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


  • 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


  • 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


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
  • 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!


Apache Myriad Incubator Proposal

Apache Myriad Incubator Status Page