The shift to public cloud computing is significantly transforming enterprise technology, with indications that workloads are moving from on-premises to the public cloud, driven by reduced storage costs and a desire for developers to focus on value creation. Major trends influencing this shift include the evolution of infrastructure (like the rise of virtualization and containers), a change in application design towards microservices, and the growing trust in public cloud solutions. AWS is a dominant player in this space, demonstrating rapid revenue growth and shaping market dynamics.

1. The Next Wave of Computing
How the shift to public cloud is changing enterprise tech
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .

2. Leaders Fund is a B2B
focused VC fund
Investing in Series A/B B2B
software companies
Based in Toronto & Atlanta
Gideon Hayden
Co-Founder & Partner
@ g i d e o n h a y d e n
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .

3. The biggest shift happening in enterprise tech right now . . .
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
Blockchain
(4+ years out)
A.I.
(1-3 years out)
Platform shift to
public cloud (now)

4. 2018 2021
$160bn $277bn 22%
CAGR
2016 - 2021
Global public
cloud spend
Source: IDCC O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
Workloads are shifting from on-prem to the public cloud

5. Cost of storage is dropping
Source: Credit SuisseC O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
12K
10K
8K
6K
4K
2K
2005 2007 2009 2011 2013 2015 2017(E)
The economics of the cloud have fundamentally changed
Global Storage Pricing (Revenue/TB Shipped)
And so is compute. . .
1.E+00
1.E-01
1.E-02
1.E-03
1.E-04
1.E-05
1.E-06
1.E-07
1.E-08
1.E-09
1968 1978 1988 1998 2008
Global Transistor Pricing (Revenue/# of Transistors)

6. C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
Developers and engineers want to focus on value creation
Infrastructure-as-a-Service (IaaS) providers allow engineers to offload
‘non core’ infrastructure work while freeing them up to focus on writing the
applications that directly drive business value.

7. IaaS vendors are winning market share
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2015 2016 2017 2018 2019 2020 2021
%ofMarketSpend
Public Cloud Private Cloud Data Center
IT Infrastructure Market Forecast
Source: IDC (Q4 2016)C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .

8. And they are consuming all layers of the value chain
Past Present
Company
consumes
capacity
using one
vertically
integrated
vendor
Company
builds
capacity
(data center)
using
multiple
vendors
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .

9. AWS is dominating the public cloud market
Source: Gartner (2016)
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
Amazon Microsoft Alibaba Google Rackspace Other Vendors
PublicCloudMarketShare
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
Public Cloud Market Share

10. C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .

11. 0
$2B
$4B
$6B
$8B
$10B
$12B
$14B
$16B
$18B
F2006 F2007 F2008 F2009 F2010 F2011 F2012 F2013 F2014 F2015 F2016 F2017
AnnualRevenue
Giving context to the growth of AWS
AWS was founded as an upstart within Amazon in 2006
And within 12 years surpassed
$17.5BN in revenue
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C . Source: Gigaom, Macquarie, Amazon

12. How does AWS growth compare to top public SaaS companies?
(Starting point is $100M in revenue)
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C . Source: Pitchbook
$0
$2
$4
$6
$8
$10
$12
$14
$16
$18
$20
1 2 3 4 5 6 7 8 9 10 11 12 13 14
AWS
Salesforce
Workday
ServiceNow
Shopify
Atlassian Corporation
Veeva
LogMeIn
Tableau Software
The Ultimate Software Group
Guidewire Software
AnnualRevenue($B)
Years After Reaching $100M In Revenue

13. $0
$2
$4
$6
$8
$10
$12
$14
$16
$18
$20
1 2 3 4 5 6 7 8 9 10 11 12 13 14
AWS Azure
Microsoft is catching up quickly
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C . Source: Pitchbook
AnnualRevenue($B)
Years After Reaching $100M In Revenue

14. If AWS were a standalone SaaS company. . .
$17.5BN
AWS Revenue (F2017)
$19.9BN
Top 10 SaaS companies annual revenue
(collective market cap ~$146BN)
compared to
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C . Source: Pitchbook
*Based on most recent fiscal yr
$0
$2
$4
$6
$8
$10
$12
$14
$16
$18
AWS Salesforce Workday ServiceNow Shopify Atlassian
Corporation
Veeva LogMeIn Tableau
Software
The Ultimate
Software
Group
Guidewire
Software
AnnualRevenue($B)

15. -$1.0
-$0.5
$0.0
$0.5
$1.0
$1.5
$2.0
$2.5
$3.0
$3.5
$4.0
$4.5
AWS Salesforce Veeva The Ultimate
Software
Group
Guidewire
Software
LogMeIn Shopify Atlassian
Corporation
ServiceNow Tableau
Software
Workday
AnnualOperatingIncome($B)
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C . Source: Pitchbook
$4.2BN
AWS Operating Income (F2017)
$460M
Sum of positive operating income
(Top 10 SaaS companies)
>
*Based on most recent fiscal yr
If AWS were a standalone SaaS company. . .

16. AWS represents a small portion of Amazon’s revenue
AWS generated
10%
of Amazon’s Revenue
In F2017
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C . Source: Pitchbook

17. But it is fueling Amazon’s ability to reinvest in the core
AWS generated
~100%
of Amazon’s Operating Income
In F2017
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C . Source: Amazon, Pitchbook

18. So what is driving public cloud adoption?
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .

19. PRODUCT STICKINESS
1
3
4
Developers desire to focus on application logic not infrastructure
2 Increased demand for vertically integrated IaaS vendors
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
Investment in the evolution of computing infrastructure
LEADS TO
RESULTING IN
WHICH DRIVES
Cost reduction, and increased adoption + investment

20. How did we get here?
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .

21. 3 major interrelated trends are driving the shift to public cloud
1. EVOLUTION OF
INFRASTRUCTURE
(DIVISION OF UNIT OF
COMPUTE + ABSTRACTION
OF OPS)
3. EVOLUTION IN MINDSET
(ENTERPRISES TRUSTING PUBLIC CLOUD)
2. EVOLUTION
IN APP DESIGN
(MONOLITHS TO
MICROSERVICES to
FUNCTIONS)
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .

22. 1. The Evolution of Infrastructure
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BARE METAL VIRTUALIZATION CONTAINERS SERVERLESS

23. Mid 90’s: dot com drives need for fast, non-stop connectivity
BARE METAL VM’S CONTAINERS SERVERLESS
Massive investment in dot com
companies and the proliferation of
Linux OS gave well funded enterprises
the resources to
build their own data centers.
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .

24. B UIL D ING A
D ATA
C ENTER
3. APPLICATION DEPLOYMENT
Application deployed
to each server2. SERVER CONFIGURATION
Configured with web
servers, DB’s, caches
4. MONITORING
Monitoring DC, patches,
analytics
1. SERVER INSTALLATION
Server installed and
connected to the network
5. SCALING
Repeat this process as you
need more capacity.
What does it take to build and run a data center?
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
BARE METAL VM’S CONTAINERS SERVERLESS

25. Massive upfront CAPEX
investment
More time spent on
administering data
center than on creating
business value
Employ an entire IT staff
to run/monitor data center
Only accessible to large
or well funded
organizations
You have 100% control, but. . .
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
BARE METAL VM’S CONTAINERS SERVERLESS

26. And if it goes down, it’s on you . . .
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
BARE METAL VM’S CONTAINERS SERVERLESS

27. Physical servers can now be split into
multiple, smaller virtual machines.
Physical server inventory could be
far better utilized as multiple applications
can be run on a single server
2000—2005: VM’s change the economics of running servers
Server
Host OS
Hypervisor
Guest
OS
Guest
OS
Guest
OS
Bins/
Labs
Bins/
Labs
Bins/
Labs
App
#1
App
#2
App
#3
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
BARE METAL VM’S CONTAINERS SERVERLESS

28. VM’s offer companies the ability to scale
SCALE
OS configured once, can be re-used to quickly
create identical servers
RELIABILITY
Can be re-created on a different physical server
and automatically switch IP address over
FLEXIBILITY
Division of computing power allows smaller and
cheaper instances to optimize cost and
performance
COST CONTROL
Easily created/destroyed, billed by hour or
month
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C . Source: Mayank Lahiri
BARE METAL VM’S CONTAINERS SERVERLESS

29. But VM’s have their drawbacks
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
UNUTILIZED CAPACITY
Running a VM consumes an entire operating
system with all the associated CPU and
memory overhead
USAGE ESTIMATION REQ.
Need to predict the instance size required and
either stop the VM to upgrade (which takes
time), or over-pay for excess capacity
BARE METAL VM’S CONTAINERS SERVERLESS

30. Enter containers: faster to start and more (cost) efficient
Multiple containers
can run on a
single host OS
compared to VMs which
require multiple OS
abstractions
Server
Host OS
Hypervisor
Guest
OS
Guest
OS
Guest
OS
Bins/
Labs
Bins/
Labs
Bins/
Labs
App
#1
App
#2
App
#3
Server
Host OS
Bins/
Labs
Bins/
Labs
Bins/
Labs
App
#1
App
#2
App
#3
Virtual Machine (VM) Container
X X X
X
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
BARE METAL VM’S CONTAINERS SERVERLESS

31. Why does this matter?
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Containers require far less memory and CPU overhead
as they do not have an entire OS worth of processes
running alongside developer’s programs.
Breaking applications down into smaller microservices
allows for more agility, speed to deployment, and scalability.
ENABLE MICROSERVICES
BASED ARCHITECTURES
MORE COMPUTE WORKLOAD
ON SAME SERVER
REACT QUICKLY TO
CHANGES IN ACTIVITY
SEPARATE OPS TEAM
FROM DEV TEAM
Provisioning containers takes a few seconds, so we can
be more reactive and flexible about scale up or scale
down capacity.
Ops team focuses on building a pipeline for deploying
containers and doesn’t concern themselves with what code
each container contains. Portability is important.
BARE METAL VM’S CONTAINERS SERVERLESS

32. But nothing is perfect; you still have to. . .
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
ESTIMATE PERFORMANCE
CAPACITY REQUIRED
MANAGE DEPLOYMENT AND
CLUSTER OF CONTAINERS
PAY FOR IDLE CAPACITY ON A
MONTHLY OR ANNUAL BASIS
BARE METAL VM’S CONTAINERS SERVERLESS

33. 2014: Lambda launch kicks off Serverless movement (FaaS)
What is it? AWS Lambda is a compute service that lets
you run code without provisioning or managing
servers.
Technology: AWS Lambda executes your code only
when needed and scales automatically, from a few
requests per day to thousands per second.
Pricing: Pay only for the compute time consumed; no
charge when code is not running.
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
BARE METAL VM’S CONTAINERS SERVERLESS

34. Serverless ≠ no servers
The term “serverless” does not mean that no servers are needed, but
rather means that the effort required to manage servers and infrastructure
is abstracted away from the developer and is owned by the service
provider (AWS, Azure, Google).
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
BARE METAL VM’S CONTAINERS SERVERLESS

35. Defining characteristics of serverless
EVENT DRIVEN
Short lived container environments triggered by
events that live for seconds/milliseconds.
PAY FOR USE
Containers fire up and down based on trigger events.
As a result, you don’t pay for idle time, only pay for
time the container is running.
EASY DEPLOYMENT
No need to provision or plan for capacity. Serverless
platforms scale up and down automatically based on
capacity needs.
SIMPLE CODE
Functions can be short purpose driven pieces of code.
Dev’s focus on application logic, not infrastructure
and deployment.
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
BARE METAL VM’S CONTAINERS SERVERLESS

36. Where are we w/ serverless adoption?
Source – SumologicC O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
2016 2017
BARE METAL VM’S CONTAINERS SERVERLESS

37. Small Unit of Compute
Infrastructure Focus Task Focus
Bare Metal
VM’s
Containers
Serverless
Large Unit of Compute
Developers Focus
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
Summary: unit of compute , ops being abstracted away
BARE METAL VM’S CONTAINERS SERVERLESS
Unit of Compute

38. 2. The Evolution of Application Design
From Monoliths to Functions
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .

39. Monolithic = all required logic within one application
Source: CitrusByte
HTML JavaScript MVC
Service Service
Service Service
Data Access
Relational
DB
Key/Value
Store
Monolithic Application
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .

40. Challenges w/ monolithic design
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
Due to continuous feature development, different
client applications, different types of users and
sync/asynchronous workflows
LESS AGILITY AND SPEED
CODE BASE BECOMES COMPLEX
AND UNWIELDLY TO MANAGE
SENSITIVE TO CHANGE
SLOW LEARNING CURVE
One change to the codebase can impact the entire
application and potentially take it down
Changes may require rebuilding/redeploying the
whole application and need to be thoroughly vetted
Many developers can’t touch the code without months
of learning about it, and when developers leave the
organization so too does the knowledge of the code.

41. Containers enable microservices architectures
The division of an application into smaller services
A method of developing
software applications as a
suite of independently
deployable, small, modular
services in which each
service runs a unique
process and communicates
through API’s to serve a
business goal
E-commerce Architecture
API
GATEWAY
REST
API
Storefront
WebApp
WEB
REST
API
REST
API
REST
API
Account
Service
Inventory
Service
Shipping
Service
Account
DB
Inventory
DB
Shipping
DB
Source: Microservices.ioC O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .

42. Microservices Operational Overhead
Each microservice you build requires:
Although easier to deploy,
microservices architectures
still require the mgmt. of a
lot of operational overhead
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
A deployment
mechanism for
that OS
Application deployment
and configuration
overhead
Monitoring of the OS
for availability
Source: Stratoscale
An underlying OS

43. Functions – Smaller unit of compute, less overhead
APPLICATION
SERVES REQUEST
API LAUNCHES
OS
EVENT
TRIGGER
FIRED
CONTAINER IS
KILLED
The process of executing a function is shortlived (ms) and as a result, the
developer’s responsibilities lay more in the application code than managing the
other elements of the application.
The cloud provider manages the underlying infrastructure,
therefore significantly decreasing the operational overhead.
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .

44. VMs Containers Serverless
Deploy in minutes
Live for weeks
Deploy in seconds
Live for mins/hrs
Deploy in milliseconds
Live for seconds
Infrastructure:
App Design:
Server
Billing Method: month/hour hour/minute Second/millisecond
Trends in infrastructure have driven changes in app design
Function
Function
Function
Microservice
Microservice
Microservice
Microservice
Microservice
Monolith
Function
Function
Function
Function
Function
Function
Function
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
Source: iron.io

45. VMs Containers ServerlessDeployment:
App Design:
And the pace of change is rapidly increasing
Function
Function
Function
Microservice
Microservice
Microservice
Microservice
Microservice
Monolith
Function
Function
Function
Function
Function
Function
Function
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
Source: iron.io
4 years 2 years?
7 years 2 years?

46. 3. The Evolution of Enterprise Mindset
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47. Enterprises are recognising the promise of the cloud
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
Most disruptive technology in 2017 Credit Suisse Outlook Survey
% of respondents (enterprise executives)
Source: Credit Suisse

48. Mindset among enterprises has shifted from build to consume.
Capex  Opex
Enterprises have realized that their
$’s are better spent focusing on
creating value for their
customers
as opposed to building & managing
the infrastructure of their
applications to create that value.
Build Consume
% of companies planning to have the following environments as their
primary environment in 2015 and 2018
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C . Source: McKinsey & Co.

49. The shift to cloud service providers is accelerating
2015 2018 2015 2018
65 80
20
35
60 81
40
19
Shipped server instances, by destination,
millions of instances shipped, %
Shipped storage capacity, by destination,
exabytes shipped, %
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
Cloud service provider
Enterprise on-prem
Source: McKinsey & Co.

50. Enterprises are more trusting of cloud security
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
% of enterprises concerned about security
Rightscale survey of 525 enterprises (1K+ employees)
2016 2017 2018
Source: Rightscale State of the
Cloud 2018

51. The challenge now is how to move more workloads to the
cloud while managing cost/governance
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
Cloud Initiatives 2018 v. 2017
Rightscale survey of 997 companies
Source: Rightscale State of the
Cloud 2018

52. But we’re still in the
early innings of this
transformation
Public cloud adoption rates
were only around
23% in 2016
with the main blockers being the skills gap to
manage the cloud and security concerns
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C . Source: IDC (Q4 2016)

53. So. . . what does the future hold?
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .

54. PRODUCT STICKINESS
Billion dollar companies will be created in these areas
Machine Learning as a Service
1
3
4
Continued adoption of Kubernetes and container based architectures
Cloud ops optimization & automation
2 The gradual shift to serverless based architectures
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
5 Chaos Engineering

55. Cloud Native/Containers – A mindset
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
WHAT MAKES
A C L OUD
NATIVE APP
2. DYNAMICALLY ORCHESTRATED
Applications are launched through
containers which are proactively
managed to optimize resource utilization
1. CONTAINERIZED
Each part of the application is
packaged in its own container
3. MICROSERVICES ORIENTED
Apps are segmented into
multiple microservices

56. Cloud Native Market Map
See full Cloud Native landscape here
from CNCF, Amplify and Redpoint
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .

57. Kubernetes is winning the orchestration layer
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
But even Kubernetes
has its challenges, and
startups are popping up
that sit on top of it to
manage the scaling of
Kubernetes clusters.

58. C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
Container unit
of deployment
Serverless
paradigm
Run containers
w/o managing
servers or clusters
Containers as ‘Functions’
Allows companies to make the shift to the ‘serverless paradigm’ without
having to rewrite their container based apps
*
*Leaders Fund
portfolio company

59. C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
Serverless – Vendor lock-in or multi-cloud opportunity?
THREAT OPPORTUNITY
Functions = vendor
lock-in
as reliance on Function platforms
causes them to lose control over
where their stack is run
3rd party prevents
vendor lock-in
by creating a layer that distributes
workloads/runs functions across
multiple cloud providers

60. NEED FOR TOOLING THAT
FOCUSES ON:
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
Serverless - Ecosystem requirement
D E P L O Y M E N T
C O N F I G U R A T I O N
M O N I T O R I N G / L O G G I N G
D E B U G G I N G
S E C U R I T Y

61. As IaaS vendor SKU counts continue
to explode, the cloud will only
become more complex.
A neutral 3rd party is required to
optimize cloud decisions at the
compute, storage, networking and
DB level.
Cloud optimization
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
*
*Leaders Fund
portfolio company

62. Reactive Value to Customer Proactive
Cost visualization and
instance reallocation
recommendations
Automatic provisioning and
optimization of workloads
across compute type/cloud
$ $$$
e.g.
e.g.
Customers want solutions that give visibility into
cloud operations and automatically take action
to save more and perform better. Optimization
tools should create less work for engineering,
not more.
*
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
*Leaders Fund
portfolio company
Cloud optimization

63. Cloud-ops automation
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
How Companies are Optimizing Cloud Cost
Rightscale survey of 997 companies
All of the manual policy decisions below should be automated
Source: Rightscale State of the
Cloud 2018

64. Source: Lenny Pruss @ Amplify
New infrastructure that is purpose built for computationally and
data intense ML/AI workflow will be required
All the major cloud providers are building out infrastructure for ML/AI.
Key Question: Will the value accrue to IaaS vendors or will we see new entrants at every level of
the stack?
The Machine Learning Stack
MODEL TRAINING
DATA
ACQUISITION &
PREPARATION
MODEL EVALUATION
AND TUNING
DEPLOYMENT MONITORING
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .

65. C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C .
Chaos Engineering
Software systems are complex
Leading to bugs, crashes, errors, and data leaks
Simulates extreme, turbulent, or novel conditions and
observes how the system responds and performs,
significantly reducing the risk of system failure
Source: Tech Crunch
‘Resiliency as a Service’
helps companies proactively
find vulnerabilities in their
software system
Opportunity

66. In summary,
The growth of
AWS signifies a
larger platform
shift that is
underway.
More and more of the
stack is being
abstracted, allowing
developers to focus
on capabilities that
are valuable to the
customer.
C O P Y R I G H T © 2 0 1 8 L E A D E R S F U N D , I N C . Source: Credit Suisse