VMTurbo Overview July 2015 v7

Demand Driven Control For Virtualized & Cloud Environments

Boston, MA (HQ)

New York, NY

Reading, UK

2009• Founded• Raised Series A

2010/11• Product GA• 100 customers• Raised Series B

2012• 300 customers• 12 consecutive qtrs of record revenues

2013• 100th employee• Released Storage and Fabric Controllers• 14 consecutive qtrs of record revenue growth• Raised Series C

2014• 1200+ Customers• 19 consecutive qtrs of record revenues• 450 employees• Raised $50M Series D

2015• $2M RedHat investment• 19 consecutive qtrs of record revenues

Company Overview

1,000+ World-Class Customers

Demand Control Systems Will Always Disrupt

Fixed Cost Supply-Based Industries

Demand Chooses Supply

Industry Examples:

Airlines, Hotels, Classifieds, Job Boards, Taxi Cabs…

Let Demand Choose its Supply

Greater Consumer choice Automated booking Minimize mistakes

Less expensive to runOverall yield increases

Scaleable!

Impact Of Demand Control Systems

% V

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resourceliquiditypool

DEMAND

SUPPLY

Native Hypervisor Schedulers Do Not Manage Application Workload

DemandGAP

Modern Data Center Management Gap

Degraded Application Performance

Labor Costs

Underutilized Infrastructure

Business Impact

Software License Sprawl

VMTurbo’s Core Concept- Control The Outcome

Assuring Performance WHILE Maximizing Efficiency

Desired State

Increasing Complexity in the Virtual Datacenter

10

Characterizing Application Workload Demand

Every Application Workload has unique characteristics

Todays environments have 100’s or 1000’s of Application Workload

Understanding the characteristics of every single application workload that runs in the data center in “N” dimensions is a critical

foundation for managing Demand

Supply & Demand Matching EngineDemand

Supply

Request Quotes &

Select Best Provider

Request Quotes &

Select Best Provider

Request Quotes &

Select Best Provider

Request Quotes &

Select Best Provider

Request Quotes &

Select Best Provider

Request Quotes &

Select Best Provider

Pricing Resources

Pricing Resources

Pricing Resources

PricingResources

Pricing Resources

SupplyCongestion Based Pricing

Example from Customer EnvironmentReal Time Control

VMTurbo addresses the GAP in native hypervisor schedulers and Cloud Orchestration systems controlling the environment in real time

so that Application Workload Demand can be satisfied in the most economic way

VMTurbo automated control ensures Application Workloads get

the compute and storage resources they require to operate

reliably while increasing the useable infrastructure capacity

Beyond Real-Time Control

Jan

AprJul

Oct DEMANDNow

servicing existing workload demand

Reservationscommitted workloads not yet in service

Deploymentwhere to place new workload

Future Projected pipeline of new workloads

Reservation & Initial Placement

Planning For The Future

Extensibility Beyond the Hypervisor

Return on Investment

16

VMTurbo Evaluation

VMTurbo

Deploymen

t

Data Collection & Testin

g

ROI Analy

sis

Business

Impac

tPresentatio

n

2 to 3 weeks of elapsed time + 2 to 3 hours man effort from your organization

Business Impact Assessment