Use when performing multi cloud cost comparison — provides a structured framework for comparing costs across multiple cloud providers for equivalent workloads. Covers service-level price comparison, TCO analysis, hidden cost identification, discount program evaluation, and recommendation generation for optimal cloud placement.
Scanned 9/8/2026
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---
name: multi-cloud-cost-comparison
enabled: true
description: |
Use when performing multi cloud cost comparison — provides a structured
framework for comparing costs across multiple cloud providers for equivalent
workloads. Covers service-level price comparison, TCO analysis, hidden cost
identification, discount program evaluation, and recommendation generation for
optimal cloud placement.
required_connections:
- prefix: cloud-billing
label: "Cloud Billing Accounts"
config_fields:
- key: providers_to_compare
label: "Cloud Providers to Compare"
required: true
placeholder: "e.g., AWS, GCP, Azure"
- key: workload_description
label: "Primary Workload Description"
required: true
placeholder: "e.g., web application with 10k daily active users"
- key: comparison_period
label: "Cost Comparison Period"
required: false
placeholder: "e.g., 1 year, 3 years"
features:
- COST_MANAGEMENT
- FINOPS
- MULTI_CLOUD
---
# Multi-Cloud Cost Comparison
## Phase 1: Workload Definition
1. Define workload requirements
- [ ] Compute (vCPUs, memory, GPU)
- [ ] Storage (block, object, file, volume)
- [ ] Database (type, size, IOPS, replicas)
- [ ] Networking (egress, load balancing, CDN)
- [ ] Managed services (containers, serverless, ML)
2. Document performance requirements (latency, throughput)
3. Specify availability requirements (SLA, multi-region)
4. Identify compliance and data residency constraints
## Phase 2: Service Mapping
### Equivalent Service Comparison
| Capability | AWS | GCP | Azure | Notes |
|-----------|-----|-----|-------|-------|
| Compute | EC2 | Compute Engine | VMs | |
| Kubernetes | EKS | GKE | AKS | |
| Serverless | Lambda | Cloud Functions | Functions | |
| Object Storage | S3 | Cloud Storage | Blob Storage | |
| Relational DB | RDS | Cloud SQL | SQL Database | |
| NoSQL DB | DynamoDB | Firestore | Cosmos DB | |
| Cache | ElastiCache | Memorystore | Cache for Redis | |
| CDN | CloudFront | Cloud CDN | Front Door | |
| Load Balancer | ALB/NLB | Cloud LB | App Gateway | |
## Phase 3: Cost Calculation
### Per-Service Cost Comparison
| Service | Spec | AWS ($/mo) | GCP ($/mo) | Azure ($/mo) | Cheapest |
|---------|------|-----------|-----------|-------------|----------|
| Compute | | | | | |
| Storage | | | | | |
| Database | | | | | |
| Networking | | | | | |
| Other managed | | | | | |
| **Total** | | **$** | **$** | **$** | |
1. Calculate on-demand pricing for each provider
2. Apply available discounts (RI, CUD, Savings Plans)
3. Include data transfer and egress costs
4. Account for support plan costs
5. Factor in free tier benefits where applicable
## Phase 4: Hidden Cost Analysis
1. Identify costs often missed in comparisons
- [ ] Data egress between regions and to internet
- [ ] API call charges
- [ ] Logging and monitoring costs
- [ ] Cross-AZ data transfer
- [ ] IP address charges
- [ ] License surcharges (Windows, enterprise DB)
2. Calculate operational costs (staffing, training, tooling)
3. Factor in migration costs if switching providers
## Phase 5: TCO Analysis
### Total Cost of Ownership (3-Year)
| Category | AWS | GCP | Azure |
|----------|-----|-----|-------|
| Infrastructure | $ | $ | $ |
| Discounts (RI/CUD) | -$ | -$ | -$ |
| Data transfer | $ | $ | $ |
| Support | $ | $ | $ |
| Operational (staff/tools) | $ | $ | $ |
| Migration cost | $ | $ | $ |
| **3-Year TCO** | **$** | **$** | **$** |
## Phase 6: Recommendation
1. Rank providers by total cost for the workload
2. Identify optimal provider per service category
3. Evaluate multi-cloud strategy if beneficial
4. Consider non-cost factors (features, ecosystem, expertise)
5. Generate final recommendation with justification
## Counter-Rationalizations
| Shortcut | Counter | Why |
|----------|---------|-----|
| "We can skip some steps for this case" | Adapt the workflow steps, don't skip them | Skipped steps are where incidents and oversights originate |
| "The user seems to already know what to do" | Complete all workflow phases with the user | The workflow catches blind spots that experience alone misses |
| "This is a minor case, full process is overkill" | Scale the process down, don't turn it off | Minor cases become major when unstructured; the process scales, not disappears |
| "I'll fill in the details later" | Complete each section before moving on | Deferred details are forgotten; real-time capture is more accurate |
| "The template output isn't necessary" | Always produce the structured output format | Structured output enables comparison, audit trails, and handoff to other teams |
## Output Format
- **Service Mapping Table**: Equivalent services across providers
- **Cost Comparison Spreadsheet**: Detailed line-item pricing
- **TCO Analysis**: 3-year total cost including hidden costs
- **Recommendation Report**: Provider ranking with justification
- **Sensitivity Analysis**: How costs change with scaling
## Action Items
- [ ] Define workload requirements and specifications
- [ ] Collect current pricing for all service equivalents
- [ ] Calculate costs with applicable discount programs
- [ ] Identify and quantify hidden costs
- [ ] Complete TCO analysis
- [ ] Present recommendation to stakeholders
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