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Sharing resources with non-Hadoop workloads

by on Jul 11, 2013

  • 1,236 views

Enterprise data centers house numerous workloads. With Hadoop growing in these data centers, IT departments need tools to avoid creating silos, while maintaining SLAs, reporting and charge-back ...

Enterprise data centers house numerous workloads. With Hadoop growing in these data centers, IT departments need tools to avoid creating silos, while maintaining SLAs, reporting and charge-back requirements. We present a completely open source reference architecture including Apache Hadoop, Linux cgroups and namespace isolation, Gluster and HTCondor. Topics to be covered – . Augmenting existing HDFS and MapReduce infrastructure with dynamically provisioned resources . On-demand creating, growing and shrinking MapReduce infrastructure for user workload . Isolating workloads to enable multi-tenant access to resources . Publishing of resource utilization and accounting information for ingest into charge-back systems

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Sharing resources with non-Hadoop workloads Sharing resources with non-Hadoop workloads Presentation Transcript