Cost Optimization Report

Step 2 — Idle & Unused Resource Detection

For each service category, identify resources with zero or near-zero utilization:

Compute:

• Stopped/terminated EC2/GCE/VMs still incurring storage costs
• EC2 instances with CPU < 5% over 14 days
• Auto Scaling Groups at minimum capacity 24/7 (no scaling events)

Storage:

• Unattached EBS volumes / Persistent Disks
• Snapshots older than 90 days without recent access
• S3 buckets with no GET requests in 30 days (excluding logging buckets)
• Empty storage containers / buckets

Networking:

• Elastic IPs not associated with running instances
• Idle NAT Gateways (< 100MB/day transfer)
• Unused Load Balancers (0 healthy targets or 0 requests)
• Unattached Elastic Network Interfaces

Database:

• RDS/Cloud SQL instances with CPU < 2% and zero connections for 7 days
• Read replicas with zero replica lag and zero queries

Other:

• Unused Elastic Container Registries with images > 1 year old
• CloudFormation stacks in ROLLBACK state
• Forgotten development environments running in production accounts

Threshold for waste reporting: ${{ cost_threshold | "50" }}/month minimum

Step 3 — Rightsizing Analysis

Identify over-provisioned resources:

Compute Rightsizing:

For each compute instance with metrics:
- Average CPU over 14 days < 20% → downsize
- Average memory over 14 days < 30% → downsize
- Max CPU burst < 50% → no need for burstable exclusion
- Calculate estimated savings from downsizing

Database Rightsizing:

For each database instance:
- Average CPU < 15% → eligible for smaller instance class
- FreeableMemory average > 75% of allocated → memory over-provisioned
- IOPS average < 30% of provisioned → IOPS over-provisioned (if io1/io2)

Step 4 — Commitment / Reserved Capacity Analysis

Evaluate savings from longer-term commitments:

1. On-Demand vs Reserved Instance coverage

   • What % of compute is on-demand vs reserved?
   • Which on-demand instances are running 24/7 (RI candidates)?
   • Reserved Instance utilization — are purchased RIs being used?

2. Savings Plan analysis

   • What is current Savings Plan coverage?
   • Recommended Savings Plan commitment amount

3. Commitment recommendation:

   • Stable workloads running > 80% of time → 1-year reserved/committed
   • Very stable workloads → 3-year for maximum savings
   • Variable workloads → on-demand or spot-eligible

Step 5 — Spot / Preemptible Opportunities

Identify workloads that can run on spot/preemptible instances:

• Batch processing jobs
• CI/CD build agents
• Dev/test environments
• Stateless application tier (with proper interruption handling)
• ML training workloads

Estimated savings: 60-80% vs on-demand pricing

Step 6 — Data Transfer & Network Costs

Analyze network spend:

• Cross-region data transfer costs
• NAT Gateway usage vs VPC endpoints (S3, DynamoDB)
• CloudFront vs direct S3 serving for public assets
• VPC endpoint usage opportunities (eliminate NAT for AWS service traffic)

Step 7 — Anomaly Detection

Identify unusual cost spikes:

• Services with >20% MoM increase without corresponding business growth
• New services with unexpected costs (developer experiments left running)
• Data transfer spikes (potential data exfiltration or misconfigured logging)
• Unexpected region usage

Step 8 — Prioritized Recommendations

Rank all findings by impact and implementation effort:

SAVINGS RECOMMENDATIONS
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

QUICK WINS (implement this week) — Low risk, immediate savings
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
1. [Resource]: [Description]
   Monthly savings: $X,XXX | Risk: Low | Effort: Hours
   Action: [specific command or step]

2. [Resource]: [Description]
   Monthly savings: $XXX | Risk: Low | Effort: Minutes
   Action: [specific command or step]

MEDIUM TERM (implement this month) — Some coordination needed
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
3. Rightsizing [service]: [X] instances downsize from [type] to [type]
   Monthly savings: $X,XXX | Risk: Medium | Effort: Days
   Action: [specific steps with validation approach]

4. Reserved Instances: Purchase [X] RIs for [service]
   Monthly savings: $X,XXX | Risk: Low | Effort: Hours (approval needed)
   Action: [purchase via console/API]

STRATEGIC (this quarter) — Requires architectural changes
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
5. [Architectural change]: [description]
   Monthly savings: $X,XXX | Risk: High | Effort: Weeks
   Action: [high-level steps and considerations]

Step 9 — Executive Summary

Produce a one-page summary:

COST OPTIMIZATION REPORT — {{ cloud_provider | uppercase }}
Generated: [date]
Period: {{ time_period }}
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

CURRENT STATE
• Monthly Spend: $X,XXX
• MoM Trend: [+/-X%]
• Top Cost Driver: [service]

SAVINGS IDENTIFIED
• Quick Wins: $X,XXX/month (implement in <1 week)
• Medium Term: $X,XXX/month (implement in <1 month)
• Strategic: $X,XXX/month (implement in <1 quarter)
• Total Potential: $XX,XXX/month (XX% reduction)

TOP 3 RECOMMENDATIONS
1. [action]: $X,XXX/month
2. [action]: $X,XXX/month
3. [action]: $X,XXX/month

NEXT STEPS
• [Owner]: [Action] by [Date]
• [Owner]: [Action] by [Date]

Counter-Rationalizations

Output Format

Produce a structured report with:

1. Cost baseline with trends
2. Waste inventory (idle/unused resources with monthly cost)
3. Rightsizing candidates with specific recommendations
4. Commitment opportunities with ROI calculations
5. Prioritized action plan sorted by savings impact
6. Executive summary for leadership sharing