조직의 클라우드 여정의 모든 단계에서 비용에 영향을 미치는 결정을 내리는 설계자, 개발자, 관리자, 운영자
온프레미스 및 클라우드 워크로드의 비용 모델은 크게 다릅니다.
온프레미스 IT 비용에는 자본적 지출 (CapEx)과 운영적 지출 (OpEx)이 포함됩니다. 온프레미스 하드웨어 및 소프트웨어 애셋은 획득되며 획득 비용은 애셋의 운영 수명에 걸쳐 감가상각됩니다. 클라우드에서 대부분의 클라우드 리소스 비용은 클라우드 리소스가 사용될 때 비용이 발생하는 OpEx로 처리됩니다. 이러한 근본적인 차이점은 비용 최적화의 다음 핵심 원칙의 중요성을 강조합니다.
AI 및 ML 워크로드와 관련된 비용 최적화 원칙 및 권장사항은 Well-Architected Framework의 AI 및 ML 관점: 비용 최적화를 참조하세요.
핵심 원칙
Well-Architected Framework의 비용 최적화 요소에 있는 권장사항은 다음 핵심 원칙에 매핑됩니다.
클라우드 지출과 비즈니스 가치 조정:
IT 지출을 비즈니스 목표에 맞게 조정하여 클라우드 리소스가 측정 가능한 비즈니스 가치를 제공하도록 합니다.
비용 인식 문화 조성:
조직 전체에서 사용자가 자신의 결정과 활동이 비용에 미치는 영향을 고려하고 정보에 입각한 결정을 내리는 데 필요한 비용 정보에 액세스할 수 있도록 합니다.
리소스 사용량 최적화: 필요한 리소스만 프로비저닝하고 사용한 리소스에 대해서만 비용을 지불합니다.
지속적으로 최적화:
클라우드 리소스 사용량과 비용을 지속적으로 모니터링하고 필요에 따라 사전 조치를 취하여 지출을 최적화합니다. 이 접근 방식은 심각한 문제가 되기 전에 잠재적인 비용 비효율성을 식별하고 해결하는 것을 포함합니다.
이러한 원칙은 클라우드 FinOps의 핵심 원칙과 밀접하게 관련되어 있습니다.
FinOps는 조직의 규모나 클라우드 성숙도와 관계없이 모든 조직에 적용됩니다. 이러한 원칙을 채택하고 관련 권장사항을 따르면 클라우드 여정 전반에서 비용을 관리하고 최적화할 수 있습니다.
[[["이해하기 쉬움","easyToUnderstand","thumb-up"],["문제가 해결됨","solvedMyProblem","thumb-up"],["기타","otherUp","thumb-up"]],[["이해하기 어려움","hardToUnderstand","thumb-down"],["잘못된 정보 또는 샘플 코드","incorrectInformationOrSampleCode","thumb-down"],["필요한 정보/샘플이 없음","missingTheInformationSamplesINeed","thumb-down"],["번역 문제","translationIssue","thumb-down"],["기타","otherDown","thumb-down"]],["최종 업데이트: 2024-10-11(UTC)"],[[["\u003cp\u003eThe Cost Optimization pillar of the Google Cloud Well-Architected Framework provides principles and recommendations for managing cloud workload expenses.\u003c/p\u003e\n"],["\u003cp\u003eThis content is relevant to a wide audience, including executives, architects, developers, administrators, and operators involved in strategic cost management and cloud resource decisions.\u003c/p\u003e\n"],["\u003cp\u003eCore principles of cost optimization include aligning spending with business value, fostering cost awareness, optimizing resource usage, and continuous optimization.\u003c/p\u003e\n"],["\u003cp\u003eCloud cost models differ from on-premises costs, with cloud resources generally treated as operational expenditure (OpEx) rather than capital expenditure (CapEx), emphasizing the need for ongoing cost management.\u003c/p\u003e\n"],["\u003cp\u003eThe cost optimization pillar principles are closely aligned with cloud FinOps, emphasizing the importance of managing costs across the entire cloud journey regardless of organizational size.\u003c/p\u003e\n"]]],[],null,["# Well-Architected Framework: Cost optimization pillar\n\n| To view the content in the cost optimization pillar on a single page or to to get a PDF output of the content, see [View on one page](/architecture/framework/cost-optimization/printable).\n\nThe cost optimization pillar in the\n[Google Cloud Well-Architected Framework](/architecture/framework)\ndescribes principles and recommendations to optimize the cost of your workloads\nin Google Cloud.\n\nThe intended audience includes the following:\n\n- CTOs, CIOs, CFOs, and other executives who are responsible for strategic cost management.\n- Architects, developers, administrators, and operators who make decisions that affect cost at all the stages of an organization's cloud journey.\n\nThe cost models for on-premises and cloud workloads differ significantly.\nOn-premises IT costs include capital expenditure (CapEx) and operational\nexpenditure (OpEx). On-premises hardware and software assets are acquired and\nthe acquisition costs are\n[depreciated](https://en.wikipedia.org/wiki/Depreciation)\nover the operating life of the assets. In the cloud, the costs for most cloud\nresources are treated as OpEx, where costs are incurred when the cloud resources\nare consumed. This fundamental difference underscores the importance of the\nfollowing core principles of cost optimization.\n| **Note:** You might be able to classify the cost of some Google Cloud services (like Compute Engine sole-tenant nodes) as capital expenditure. For more information, see [Sole-tenancy accounting FAQ](/compute/docs/nodes/sole-tenancy-accounting-faq).\n\n\nFor cost optimization principles and recommendations that are specific to AI and ML workloads, see\n[AI and ML perspective: Cost optimization](/architecture/framework/perspectives/ai-ml/cost-optimization)\nin the Well-Architected Framework.\n\nCore principles\n---------------\n\nThe recommendations in the cost optimization pillar of the Well-Architected Framework\nare mapped to the following core principles:\n\n- [**Align cloud spending with business\n value**](/architecture/framework/cost-optimization/align-cloud-spending-business-value): Ensure that your cloud resources deliver measurable business value by aligning IT spending with business objectives.\n- [**Foster a culture of cost\n awareness**](/architecture/framework/cost-optimization/foster-culture-cost-awareness): Ensure that people across your organization consider the cost impact of their decisions and activities, and ensure that they have access to the cost information required to make informed decisions.\n- [**Optimize resource\n usage**](/architecture/framework/cost-optimization/optimize-resource-usage): Provision only the resources that you need, and pay only for the resources that you consume.\n- [**Optimize\n continuously**](/architecture/framework/cost-optimization/optimize-continuously): Continuously monitor your cloud resource usage and costs, and proactively make adjustments as needed to optimize your spending. This approach involves identifying and addressing potential cost inefficiencies before they become significant problems.\n\nThese principles are closely aligned with the core tenets of\n[cloud FinOps](/learn/what-is-finops?).\nFinOps is relevant to any organization, regardless of its size or maturity in\nthe cloud. By adopting these principles and following the related\nrecommendations, you can control and optimize costs throughout your journey in\nthe cloud.\n\nContributors\n------------\n\nAuthor: [Nicolas Pintaux](https://www.linkedin.com/in/nicolaspintaux) \\| Customer Engineer, Application Modernization Specialist\n\nOther contributors:\n\n- [Anuradha Bajpai](https://www.linkedin.com/in/anuradhabajpai) \\| Solutions Architect\n- [Daniel Lees](https://www.linkedin.com/in/daniellees) \\| Cloud Security Architect\n- [Eric Lam](https://www.linkedin.com/in/ericlam) \\| Head of Google Cloud FinOps\n- [Fernando Rubbo](https://www.linkedin.com/in/fernandorubbo) \\| Cloud Solutions Architect\n- [Filipe Gracio, PhD](https://www.linkedin.com/in/filipegracio) \\| Customer Engineer, AI/ML Specialist\n- [Gary Harmson](https://www.linkedin.com/in/garyharmson) \\| Principal Architect\n- [Jose Andrade](https://www.linkedin.com/in/jmandrade) \\| Customer Engineer, SRE Specialist\n- [Kent Hua](https://www.linkedin.com/in/kenthua) \\| Solutions Manager\n- [Kumar Dhanagopal](https://www.linkedin.com/in/kumardhanagopal) \\| Cross-Product Solution Developer\n- [Marwan Al Shawi](https://www.linkedin.com/in/marwanalshawi) \\| Partner Customer Engineer\n- [Radhika Kanakam](https://www.linkedin.com/in/radhika-kanakam-18ab876) \\| Program Lead, Google Cloud Well-Architected Framework\n- [Samantha He](https://www.linkedin.com/in/samantha-he-05a98173) \\| Technical Writer\n- [Steve McGhee](https://www.linkedin.com/in/stevemcghee) \\| Reliability Advocate\n- [Sergei Lilichenko](https://www.linkedin.com/in/sergei-lilichenko) \\| Solutions Architect\n- [Wade Holmes](https://www.linkedin.com/in/wholmes) \\| Global Solutions Director\n- [Zach Seils](https://www.linkedin.com/in/zachseils) \\| Networking Specialist\n\n\u003cbr /\u003e"]]