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Resource Sharing Beyond Boundaries
  Mohit Soni Santosh Marella
Adam Bordelon Anoop Dawar Ben Hindman
Brandon Gulla Danese Cooper Darin Johnson
Jim Klucar Kannan Rajah Ken Sipe
Luciano Resende Meghdoot Bhattacharya Paul Reed
Renan DelValle Ruth Harris Shingo Omura
Swapnil Daingade Ted Dunning Will Ochandarena
Yuliya Feldman Zhongyue Luo
Agenda
What's up with Datacenters these days?
Apache Mesos vs. Apache Hadoop/YARN?
Why would you want/need both?
Resource Sharing with Apache Myriad
What's running on your datacenter?
Tier 1 services
Tier 2 services
High Priority Batch
Best Effort, backfill
Requirements
Programming models based on resources,
not machines
Custom resource types
Custom scheduling algorithms:
Fast vs. careful/slow
Lightweight executors, fast task launch time
Multi-tenancy, utilization, strong isolation
Hadoop and More
Support Hadoop/BigData ecosystem
Support arbitrary (legacy) processes/containers
Connect Big Data to non-Hadoop apps,
share data, resources
Mesos from 10,000 feet
 Open Source Apache project
 Cluster Resource Manager
 Scalable to 10,000s of nodes
 Fault-tolerant, no SPOF
 Multi-tenancy, Resource Isolation
 Improved resource utilization
Mesos is more than
Yet Another Resource Negotiator
 Long-running services; real-time jobs
 Native Docker; cgroups for years;
Isolate cpu/mem/disk/net/other
 Distributed systems SDK;
~200 loc for a new app
 Core written in C++ for performance,
Apps in any language
Why two resource managers?
Static Partitioning sucks
Hadoop teams fine with isolated clusters,
but Ops team unhappy; slow to provision
Resource silos, no elasticity
Want to run Hadoop on the same infrastructure,
without interrupting Tier-1 services
Want multi-tenancy, resource sharing/isolation
Introducing Myriad
Myriad Overview
Mesos Framework for Apache YARN
Mesos manages DC, YARN manages Hadoop
Coarse and fine grained resource sharing
Resource Sharing
Demo
Myriad improves Mesos
 Tighter integration with Hadoop frameworks
like HBase, Hive, Pig
Borrow resources from Hadoop
when traffic spikes for tier-1 services
Backfill unused resource capacity
with best-effort Hadoop jobs
 No Mesos code changes necessary


Myriad improves Hadoop
 Elastic scaling
 Fault-tolerant: Maintain NM capacity
 Share resources with other workloads,
improve resource utilization
 High SLA hadoop jobs unaffected
 No YARN/Hadoop code changes
Other Features
RM failover/discovery using
Marathon/Mesos-DNS
Distribution of hadoop binaries
Web Interface
Myriad scheduler HA, task reconciliation
(in progress)
Ability to launch Job History Server
(in progress)
Your favorite feature here!
Learn More!
https://github.com/mesos/myriad
dev@myriad.incubator.apache.org
MYRIAD JIRA
Apache Myriad Incubator Proposal
Apache Myriad Incubator Status Page

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Resource Sharing Beyond Boundaries - Apache Myriad

  • 1. Resource Sharing Beyond Boundaries   Mohit Soni Santosh Marella
  • 2.
  • 3.
  • 4. Adam Bordelon Anoop Dawar Ben Hindman Brandon Gulla Danese Cooper Darin Johnson Jim Klucar Kannan Rajah Ken Sipe Luciano Resende Meghdoot Bhattacharya Paul Reed Renan DelValle Ruth Harris Shingo Omura Swapnil Daingade Ted Dunning Will Ochandarena Yuliya Feldman Zhongyue Luo
  • 5. Agenda What's up with Datacenters these days? Apache Mesos vs. Apache Hadoop/YARN? Why would you want/need both? Resource Sharing with Apache Myriad
  • 6. What's running on your datacenter? Tier 1 services Tier 2 services High Priority Batch Best Effort, backfill
  • 7. Requirements Programming models based on resources, not machines Custom resource types Custom scheduling algorithms: Fast vs. careful/slow Lightweight executors, fast task launch time Multi-tenancy, utilization, strong isolation
  • 8. Hadoop and More Support Hadoop/BigData ecosystem Support arbitrary (legacy) processes/containers Connect Big Data to non-Hadoop apps, share data, resources
  • 9. Mesos from 10,000 feet  Open Source Apache project  Cluster Resource Manager  Scalable to 10,000s of nodes  Fault-tolerant, no SPOF  Multi-tenancy, Resource Isolation  Improved resource utilization
  • 10. Mesos is more than Yet Another Resource Negotiator  Long-running services; real-time jobs  Native Docker; cgroups for years; Isolate cpu/mem/disk/net/other  Distributed systems SDK; ~200 loc for a new app  Core written in C++ for performance, Apps in any language
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  • 14. Why two resource managers?
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  • 16. Static Partitioning sucks Hadoop teams fine with isolated clusters, but Ops team unhappy; slow to provision Resource silos, no elasticity Want to run Hadoop on the same infrastructure, without interrupting Tier-1 services Want multi-tenancy, resource sharing/isolation
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  • 19. Myriad Overview Mesos Framework for Apache YARN Mesos manages DC, YARN manages Hadoop Coarse and fine grained resource sharing
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  • 39. Demo
  • 40. Myriad improves Mesos  Tighter integration with Hadoop frameworks like HBase, Hive, Pig Borrow resources from Hadoop when traffic spikes for tier-1 services Backfill unused resource capacity with best-effort Hadoop jobs  No Mesos code changes necessary  
  • 41. Myriad improves Hadoop  Elastic scaling  Fault-tolerant: Maintain NM capacity  Share resources with other workloads, improve resource utilization  High SLA hadoop jobs unaffected  No YARN/Hadoop code changes
  • 42. Other Features RM failover/discovery using Marathon/Mesos-DNS Distribution of hadoop binaries Web Interface Myriad scheduler HA, task reconciliation (in progress) Ability to launch Job History Server (in progress) Your favorite feature here!
  • 43. Learn More! https://github.com/mesos/myriad dev@myriad.incubator.apache.org MYRIAD JIRA Apache Myriad Incubator Proposal Apache Myriad Incubator Status Page