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The Rise of Dynamic Computing

David AronoffGeneral Partner

Flybridge Capital Partners

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DESPITE ARCHITECTURAL CHANGES OVER TIME, APPLICATION DEVELOPERS HISTORICALLY HAD

FEW CHOICES TO MAKE

1960s

• Monolithic platforms force “one-size fits all” approach

• Architectures tend to be bloated, brittle and energy intensive

• In the immediate period after the emergence of internet application platforms, innovation and opportunities for new entrants were constrained

Early 2000s

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RECENT MARKET FORCES HAVE BLOWN THIS MONOLITHIC, ONE-SIZE-FITS-ALL APPLICATION

PLATFORM APART

Cloud Computing

Dynamic Scripting

Languages

Open Source

Virtualization

Exposed Data Flows

& APIs

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Themes Implications

1. Developer-Driven Business Models

➟ Low cost, widespread adoption, wedge for growing additional sales

2. Legacy Applications Don’t Translate Well

➟ Customers seek out alternatives as traditional solutions no longer work given distributed topologies & ownership

3. “Big Data” Analytics of Exposed Data Flow & APIs

➟ For 1st time can analyze global, real-time behavior of users, applications & interactions

4. New Opportunities Emerge ➟ Disaggregation creates distinct problems and new applications that were unforeseen

5. Purpose-Built Foundation Technologies

➟ Innovator’s Dilemma for incumbents creating opportunities for big swings in core technology

INVESTMENT IMPLICATIONS

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Themes Example Companies

1. Developer-Driven Business Models

2. Legacy Applications Don’t Translate Well

3. “Big Data” Analytics of Exposed Data Flow & APIs

4. New Opportunities Emerge

5. Purpose-Built Foundation Technologies

EXAMPLES