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Unravelling Todays Disruptive Tech
Landscape
Vice President, Research,
WSO2
Srinath Perera
● Landscape and market forces shape technology competition
○ With the added complexity that the landscape changes very fast
● Global Market Outlook (internal use)
○ Categorize middleware into segments and subsegments and estimate their
sizes and growth
● Global Technology Outlook (externally published)
○ A yearly critical review of emerging tech
● Goals
○ Internal understanding and planning
○ Sharing how we think about current and future markets
○ A means for dialog and feedback
CTO Office
Middleware Landscape (Market Outlook)
● We identified seven segments
○ Apps
○ Integration - ESB, APIs, Messaging, Workflows
○ Observability
○ Storage - RDBMS & NoSQL
○ Infrastructure - DevOps and Orchestration
○ Security
○ IoT
● We did an exercise to estimate their size and growth (CAGR)
ObservabilityApps Integration
AI & Analytics
Infrastructure
Security
Middleware Landscape
Application
Platforms
4.5(7%)
aPaas
ESB
Data
Integration
Analytics
AI
Storage
Data
Center
Automation
IoT
IMG
iPaas
API iSaaS
APM
Log
Analytics
DevOps
iDaaS
Access
Management
Security
Analytics
PIM
iDaaS
Legend
Growth>20%
10%<Growth <20%
Growth<10%
Increasing Growth
Decreasing Growth
Stream
Processing
CIAM
2B(25%)
1B(50%) 3.5(2%) 2.5(5%)
1B(50%) 1B(50%)
4B(25%) 3B(25%)
25(5%)
3B(5%) 40B(10%)
2.0(5%) 2B(34%)
0.5B
(30%)
3B(5%)
1B
(50%)
1B(30%) 1.5B(40%) 1.5B(20%)
Container
Orchestration
Interactions Between Segments
IoT
Integration
InfrastructureStorage
Security
AI&Analytics
Observability
Apps
Emerging Technologies (ET) Shapes the Landscape
IoT
Integration
InfrastructureStorage
Security
AI&Analytics
Observability
Apps
Sharing
Economy
3D Printing
Fintech
ServiceMesh
Serverless
Blockchain
Quantum
Computing
Chatbots
AR/VR
Understanding ETs: History
Understanding ETs: Gartner Hype Cycle
Understanding ETs: Carlota Perez Framework
TECHNOLOGIES
Lack of Programmers
Privacy
Government Policy & Law
Complexity
Security & Risk
Monopoly/Vendor Lock in
Cost Saving Agility &
Productivity
Automation
Communication,
Integration & Test
Loose Coupling
ServiceMesh
Serverless
BlockChain
AR/VR
Chatbots
Quantum
Computing
3DPrinting
Sharing
Economy
Fintech
IoT
AI&Analytics
Apps
Security
Integration
Observability
Infra&Cloud
Storage
Cost Saving Agility,
& Productivity
Automation
Communication,
Integration, and
Trust
Loose Coupling
Between Entitle
Lack of
Programmers
Privacy
Government
Policy and Law
Complexity
Security
Monopoly/
Vendor Lock-in
ServiceMesh
Serverless
BlockChain
AR/VR
Chatbots
Quantum
Computing
3DPrinting
Sharing
Economy
Fintech
IoT
AI&Analytics
Apps
Security
Integration
Observability
Infra&Cloud
Storage
Cost Saving Agility,
& Productivity
Automation
Communication,
Integration, and
Trust
Loose Coupling
Between Entitle
Lack of
Programmers
Privacy
Government
Policy and Law
Complexity
Security
Monopoly/
Vendor-Lock-in
Cost savings is the
key driver!
Everything
drives
integration
AI/ML
IoT
BlockChain
BigData
Cloud-
Native
Chatbots
EDA
Micro
Services
API
Quantum
Computing
AR/VR Serverless
Fntech
Service
Mesh
Incubation Hype Disillusionment Deployment
Worldwide
Change
Industry
Major
Advantage
Stage of Progress
PotentialImpact
Technology Canvas
(work in progress)
● A framework for us to analyze technologies
○ Are we asking the right questions
● Inspired by “Business Model Canvas”
○ Designed to capture a business model narrative
○ https://strategyzer.com/canvas/business-model-canvas
● The narrative and questions let us analyze an emerging
technology with a critical approach
Can it be
done with
reasonable
effort?
Is there real
impact?
Net positive drivers
Future & risks
Narrative
Blockchain
A distributed immutable ledger that
provides trust without a third party
Technology
Slow (8 trans/minute)
Scale is limited
Can’t undo operations
e.g. Ethereum, HyperLedger
Vision
Electronic cash (Bitcoin)
Decentralized systems without central
control (social network, DNS, auction,
prediction markets, global reputation)
Safe ledgers (Government records, land
registry)
Opinion
Still early, vision is too big in many ways
Artificial Intelligence
Enable computer based data driven
decisions
Enables automation
Currently world is limited by humans in
the loop.
Next industrial revolution may be
powered by unlimited decision making
power (as opposed to by unlimited
mechanical power in the last)
Opinion:
it has slowed down due to lack of
programmers and data scientists (needs
automation for the data science process
itself and turnkey solutions)
Many initial wins
Nate Silver Election Forecasts IBM Watson
Moneyball (Baseball)
Timeline
● Timeline for publication of GTO outputs
○ Serverless - end of July
○ Blockchain - end of September
○ We will release each technology updates independently and do
summaries connecting them at end of each year.
● Other candidate areas
○ Chatbots, IoT, Immersive AR/VR, AI & Analytics, etc
THANK YOU
wso2.com

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[WSO2Con Asia 2018] Unravelling Todays Disruptive Tech Landscape