Today's Technology and Emerging Technology Landscape
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The document discusses the rapidly evolving technology landscape and market forces affecting middleware, categorizing it into seven segments and providing growth estimates. It emphasizes emerging technologies like IoT, AI, and blockchain, while introducing a framework for analyzing these technologies critically. The timeline for publishing further technology outlooks and updates is also outlined, highlighting key drivers and barriers to growth.
Today's Technology and Emerging Technology Landscape
- 1. Vice President, Research, WSO2 Unravelling Todays Disruptive Tech Landscape Srinath Perera
- 3. ● 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
- 4. 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)
- 5. 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
- 7. 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
- 8. Understanding ETs: History EDI AI(take 1) RPC Automatic computing VM NoSQL Binary RPC JSON Chatbots GPU Deep Learning Big Data AI Serveless Blockchain API IoT Edge Computing AR/VR 3D Printing Quantum Computing Limited Success Died Major Impact Current Semantic Web Cloud DevOps Containers Microservices ROA SOA Web Services CORBA RMI OOP Design Patterns XML -2000 2000-05 2005-10 2010-15 2015- Legend
- 9. Understanding ETs: Gartner Hype Cycle
- 10. Understanding ETs: Carlota Perez Framework
- 12. 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
- 13. 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
- 14. Fintech AR/VR Quantum Computing 3D Printing ServiceMesh Serveless Sharing Economy Blockchain Chatbots EDA BigData AI/ML API Microservices Cloud-Native IoT Potential Impact Major Advantage Change Industry Worldwide Deployment Disillusionment Hype Incubation
- 15. 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
- 16. Can it be done with reasonable effort? Is there real impact? Net positive drivers Future & risks Narrative
- 19. 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
- 20. 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)
- 21. 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
- 23. Forces at Play ● Encourages Growth ○ Cost saving, agility, and productivity ○ Automation ○ Communication, integration, and trust ○ Loose coupling between entities (e.g. via SOA, microservices, API economy) ● Discourages Growth ○ Lack of programmers ○ Privacy ○ Government policy and law ○ Complexity ○ Security concerns ○ Monopoly / Vendor lock-In