cloud-finops
starsforks
How to install cloud-finops?
optimnow/cloud-finops-skills/cloud-finops
$npx -y skills add OptimNow/cloud-finops-skills --skill cloud-finopsExpert FinOps guidance covering cloud, AI, and SaaS technology spend. Includes AI cost management, GenAI capacity planning, self-hosted vs managed inference, Anthropic billing, AWS (EC2, Bedrock, SageMaker, GPU rightsizing, Savings Plans, CUR, commitment strategy), Azure (reserva
SKILL.md
| 1 | # FinOps - Expert Guidance |
| 2 | |
| 3 | > Built by OptimNow. Grounded in hands-on enterprise delivery, not abstract frameworks. |
| 4 | |
| 5 | --- |
| 6 | |
| 7 | ## How to use this skill |
| 8 | |
| 9 | This skill covers cloud, AI, SaaS, and adjacent technology spend domains. Use |
| 10 | `references/optimnow-methodology.md` as a reasoning lens (diagnose before prescribing, |
| 11 | connect cost to value, recommend progressively); then load the domain reference(s) |
| 12 | matching the query. |
| 13 | |
| 14 | ### Domain routing |
| 15 | |
| 16 | | Query topic | Load reference | |
| 17 | |---|---| |
| 18 | | AI costs, LLM inference, token economics, agentic cost patterns, AI ROI, AI cost allocation, GPU cost attribution, GPU telemetry, DCGM metrics, "GPU utilization is misleading", tensor core activity, GPU memory bandwidth, RAG harness costs | `references/finops-for-ai.md` | |
| 19 | | AI investment governance, AI Investment Council, stage gates, incremental funding, AI value management, AI practice operations | `references/finops-ai-value-management.md` | |
| 20 | | GenAI capacity planning, provisioned vs shared capacity, traffic shape, spillover, throughput units | `references/finops-genai-capacity.md` | |
| 21 | | Self-hosted vs managed AI inference, build vs buy LLM, vLLM, SGLang, llama.cpp, GPU rental, RunPod, CoreWeave, Lambda, hidden cost surface, ML-Ops maturity rubric, hybrid routing (LiteLLM, Portkey) | `references/finops-ai-self-hosted-vs-managed.md` | |
| 22 | | AWS billing, EC2 rightsizing, RIs, Savings Plans, commitment strategy, portfolio liquidity, phased purchasing, CUR, Data Exports for FOCUS 1.2, Cost Explorer hourly granularity, EDP negotiation, RDS cost management, database commitments, SageMaker AI Savings Plan, Database Savings Plan, SageMaker operational FinOps (real-time vs serverless vs async vs batch deployment patterns, Multi-Model Endpoints, Inference Components, notebook auto-shutdown), GPU instance rightsizing, MIG candidates, multi-GPU underutilization, outdated GPU generation modernization | `references/finops-aws.md` | |
| 23 | | AWS Bedrock billing, Bedrock provisioned throughput, model unit pricing, Bedrock batch inference, Application Inference Profiles, Bedrock Projects, prompt caching, IAM Principal Cost Allocation | `references/finops-bedrock.md` | |
| 24 | | Azure cost management, reservations, Savings Plans, Azure Hybrid Benefit, AHB, commitment strategy, portfolio liquidity, phased purchasing, sizing methodology, MACC, Azure Advisor, compute rightsizing, AKS optimisation, Azure Linux retirement, Node Auto Provisioning, NAP, database optimisation (Azure SQL, Postgres/MySQL, Cosmos), Log Analytics cost control, backup and snapshot management, storage tiering and lifecycle, networking cost, tagging and Azure Policy governance, FOCUS exports, EA-to-MCA transition, MCA contractual mechanics, billing hierarchy, ISF CSV deprecation | `references/finops-azure.md` | |
| 25 | | Azure OpenAI Service, Azure AI Foundry, PTU reservations, locality constraint, GPT-4o, GPT-5 pricing, AOAI spillover, fine-tuning costs | `references/finops-azure-openai.md` | |
| 26 | | Anthropic billing, Claude API costs, Claude Code costs, Opus, Sonnet, Haiku pricing, Fast mode, prompt caching, Batch API, long-context pricing, Managed Agents | `references/finops-anthropic.md` | |
| 27 | | GCP billing, Compute Engine, Cloud SQL, GCS, BigQuery billing export, BigQuery optimisation, FOCUS export, Sustained Use Discounts, SUDs, Committed Use Discounts, CUDs, Flexible CUDs, Spot VMs, Cloud Carbon Footprint | `references/finops-gcp.md` | |
| 28 | | GCP Vertex AI billing, Vertex provisioned throughput, Gemini pricing, Vertex batch prediction, default PAYG spillover | `references/finops-vertexai.md` | |
| 29 | | Tagging strategy, naming conventions, IaC enforcement, MCP governance | `references/finops-tagging.md` | |
| 30 | | FinOps framework 2026, 4 domains, 22 capabilities including Executive Strategy Alignment, Usage Optimization, Architecting & Workload Placement, Sustainability, KPIs & Benchmarking, Governance Policy & Risk, Automation Tools & Services, maturity model, phases, personas | `references/fino |
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