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01 NUTANIX INC. – CONFIDENTIAL AND PROPRIETARY Big Data: Lessons for VDI Dheeraj Pandey, Co-founder & CEO Lionel Marks, Dir of Prod Marketing

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The Arab Spring of Enterprise IT.

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Page 1: Nutanix BriForum 05242012

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NUTANIX INC. – CONFIDENTIAL AND PROPRIETARY

Big Data: Lessons for VDI

Dheeraj Pandey, Co-founder & CEOLionel Marks, Dir of Prod Marketing

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NUTANIX INC. – CONFIDENTIAL AND PROPRIETARY

The Big Data MomentumThe “Arab Spring” of Enterprise Computing

It’s massiveIt’s about people, and people-to-peopleIt’s swiftIt’s about breaking away

#briforum #breakingaway The Big Data Momentum: The “Arab Spring” of Enterprise Computing http://ow.ly/b7fD0 @trailsfootmarks @nutanix

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NUTANIX INC. – CONFIDENTIAL AND PROPRIETARY

The Big Data MomentumThe “Arab Spring” of Enterprise Computing

It’s massiveMobile, RFID, surveillance cameras, genomics, click stream, PoS cash registers, search engines, browser cookies, logs, …

It’s about people, and people-to-people

It’s swift

It’s about breaking away

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NUTANIX INC. – CONFIDENTIAL AND PROPRIETARY

The Big Data MomentumThe “Arab Spring” of Enterprise Computing

It’s massive

It’s about people, and people-to-peopleSentiments, risks, terror watch, intent, social interactions, buying behavior, likes-dislikes, tastes, sharing, trending

It’s swift

It’s about breaking away

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NUTANIX INC. – CONFIDENTIAL AND PROPRIETARY

The Big Data MomentumThe “Arab Spring” of Enterprise Computing

It’s massive

It’s about people, and people-to-people

It’s swift2+ years in the makingAgility in decision-makingTime-to-value, speed-to-market

It’s about breaking away

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The Big Data MomentumThe “Arab Spring” of Enterprise Computing

It’s massive

It’s about people, and people-to-people

It’s swift

It’s about breaking awayAutonomy, independence in decision-makingFlattening of infrastructure

#briforum #breakingaway http://ow.ly/b7fVB @trailsfootmarks @nutanix

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Breaking AwayFlattening of Infrastructure: No SANs

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Breaking AwayThe mutiny that revolutionized analytics

“The practitioners of big data are hostile to shared storage.

They prefer server-attached storage… The perception of

SAN and NAS is that they are slow, complex, and above all,

expensive. These qualities are not consistent with big data

analytic systems that thrive on system performance,

commodity infrastructure, and low cost.”

- Wikipedia (“Big Data”)

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Breaking AwayFlattening of Infrastructure: NoSQL, No Database, No DBAs

DW MapReduce, SQL REST/HTTP

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Breaking AwayPower to the People Who Matter

Massive democratization of infrastructureAutonomy, independence, access

DevOps takes chargeApplication owners become paramount

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Breaking AwayFlattening of Infrastructure: A Brief History of the Post-SAN Era

Infrastructure is totally flattened… and simplifiedSAN goes awayTransactional database and SQL go awayMonolithic systems are bannedGrow-as-you-go clusters are in vogueNetwork topologies are flattened

#briforum #breakingaway Flattening of Infrastructure: A Brief History of the Post-SAN Era http://ow.ly/b7fxu @trailsfootmarks @nutanix

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KEY CONCEPTSMassive-Parallelism, MapReduce, NoSQL

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Massively Parallel ArchitectureEmbarrassingly Parallel Computing

“Just-throw-a-server” approach:Commodity off-the-shelf hardwareWorks beautifully if the data access is localEverything grows: compute, (virtual) network, storage capacity, IOPS, MB/s

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Massively Parallel ArchitectureNutanix’s “Embarrassingly Parallel” Filesystem

Build to scale from “merchant-grade” to “enterprise-grade”:The largest and fastest filesystem ever built for virtualized environmentsIndustry’s first unified and converged virtualization stack

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NoSQLEmbarrassingly Parallel Key-Value Stores

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NoSQLNutanix’s use of NoSQL

To store metadata that massively scalesMetadata: to answer “where is user’s data located” questionPresent on every cluster nodeRebalances when nodes are added or removedLock-less: No database-like transactions for updatesDistributed consensus on updates

We’ve forked off Cassandra to build our own NoSQL store

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MapReduceDivide-Conquer-Sort-Shuffle-Collect

“Just-throw-a-server” approach:Embarrassingly Parallel problem solving

Click stream analysis example:Sum of all clicks, grouped-by IP addressesTop 10 IP addresses with most clicks: Pipelining

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MapReduceNutanix’s use of MapReduce

We do *not* use Hadoop, an open source MapReduce frameworkWe built our own framework

So what is it used for?Our metadata is partitioned on all the nodesWe constantly need to do a lot of “heavy-lifting”:

run metadata heuristics on access patternsrebalance storage after node add/removewaterfall data between flash and spindle tiersheal the clusters during hardware failuresgarbage-collect deleted vDiskssever parent-child links for snapshot’ed vDisks

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VDI’s TakeawayFreedom is refreshing

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VDI 2008-’11The one that couldn’t break away

Legacy infrastructureUgly retrofitting: square-peg-in-a-round-hole

Too much consensus-buildingToo many people in the room, too many to appease

Lack of rapid prototypingPilot was not the same as productionApplication owners had little to no power

Note: VDI is an “embarrassingly-parallel” problem, if storage is kept local

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SAN-less VDIBringing the disk back to the PC

Caching is localFlash is localNFS is simpleDedup is massiveUser-data (D:\) is safePilot _is_ productionXenApp is complementary

Shares the same infrastructure

Freedom is refreshing… isn’t that what BYOD is all about?!

#briforum #breakingaway @trailsfootmarks on Big Data + Virtualization; Big Virtualization's Biggest Nemesis: storage http://ow.ly/b7eSD

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Break Away… Bring Your Own Infrastructure (BYOI)™