Elastic data services on Mesos via Mesospheres DC/OS
Adam Bordelon and Mohit Soni demonstrate how projects like Apache Myriad (incubating) can install Hadoop on Mesosphere DC/OS alongside other data center-scale applications, enabling efficient resource sharing and isolation across a variety of distributed applications while sharing the same cluster resources and hence breaking silos.
| Talk Title | Elastic data services on Mesos via Mesospheres DC/OS |
| Speakers | |
| Conference | Strata + Hadoop World |
| Conf Tag | Make Data Work |
| Location | New York, New York |
| Date | September 27-29, 2016 |
| URL | Talk Page |
| Slides | Talk Slides |
| Video | |
Most data centers (and many cloud deployments) are statically partitioned into siloed clusters dedicated to running individual datacenter-scale applications, including web services, databases, and batch/stream processing. This static partitioning model limits overall cluster utilization, decreases flexibility, and poses operational challenges. There is an increasing need to integrate big data applications like Apache Hadoop and Apache Spark with other data center services like Apache Cassandra or Apache Kafka, ideally colocating the data with the services that need it. Adam Bordelon and Mohit Soni demonstrate how projects like Apache Myriad (incubating) can install Hadoop on Mesosphere DC/OS alongside other data center-scale applications, enabling efficient resource sharing and isolation across a variety of distributed applications while sharing the same cluster resources and hence breaking silos. The multitenancy strategy improves overall cluster utilization and operational efficiency while allowing cluster operators to run multiple isolated data services on the same hardware.
