lightning talk: turbo charge your mongodb app

© 2014 Pure Storage, Inc. | 1 Pure Storage CONFIDENTIAL – Do Not Distribute

Introducing Pure StorageTurbo Charge your MongoDB App

Markus GrauNovember, 2014


Consistent performance100% MLC Flash

Less cost than diskInline deduplication & compression

Mission-critical reliability99.999%, non-disruptive operations

Pure Storage is Flash for the Enterprise

Scalable & compatible10 100s of TBs, Purity software


IBM24.6%

Pure Storage17.1%

Violin13.2%

EMC11.1%

NetApp10.6%

Cisco3.2%

SolidFire3.1%

HP1.3%

Others15.8%

– Pure Storage #2 Solid State Array Market ShareFastest Growing All-Flash Leader

Data Source: Gartner Research, June 10, 2014 Chart: Pure Storage

182%SSA Market

Growth

Gartner Market Share Analysis: Solid State Arrays Worldwide 2013

Others24%

IBM18%

Pure Storage7%

Violin30%

NetApp13%

Cisco8%

2012$236M

2013$667M

#2Market Share

>600%YoY Growth

20132013


Pure Storage FlashArray 400 Series

FA-405 FA-450FA-420

Up to 40TBs2 controllers in

2U

Up to 250TBs16 Gb/s FC

Up to 125 TBs

Pricing includes deduplication, snapshots, replication, etc.

Usable Capacity includes overheads for RAID-3D, Flash Management, GB-to-GiB conversion, and assumes 6-to-1 data reduction.


Typical Scaling Concerns for MongoDB Admins

•Performance• Disk performance has not changed (GB/IOP is getting worse)• SSD is expensive at scale

•Complexity• Scaling increases complexity (sharding, caching, tiering, etc)• Requires significant management / training• Mistakes = Downtime or Performance Impact

•Inefficiency• Underutilized capacity • Data center power, cooling, rack space is expensive


Performance: Results running MongoDB


Case Study: Cengage Learning •Profile

• Educational Services Provider offering wide variety of online services worldwide

• Run analytics, data warehouse, and royalty apps based on MongoDB

•Performance• “(after replacing disk with Pure) “In almost all cases, a .5 ms response time

was a 500-700% improvement in data store response time”

•Simplicity• "The Pure array has done everything as advertised”

•Efficiency• "Pure has brought to light major configuration issues we had in our own

environment -- some with multi-pathing, some of our UCS configuration”

- Jason Spruance, Operations Manager


Reducing Complexity: Configuring Pure for MongoDB

Provision a LUN of appropriate size for your DB• No need to create RAID groups• No need to set cache policies

Pure is block storage, so access from compute nodes:• Via Ethernet for iSCSI• Via dedicated Fiber Channel Network

Create zero space DB clones in seconds


ND Non-Disruptive Everything*For a true enterprise consolidation array hosting 100s of

applications, downtime is simply NOT an option.

Non-DisruptiveCapacity Expansion

Non-DisruptivePerformance

Expansion

Non-DisruptiveHardware

Replacement

Non-DisruptiveSoftware Updates

…All WithZero Performance

Loss


Case Study: Online Photo Company•Profile

• Rapid growth taxing traditional disk storage

•Performance• Move to Pure resulted in “Half the average response time”• 4x faster for replication to catch up after maintenance

•Simplicity• Array Installed in an hour• No configuration of devices • Mongo Team Manages Their Own Storage

•Efficiency:• Averaging 12 to 1 Data Reduction• 16TB Production Mongo Instance stored in 1.35TB of Pure Storage


Efficiency: Pure Storage Data Reduction

• Comprehensive, high-performance data reduction

• Pattern Removal • Adaptive, Inline Deduplication • Adaptive, Inline Compression • Deep Reduction • Zero-cost snapshots, clones & XCopy

• 5 – 10x reduction across broad number of data sets

• Reduces usable €/GB

* Based on CloudAssist data of Pure FlashArray deployments as of April 2014


Typical Customer Data Reduction Results


The Flash Price Barrier Has Been Broken!

$/GBHA

USABLEW/ SW

2012 2013 2014 2015 2016 2017…

$6$5 $4 10/15K

HDD

$2 $1.5 $1 SATAHDD

>$20

$15

$10

$6

$3

FlashAppliances

$8

$5

$4

$2$1

5-10xData Reduction!

Consumer SSD + Data Reduction

= Cost Parity to Disk


Typical Pain Points: Addressed

•Performance• All-flash combines benefits of SAN with SSD performance

•Simplicity• Pure’s all-flash implementation is radically simpler than disk or all-flash alternatives

•Efficiency• Data Reduction maximizes utilization


Case Study: Healthcare SaaS Provider•Profile

• Runs their business on applications leveraging Mongo DB

• < 1 ms latency critical for end user experience.

•Performance• Performance so good that customer will use Pure as a sales tool to attract

customers and differentiate from competition

•Simplicity• Pure allows their Network Engineer to be their storage expert & continue growth

without additional FTE headcount

•Efficiency• 5:1 data reduction for MongoDB enables scale without sprawl• Will consolidate a HP & DELL array into Pure for production


MongoDB Scaling Recommendations

Compute Nodes

DB Size

1

2

4

8

1TB 2TB 4TB 8TB 16TB

Use Commodity Servers with PCIe Flash:

• Low node count • Low application

count• Small databases

Migrate to All-flash SAN when:

• Multiple nodes increase complexity

• Database size taxes disk I/O

Upgrade:• Servers based on

performance requirements and CPU cycles

• Storage based on capacity requirements


Reference Architecture

•Scalable Capacity

•Resiliency

•Consistent Performance

•Data Reduction

•Ease of Management

•Snapshots and Database Cloning

http://info.purestorage.com/WP-PureStorageandMongoDB_Request.html





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