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Enabling Production ML at Scale With LakehouseMarch 14, 9 AM PDT / 4 PM GMT
Register nowIntroductionModel Serving is built within the Databricks Lakehouse Platform and integrates with your lakehouse data, offering automatic lineage, governance and monitoring across data, features and model lifecycle. Simplify model deployment, reduce infrastructure overheads and accelerate time to production. With built-in auto-scaling capability, you can scale from zero all the way up to your most critical needs while paying only for the compute you use.Customer QuotesUnified with lakehouse dataDeep integration with the lakehouse provides automatic lineage, governance and monitoring across data, features and model lifecycleSimplified deploymentAutomated infrastructure configuration and maintenance to reduce overheads and accelerate your ML deploymentsReal-timeQuickly scale from zero all the way up to your most critical needs, and down as your needs change, while paying only for the compute you useGet started with these resourcesBlogAnnouncing General Availability of Databricks Model ServingDocumentationModel serving on the lakehouseeBookThe Big Book of Machine Learning Use CasesReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers
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