Sep 2012 HUG: Elastic, Multi-tenant, Highly Available Hadoop on Demand
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Sep 2012 HUG: Elastic, Multi-tenant, Highly Available Hadoop on Demand

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Serengeti is an open-source project, initiated by VMware, to enable the rapid deployment of Hadoop clusters in virtual environments. While Hadoop clusters are typically run on physical machines, ...

Serengeti is an open-source project, initiated by VMware, to enable the rapid deployment of Hadoop clusters in virtual environments. While Hadoop clusters are typically run on physical machines, Serengeti aims to bridge Hadoop and virtualization, and bring the classic benefits of virtualization to the Hadoop user. Leveraging virtual machines, Serengeti-deployed clusters can be simply operated, configured for HA protection, and made elastic through the decoupling of Hadoop compute and data layers. In this talk, we explore each of these aspects of running Hadoop on a virtual platform.

Presenter: Kevin Leong, Product Manager, VMware

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Sep 2012 HUG: Elastic, Multi-tenant, Highly Available Hadoop on Demand Sep 2012 HUG: Elastic, Multi-tenant, Highly Available Hadoop on Demand Presentation Transcript

  • Elastic, Multi-tenant, Highly Available Hadoopon DemandKevin Leongkleong@vmware.com © 2012 VMware Inc. All rights reserved
  • Agenda VMware Data Products Current Hadoop Challenges Simple, Reliable, Elastic Hadoop on Demand Summary2
  • The Database is Being Stretched Fast Data Global access patterns Mobile app proliferation Big Data Flexible Data Petabytes vs. Multi-structured data Gigabytes Developer productivity Democratize BI Cloud Delivery Virtualized Offered “-as-a-Service”3
  • Big, Fast and Flexible Data Big Fast Flexible Big Data OLTP OSS Relational Processing workloads vPostgres Object Serengeti GemFire Big Data Analytic Key / Value Analytics workloads Document Cloud Delivery Model Data as a service for private and public clouds4
  • AgendaVMware Data ProductsCurrent Hadoop ChallengesSimple, Reliable, Elastic Hadoop on Demand
  • ERROR: stackunderflowOFFENDING COMMAND: ~STACK: