OPENSTACK AND BIG DATA, A LOVE STORY

Michael Still Senior Software Development Manager michael.still@rackspace.com or @mikal on twitter

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WHO IS THIS GUY? •  A Canberran born and bred •  An OpenStack developer since 2011, first commit

merged January 2012 -  https://review.openstack.org/#/c/2899/

•  A Compute Core Reviewer, former Compute PTL, and have served on the OpenStack Technical Committee

•  Manager for a team of OpenStack developers spread across Australia

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CAUTION, THIS BIT IS A TEST

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WHO IS RACKSPACE? •  Do any of you guys know who Rackspace is and how they fit into the

OpenStack story?

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BIG DATA •  Hopefully we’re all familiar with the term

•  That said, the basic idea is to store and process large amounts of data on commodity equipment

•  Pioneered by Internet companies •  But now used by many ”more traditional” organizations

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THE OLD WAY

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THE NEW WAY

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BIG DATA •  The most obvious thing here is that machine counts are increasing… •  We’re talking about hundreds or thousands of machines instead of the one

big machine

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BIG DATA •  The most obvious thing here is that machine counts are increasing… •  We’re talking about hundreds or thousands of machines instead of the one

big machine

•  And our operational budgets are not increasing with machine count (of course)

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BIG DATA •  The most obvious thing here is that machine counts are increasing… •  We’re talking about hundreds or thousands of machines instead of the one

big machine

•  And our operational budgets are not increasing with machine count (of course)

•  So we need to automate more

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OPENSTACK COMPUTE •  From day zero OpenStack supported running virtual machines •  We call them instances

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OPENSTACK COMPUTE •  From day zero OpenStack supported running virtual machines •  We call them instances

•  Virtual machines aren’t a great choice for most big data applications though -  For example, its nice if you replicate your data -  But what if all the VMs containing replicas are on the same hypervisor? -  There are performance costs as well

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OPENSTACK COMPUTE •  From day zero OpenStack supported running virtual machines •  We call them instances

•  Virtual machines aren’t a great choice for most big data applications though -  For example, its nice if you replicate your data -  But what if all the VMs containing replicas are on the same hypervisor? -  There are performance costs as well

•  Big data is about bulk, not artisanal machine orchestration

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OPENSTACK BAREMETAL •  A research project started in 2012

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OPENSTACK BAREMETAL •  A research project started in 2012 •  It was… horrible •  But has been deployed. Yahoo has tens of thousands of machines running

this code.

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OPENSTACK BAREMETAL •  A research project started in 2012 •  It was… horrible •  But has been deployed. Yahoo has tens of thousands of machines running

this code.

•  Luckily some adults came along and turned that research project into a productionized thing in 2013

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OPENSTACK BAREMETAL •  The new implementation is a separate OpenStack project •  Manages machines by talking IPMI / DRAC / iLO / other things •  Integrates with OpenStack Compute so that the same APIs work

everywhere

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WHICH MEANS…

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API CONTROL OF BULK INFRASTRUCTURE •  We can now build images for all our various big data machine types

-  Management nodes -  Zookeeper nodes -  Data storage / worker nodes

•  And then manage them with simple command line tools

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API CONTROL OF BULK INFRASTRUCTURE •  I’ve spent the last year helping a customer of ours do something like this

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API CONTROL OF BULK INFRASTRUCTURE •  I’ve spent the last year helping a customer of ours do something like this

•  Why a year? •  Well, they wanted some other stuff like continuous deployment of

OpenStack as well, and that was a lot harder than the Hadoop bits

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API CONTROL OF BULK INFRASTRUCTURE •  That said, based on a simpler version of their deployment, I think I have

some recommendations now for how to approach a project like this…

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API CONTROL OF BULK INFRASTRUCTURE •  That said, based on a simpler version of their deployment, I think I have

some recommendations now for how to approach a project like this…

•  Zookeeper nodes are harder than I thought •  Management nodes are even harder •  But data and processing nodes are easy

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API CONTROL OF BULK INFRASTRUCTURE •  That said, based on a simpler version of their deployment, I think I have

some recommendations now for how to approach a project like this…

•  Zookeeper nodes are harder than I thought •  Management nodes are even harder •  But data and processing nodes are easy

Luckily, this is the vast majority of your machines

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API CONTROL OF BULK INFRASTRUCTURE •  That said, based on a simpler version of their deployment, I think I have

some recommendations now for how to approach a project like this…

•  Zookeeper nodes are harder than I thought •  Management nodes are even harder •  But data and processing nodes are easy

Luckily, this is the vast majority of your machines

And this is possible, just harder

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API CONTROL OF BULK INFRASTRUCTURE •  Data and processing nodes

-  Golden image deployments are the way to go -  Keep your data on non-boot disks -  To update the OS / image, just rebuild the image and the use nova rebuild -  Use keep-ephemeral to avoid re-syncing data during a rollout

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API CONTROL OF BULK INFRASTRUCTURE •  Zookeeper nodes

-  This is harder because all the machines in the zookeeper cluster need a shared config listing all their peers

-  We solved this by using an overlay network -  But floating IPs would probably work in a simpler environment

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CANBERRA OPENSTACK MEETUP

Tuesday 29 November 7pm to 9pm

https://goo.gl/nxW62K

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Copyright © 2016 Rackspace | Rackspace® Fanatical Support® and other Rackspace marks are either registered service marks or service marks of Rackspce US, Inc. in the United States and other countries. Features, benefits and pricing presented depend on system configuration and are subject to change without notice. Rackspace disclaims any representation, warranty or other legal commitment regarding its services except for those expressly

stated in a Rackspace services agreement. All other trademarks, service marks, images, products and brands remain the sole property of their respective holders and do not imply endorsement or sponsorship.

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US

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Copyright © 2016 Rackspace | Rackspace® Fanatical Support® and other Rackspace marks are either registered service marks or service marks of Rackspce US, Inc. in the United States and other countries. Features, benefits and pricing presented depend on system configuration and are subject to change without notice. Rackspace disclaims any representation, warranty or other legal commitment regarding its services except for those expressly

stated in a Rackspace services agreement. All other trademarks, service marks, images, products and brands remain the sole property of their respective holders and do not imply endorsement or sponsorship.

ONE FANATICAL PLACE | SAN ANTONIO, TX 78218

US SALES: 1-800-961-2888 | US SUPPORT: 1-800-961-4454 | WWW.RACKSPACE.COM

US

Feel free to contact me at: michael.still@rackspace.com or @mikal on twitter

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