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Optimize cloud costs through resource rightsizing, tagging strategies, reserved instances, and spending analysis. Use when reducing cloud expenses, analyzing infrastructure costs, or implementing cost governance policies.
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SOC 職業分類に基づく
Perform code review. Quality analysis. Acceptance criteria verification. Best practices review.
Transform extracted epics and user stories into Jira-ready format following a benchmark template. Handles field mapping, formatting for Jira markdown compatibility, two-gate user review, and guidance for Jira issue creation via Atlassian tools.
Identify and structure epics and user stories from workshop materials (cleaned transcripts, Figma designs, codebase analysis, and other documents). Produces a business-oriented task breakdown with dependencies, assumptions, and open questions.
Analyze extracted epics and user stories for quality gaps, missing edge cases, and improvement opportunities. Runs domain-agnostic analysis passes, optionally enriches findings with Jira board context, and produces accept/reject suggestions that refine the task list before Jira formatting.
Design the architecture to solve a given task. Propose the solutions to be used to deliver the task following the best practices and standards.
Discover and establish technical context before implementing any feature. Prioritize project instructions, existing codebase patterns, and external documentation in that order. Use for any task requiring understanding of project conventions, coding standards, architecture patterns, and established practices before writing code.
| name | tsh-optimizing-cloud-cost |
| description | Optimize cloud costs through resource rightsizing, tagging strategies, reserved instances, and spending analysis. Use when reducing cloud expenses, analyzing infrastructure costs, or implementing cost governance policies. |
| user-invocable | false |
| Workload Type | AWS | Azure | GCP | Savings |
|---|---|---|---|---|
| Steady-state (24/7) | Reserved Instances / Savings Plans | Reserved VMs | Committed Use | 30-72% |
| Variable / burst | On-Demand + Auto-scaling | Pay-as-you-go | On-Demand | Baseline |
| Fault-tolerant batch | Spot Instances | Spot VMs | Preemptible | Up to 90% |
| Serverless / event-driven | Lambda | Functions | Cloud Functions | Pay-per-use |
| Data Access Pattern | AWS | Azure | GCP |
|---|---|---|---|
| Frequent (hot) | S3 Standard | Hot | Standard |
| Infrequent (30+ days) | S3 Standard-IA | Cool | Nearline |
| Rare (90+ days) | S3 Glacier | Cold | Coldline |
| Archive (365+ days) | S3 Deep Archive | Archive | Archive |
Rule: Implement lifecycle policies to auto-transition data between tiers.
| Tag | Purpose | Example |
|---|---|---|
Environment | Cost allocation by env | production, staging |
Project | Cost allocation by project | my-project |
CostCenter | Finance reporting | engineering |
Owner | Contact for unused resources | team@example.com |
ManagedBy | Track IaC vs manual | terraform |
Reference: See references/tagging-standards.md for full standards.
| ❌ Don't | ✅ Do |
|---|---|
| Over-provision "just in case" | Right-size based on metrics, scale up if needed |
| Use On-Demand for steady workloads | Use Reserved/Committed for predictable usage |
| Store all data in hot tier | Implement lifecycle policies |
| Skip tagging | Tag everything for cost visibility |
| Review costs monthly | Review weekly, alert on anomalies |
| Provider | Tools |
|---|---|
| AWS | Cost Explorer, Cost Anomaly Detection, Compute Optimizer |
| Azure | Cost Management, Advisor |
| GCP | Cost Management, Recommender |
| Multi-cloud | CloudHealth, Cloudability, Kubecost |
references/tagging-standards.md - Tagging conventions and enforcementtsh-implementing-terraform-modules - For resource provisioningtsh-designing-multi-cloud-architecture - For cloud selection