{"templateName":"blog-page","cssClassNames":"blog-page page basicpage summit-page","allowedRenditionsWidth":["320","480","640","768","960","1200","1440","1920"],"language":"ko","description":"Snowflake Adaptive Compute는 이제 AWS, Azure 및 Google Cloud의 일부 리전에서 GA로 제공되며, 수동 튜닝 없이도 변수 및 AI 워크로드에 대해 향상된 가격 대비 성능을 제공합니다.","title":"Adaptive Compute: AWS, Azure 및 Google Cloud의 일부 리전에서 GA로 제공","analyticsPageType":"homepage","analyticsCategory":"general","analyticsSubCategory":"","excludeFromAnalytics":false,":mappedPath":"/ko/blog/adaptive-compute-ga-azure-google-cloud/",":type":"snowflake-site/components/structure/page",":items":{"root":{"columnCount":12,"columnClassNames":{"experiencefragment-banner":"aem-GridColumn aem-GridColumn--default--12","experiencefragment-sub-header":"aem-GridColumn aem-GridColumn--default--12","experiencefragment-pre-footer":"aem-GridColumn aem-GridColumn--default--12","experiencefragment-header":"aem-GridColumn 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photo of Likhita Thogersen of Snowflake","lazyEnabled":true,"width":"1254",":type":"snowflake-site/components/image"},"authorCta":{"id":"button-14bda642cc","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/blog/authors/likhita-thogersen/"},"linkTargetContentType":"DOCUMENT_LEARN",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"Likhita Thogersen"}},{"authorImage":{"id":"image-ef7157acdd","height":"400","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--8abfe0e1-f452-4f0c-85cb-2c21dbcc9bef/tehzeeb-versey-patel.png?preferwebp=true&quality=85","alt":"Avatar headshot of Tehzeeb Versey-Patel of Snowflake","lazyEnabled":true,"width":"400",":type":"snowflake-site/components/image"},"authorCta":{"id":"button-45bf436b44","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/blog/authors/tehzeeb-versey-patel/"},"linkTargetContentType":"DOCUMENT_LEARN",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"Tehzeeb Versey-Patel"}}],"image":{"id":"image-ace571a0d8","height":"720","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--67328fa5-6658-4ba6-bbee-8ef32ba1d78c/25-general.jpg?preferwebp=true&quality=85","lazyEnabled":true,"width":"1680",":type":"snowflake-site/components/image"},"timeToRead":"3","publicationDate":"JUL 29, 2026","tag":{"tagText":"제품 및 기술","tagColor":"#3F808A"},"title":{"lines":["Snowflake Adaptive Compute: 실제 워크로드에서 더욱 향상된 가격 대비 성능, 이제 AWS에 이어 Azure, GCP에서도 제공"],"type":"heading2",":type":"snowflake-site/components/title-v2"},":type":"snowflake-site/components/blog/blog-hero"}},":itemsOrder":["blog_hero"]},"responsivegrid_content":{"columnCount":12,"columnClassNames":{"image":"aem-GridColumn aem-GridColumn--default--12","code_snippet":"aem-GridColumn aem-GridColumn--default--12","blog_text_1573939951":"aem-GridColumn aem-GridColumn--default--12","blog_text":"aem-GridColumn aem-GridColumn--default--12","image_1014883481":"aem-GridColumn aem-GridColumn--default--12","blog_text_725549142":"aem-GridColumn aem-GridColumn--default--12","blog_text_1418044943":"aem-GridColumn aem-GridColumn--default--12","blog_text_683512397":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","appliedCssClassNames":"snowflake-layout-container-inner-padding-small",":items":{"blog_text":{"id":"blog-text-952b38cc9b","text":"\u003Cp\u003EAI 워크로드는 예측 가능한 패턴으로 움직이지 않습니다. 대시보드 사용량은 갑자기 증가하고, 에이전트 활동은 계속 변합니다. 또한 최신 AI 앱은 데이터 준비, 검색, 추론 요청이 예측하기 어려운 방식으로 급증하기도 합니다. 따라서 워크로드가 어디에서 실행되든, 지속적인 튜닝 없이도 이러한 변화에 유연하게 대응할 수 있는 컴퓨팅 환경이 필요합니다.\u003C/p\u003E\r\n\u003Cp\u003ESnowflake Adaptive Compute는 변화하는 워크로드 수요에 맞춰 컴퓨팅 리소스를 자동으로 조정해, 많은 시간이 소요되는 수작업 튜닝과 유지 보수의 부담을 줄입니다. 이번에 새롭게 추가된 기능은 변동성이 큰 워크로드에서 실제 운영 환경의 가격 대비 성능을 더욱 향상하도록 설계되었으며, 이러한 기능은 \u003Ca rel=\"nofollow noopener noreferrer\" target=\"_blank\" href=\"https://www.snowflake.com/ko/blog/adaptive-compute-generally-available/?utm_source=linkedin&utm_medium=sm-boost&utm_campaign=compete&utm_cta=button&utm_content=1781617519\"\u003EAWS\u003C/a\u003E에 이어, 이제 Microsoft Azure와 Google Cloud 고객에게도 GA로 제공됩니다.\u003C/p\u003E\r\n\u003Cp\u003E \u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"image":{"id":"image-b63f740ccf","height":"783","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--f826b969-d07a-4840-8c21-59ecbfe5b676/a186f68f-da74-4504-8584-0987c85f6bf1.png?preferwebp=true&quality=85","alt":"Diagram showing how Adaptive Warehouses tap into shared compute and fuel Adaptive Compute","lazyEnabled":true,"width":"850",":type":"snowflake-site/components/image"},"blog_text_1418044943":{"id":"blog-text-8f3e43c871","text":"\u003Ch2\u003E다양한 AI 워크로드를 위한 컴퓨팅 엔진 \u003C/h2\u003E\n\u003Cp\u003EAdaptive Compute는 피크 트래픽에 대비해 오버 프로비저닝을 선택하거나 성능 저하 위험을 감수해야 하는 상황을 줄이고, 변화하는 워크로드 수요에 맞춰 컴퓨팅 리소스를 지속적으로 조정하도록 설계되었습니다. 이를 통해 성능을 유지하면서 수동 튜닝 부담을 낮추고, 팀은 웨어하우스 관리가 아니라 인사이트 제공에 집중할 수 있습니다. 이번 출시로 Adaptive Compute가 AWS, Microsoft Azure 및 Google Cloud의 일부 리전으로 확대되면서, 멀티 클라우드 환경 전반에서 이러한 적응형 이점을 활용할 수 있습니다.\u003C/p\u003E\n\u003Ch2\u003E변동성이 큰 워크로드를 위한 향상된 가격 대비 성능\u003C/h2\u003E\n\u003Cp\u003EAdaptive Compute의 최신 개선 사항은 동시성이 낮거나, 하루 동안 수요가 계속 변하거나 예측하기 어려운 시점에 급증하는 가변적인 워크로드에서 실제 운영 환경 기준의 가격 대비 성능을 향상합니다. \u003C/p\u003E\n\u003Cp\u003E2026년 6월에 출시된 Adaptive Compute 버전과 비교하면, 이제 고객은 워크로드 형태에 따라 최대 30%의 비용 절감 효과를 기대할 수 있습니다. 이를 통해 Adaptive Compute는 까다롭고 변화가 많은 여러 유형의 워크로드를 운영하는 기업에 더욱 매력적인 선택지가 되었습니다.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"image_1014883481":{"id":"image-5f55ee5cc4","height":"1024","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--04435107-9fe3-4cf7-9575-a2cb0105a12c/adaptive-30-percent-cheaper.png?preferwebp=true&quality=85","alt":"Bar chart showing up to 30% lower cost for the Adaptive version released July 23 compared to the version announced June 16 at time of GA","lazyEnabled":true,"width":"1536","title":"비용 개선 사항이 적용된 2026년 7월 23일 버전의 Adaptive Compute와 2026년 6월 16일 버전을 단일 사용자 10TB TPC-DS 벤치마크로 비교한 결과입니다. 실제 절감 효과는 클라우드, 리전, 웨어하우스 크기, 워크로드 및 사용 패턴에 따라 달라질 수 있습니다.",":type":"snowflake-site/components/image"},"blog_text_725549142":{"id":"blog-text-14f3a51afa","text":"\u003Ch2\u003E이제 Azure 및 Google Cloud의 일부 리전에서도 이용 가능 \u003C/h2\u003E\n\u003Cp\u003EAdaptive Compute는 6월에 \u003Ca href=\"https://www.snowflake.com/ko/blog/adaptive-compute-generally-available/?utm_source=linkedin&utm_medium=sm-boost&utm_campaign=compete&utm_cta=button&utm_content=1781617519\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003E발표된\u003C/a\u003E AWS 리전에 이어, Microsoft Azure 및 Google Cloud의 리전에서도 Enterprise+ 계정을 대상으로 GA로 제공됩니다.\u003C/p\u003E\n\u003Ch4\u003EMicrosoft Azure\u003C/h4\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E미주: \u003C/b\u003ECentral US(아이오와주), East US 2(버지니아주)\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E유럽: \u003C/b\u003EWest Europe(네덜란드), North Europe(아일랜드), UK South(런던), Switzerland North(취리히), Sweden Central(예블레)\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Ch4\u003EGoogle Cloud\u003C/h4\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E미주: \u003C/b\u003Eus-east4(버지니아주 북부)\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E유럽: \u003C/b\u003Eeurope-west 2(런던), europe-west 3(프랑크푸르트), europe-west 4(네덜란드)\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E아시아 태평양: \u003C/b\u003EAustralia-Southeast 2(멜버른)\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Ch4\u003EAWS\u003C/h4\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E미주: \u003C/b\u003EUS West 2(오리건주), US East 2(오하이오주)\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E유럽: \u003C/b\u003EEU West 1(아일랜드), EU Central 1(프랑크푸르트)\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E아시아 태평양: \u003C/b\u003EAP Northeast 1(도쿄), AP Southeast 2(시드니)\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Ch2\u003EAdaptive Compute 시작하기\u003C/h2\u003E\n\u003Cp\u003E이미 Snowflake를 사용하고 있다면 Adaptive Compute로의 전환은 매우 간단합니다. 인프라를 다시 구축하거나 기존 파이프라인과 스크립트의 웨어하우스 이름을 변경할 필요 없이, 간단한 구성 변경만으로 기존 Snowflake 표준 웨어하우스를 다운타임 없이 업그레이드할 수 있습니다. 따라서 기존 구성, 액세스 제어 정책, 모니터링 지표를 그대로 유지하면서 프로덕션 및 AI 워크로드를 원활하게 Adaptive Compute로 전환할 수 있습니다.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"code_snippet":{"id":"code-snippet-e0fd0af234","codeSnippet":"alter warehouse \u003Cwarehouse_name\u003E set warehouse_type='ADAPTIVE';","multiLine":true,":type":"snowflake-site/components/code-snippet"},"blog_text_683512397":{"id":"blog-text-8d5155c5cb","text":"\u003Cp\u003E분석, 처리량 및 DML 워크로드 전반의 설정 가이드와 벤치마크 결과는 \u003Ca rel=\"nofollow noopener noreferrer\" target=\"_blank\" href=\"https://www.snowflake.com/ko/blog/adaptive-compute-generally-available/?utm_source=linkedin&utm_medium=sm-boost&utm_campaign=compete&utm_cta=button&utm_content=1781617519\"\u003E6월 출시 발표 블로그 포스팅\u003C/a\u003E에서 확인할 수 있습니다.\u003C/p\u003E\n\u003Ch2\u003E다음 단계\u003C/h2\u003E\n\u003Cp\u003ESnowflake의 컴퓨팅 향상 기능과 이를 통해 조직이 운영 복잡성을 줄이면서 더 나은 성능을 실현하는 방법에 대해 자세히 알아보세요.\u003C/p\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Ca rel=\"nofollow noopener noreferrer\" target=\"_blank\" href=\"https://youtu.be/_KiqMbX3dnM?t=2829\"\u003E Snowflake AI Pulse\u003C/a\u003E 웨비나를 시청하고 Adaptive Compute가 AI 워크로드의 성공적인 운영을 어떻게 지원하는지 확인해 보세요.\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Ca rel=\"nofollow noopener noreferrer\" target=\"_blank\" href=\"https://www.snowflake.com/ko/product/features/adaptive-compute/?utm_campaign=compete&utm_source=linkedin&utm_medium=sm-boost&utm_content=1781617519&utm_cta=button\"\u003EAdaptive Compute\u003C/a\u003E의 주요 기능과 사용 사례를 살펴보세요.\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E제공 리전, 요구 사항 및 설정 방법에 대한 자세한 내용은 \u003Ca rel=\"nofollow noopener noreferrer\" target=\"_blank\" href=\"https://docs.snowflake.com/en/user-guide/warehouses-adaptive?utm_campaign=compete&utm_source=linkedin&utm_medium=sm-boost&utm_content=1781617519&utm_cta=button\"\u003E설명서\u003C/a\u003E에서 확인하세요.\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"blog_text_1573939951":{"id":"blog-text-6ed0583434","text":"\u003Cp\u003E \u003C/p\u003E\n\u003Cp\u003E\u003Ci\u003E미래 전망 진술: 이 콘텐츠에는 당사의 향후 제품 제공에 대한 미래 전망 진술이 포함되어 있으며, 이는 어떠한 제품 제공을 약속하는 것이 아닙니다. 실제 결과 및 제공 내용은 다를 수 있으며, 알려지거나 알려지지 않은 위험 및 불확실성의 영향을 받을 수 있습니다. 보다 자세한 내용은 최신 10-Q를 참조하세요.\u003C/i\u003E\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/blog/blog-text"}},":itemsOrder":["blog_text","image","blog_text_1418044943","image_1014883481","blog_text_725549142","code_snippet","blog_text_683512397","blog_text_1573939951"],":type":"wcm/foundation/components/responsivegrid"},"responsivegrid_premium_content_banner":{"columnCount":12,"columnClassNames":{},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","appliedCssClassNames":"snowflake-responsive-component-top-padding-medium",":items":{},":itemsOrder":[],":type":"wcm/foundation/components/responsivegrid"},"container_author_chip":{"layout":"RESPONSIVE_GRID","columnCount":12,"columnClassNames":{"author_chip":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 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"},{"authorImage":{"id":"image-ef7157acdd","height":"400","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--8abfe0e1-f452-4f0c-85cb-2c21dbcc9bef/tehzeeb-versey-patel.png?preferwebp=true&quality=85","alt":"Avatar headshot of Tehzeeb Versey-Patel of Snowflake","lazyEnabled":true,"width":"400",":type":"snowflake-site/components/image"},"authorCta":{"id":"button-45bf436b44","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/blog/authors/tehzeeb-versey-patel/"},"linkTargetContentType":"DOCUMENT_LEARN",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"Tehzeeb Versey-Patel"},"authorTitle":"Platform Product Marketing Lead, 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전략 및 사용 사례"],"type":"heading4",":type":"snowflake-site/components/title-v2"},"button":{"id":"button-bbbb83d0e3","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ko/resources/ebook/telecom-ai-transformation-comprehensive-strategy-and-use-cases/"},"linkTargetContentType":"DOCUMENT_LEARN",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"통신 산업의 AI 혁신: 종합 전략 및 사용 사례"},"image":{"id":"image-189f5cf5d9","height":"1165","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--655e695d-69c6-4d24-8274-67ce08ce4ff8/%25E1%2584%2590%25E1%2585%25A9%25E1%2586%25BC%25E1%2584%2589%25E1%2585%25B5%25E1%2586%25AB-%25E1%2584%2589%25E1%2585%25A1%25E1%2586%25AB%25E1%2584%258B%25E1%2585%25A5%25E1%2586%25B8%25E1%2584%258B%25E1%2585%25B4-ai-%25E1%2584%2592%25E1%2585%25A7%25E1%2586%25A8%25E1%2584%2589%25E1%2585%25B5%25E1%2586%25AB--%25E1%2584%258C%25E1%2585%25A9%25E1%2586%25BC%25E1%2584%2592%25E1%2585%25A1%25E1%2586%25B8-%25E1%2584%258C%25E1%2585%25A5%25E1%2586%25AB%25E1%2584%2585%25E1%2585%25A3%25E1%2586%25A8-%25E1%2584%2586%25E1%2585%25B5%25E1%2586%25BE-%25E1%2584%2589%25E1%2585%25A1%25E1%2584%258B%25E1%2585%25AD%25E1%2586%25BC-%25E1%2584%2589%25E1%2585%25A1%25E1%2584%2585%25E1%2585%25A8.png?preferwebp=true&quality=85","lazyEnabled":true,"width":"2064",":type":"snowflake-site/components/image"}}],":type":"snowflake-site/components/blog/related-content","isBlogPage":true}},":itemsOrder":["flexible_column_container","related_content"],"appliedCssClassNames":"snowflake-container"}},":itemsOrder":["container_breadcrumb","container_main_content"],":type":"wcm/foundation/components/responsivegrid"},"container_47873732":{"additionalClasses":"section--blog-newsletter","layout":"RESPONSIVE_GRID","columnCount":12,"columnClassNames":{"flexible_column_cont":"aem-GridColumn 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