1© Violin Memory, Inc. 2014 CONFIDENTIAL CONFIDENTIAL © Violin Memory, Inc. 2014

Databases in the Virtualized World

By Matt HendersonDirector, Microsoft Solutions

2© Violin Memory, Inc. 2014 CONFIDENTIAL

Application Sprawl

Application Sprawl• CRM• Billing• ERP• Sales• Engineering• Monitoring• Manufacturing

Real World• 3rd Party apps• Old versions

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Server Sprawl

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Databases: 31 flavors

• Databases• MySQL• Oracle• MSFT SQL• Hadoop

• Workloads• BI / DW• OLTP

• Resources• RAM• CPU• Storage

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Dynamic & Shifting Workloads

Unique and changing• Per Server• Per Application• Per Day/Hour• Week day versus

weekend• Adhoc reporting• Administration

Designed for Peak• Not optimal

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Databases

Persistent data storage

Data access engine

Application logic processor

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Many Databases – Many Data Sets

• Not all data can fit in memory

• Tiering works only if patterns well defined

• Caching is for reads• Access patterns change• Dedicating resources is

inefficient & wasteful

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RAM versus Storage

Architectural ConceptsRAM based:

• Invest in memory tier. Dedicate resources to applications. Over allocate to ensure consistent performance. “Distributed” model as performance is reliant on local resources.

Storage based• Invest in high performance storage. Reduce memory to

minimal amounts. Data needed will almost always come from storage. “Central” model as performance is reliant on shared storage.

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RAM versus Storage

Memory Challenges• Hard cap in OS (~2TB)• Size limitations per server• More expensive $ per GB• Disruptive to upgrade• Not shareable (dedicated)

Database Buffer / Virtualization• Buffers don’t deallocate• Buffers don’t dedup• Inefficient to virtualize

Storage Challenges• Disk massively slower

than memory • Complex to setup• Needs frequent tuning• Over provisioning is key

New Technology Needed• Bridge gap in speed• Easier to manage

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Visualizing I/O Wait

• Applications wait for I/O to return = I/O Wait

• Time slices missed while waiting are lost

• Faster CPUs and more cores only increase lost time slices between I/O returns

• Solve actual bottleneck, don’t shoot from the hip

→ Your applications now spend more time doingand less time waiting

CPU Cycle with Disk

I/O Wait I/O Wait

20%Work

80%Wait

CPU Cycle with Violin

5%Wait

95%Work

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Optimizing Architecture – Performance & Cost

• CPU’s are faster than hard drives

• Adding cores does not correct issue

• 8 cores @ 10% = 1 core @ 80%

• 40% utilization = 60% over paying

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Visualizing latency - I/O Wait Infrastructure

I/O W

ait

HDD StorageMany milli-second

latency

PowerEdge M1000e

9 101 2

11 123 4

13 145 6

15 167 8

0

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PowerEdge M1000e

9 101 2

11 123 4

13 145 6

15 167 8

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I/O W

ait

SSD StorageFew milli-second

latency

SSD

SSD

SSD….

Or

SSD

SSD

SSD….C

on

tro

llers

Cac

he

Flash StorageMicro-second latency

Fully optimal system

PowerEdge M1000e

9 101 2

11 123 4

13 145 6

15 167 8

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Legacy Architecture Model

• Large batches to SSDs• SSDs in disk chassis = bottlenecks• Stranded space and speed

64k

64k

64k

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Modern Architecture Model

• Small batches to custom cards• Data spread evenly

• 100% usable space• 100% performance on every I/O

4k 4k 4k 4k

4k 4k 4k 4k

4k 4k 4k 4k

4k 4k 4k 4k

64k 4k data+

1k parity

5kD

ata

Dat

aD

ata

Dat

aP

arit

y

1k

1k

1k

1k

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++

++

=5

k

VIM

MV

IMM

VIM

MV

IMM

VIM

M

flash flash flash flash flash flash flash flash

controller

1k

bitsbits

VIMM

Parallel and distributedfor lowest latency

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RAM versus Storage

Take Aways:

• Architectures should be optimal across all tiers• I/O latency is currency of performance• Centralized performance, through fast storage =

always works• Licensing is the highest expense, optimize for

CPU usage• Violin performance optimizes IT spend.