
Certero is a FinOps Foundation member, committed to advancing FinOps practices and helping organizations bring financial accountability to cloud spending.
Recognition
#1 rated on Gartner Peer Insights for IT Asset Management
97% of customers recommend Certero
Frequently asked questions
How much can rightsizing save?
Typical savings range from 20-40% on compute costs. The exact amount depends on current over-provisioning levels.
Will rightsizing affect application performance?
When done correctly, no. Proper rightsizing uses utilization data to ensure resources match actual needs. Some organizations see improved performance after rightsizing due to better resource selection.
How often should we rightsize?
Review rightsizing opportunities monthly at minimum. Cloud providers release new instance types regularly, and workload patterns change over time.
Should we rightsize before buying reserved instances?
Yes. Always rightsize first, then commit. Buying reservations for over-provisioned resources locks in waste for 1-3 years.
Can rightsizing be automated?
Partially. Recommendation generation can be fully automated. Implementation typically requires human approval due to application impact considerations.
What's the difference between rightsizing and auto-scaling?
Auto-scaling adjusts capacity dynamically based on demand. Rightsizing sets the baseline configuration. Both are complementary—rightsize the baseline, then auto-scale for variable demand.
Related resources
Last updated: February 2026