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Journey to a Real-Time Enterprise
Neha Narkhede, Co-founder/CTO at Confluent, Co-Creator Apache Kafka
Journey to a Real-Time Enterprise Neha Narkhede, Co-founder/CTO at - - PowerPoint PPT Presentation
Journey to a Real-Time Enterprise Neha Narkhede, Co-founder/CTO at - - PowerPoint PPT Presentation
Journey to a Real-Time Enterprise Neha Narkhede, Co-founder/CTO at Confluent, Co-Creator Apache Kafka Infrastructure Technology ? Relational Data Database Warehousing Management Systems Adoption in Silicon Valley Adoption in Silicon
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Adoption in Silicon Valley
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Adoption in Silicon Valley
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Adoption in the Enterprise
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Fortune 500’s are using Apache KafkaTM
Global Banks Insurance Telecom Travel Companies
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Emergence of the Streaming Platform
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Pre-Streaming
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Request-Response Applications
Deterministic Rigid Tight coupling
App Service Service Service Service Service Service Service Service App
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App App
Developer APIs
Service Service
Event-Driven Applications
Responsive Flexible Extensible
Service Service Service Streaming Platform
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Pre-Streaming -> Event-Driven
Request-Response Event-Driven
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Message-Oriented Middlewhere
No persistence Single point of failure Not fault tolerant Cannot order messages Cannot process messaging in flight Order of magnitude lower throughput No “Replay” functionality
EAI & ESBs
Not event-oriented Fragile and bespoke Weak transformation capabilities
ETL
Often slow, batch oriented, and non-scalable Point-to-point not publish subscribe Not a true infrastructure platform
Why Didn’t It Work Before? Past Solutions Are Insufficient
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Microservices Mobile Machine Learning Internet of Things
The World has Changed
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What’s Needed? Event Centric Thinking
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Events What is an event?
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Events
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Events
A Sale An Invoice A Trade A Customer Experience
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All Your Data is Streams of Events
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What is a Company?
A business is a series of events and reacting to those events.
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5.2 Million Citizens
Event-Driven Government
Norwegian Work and Welfare Administration Life is a Stream of Events
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The Future of the Automotive Industry is a Real Time Data Cluster
Front, rear and top view cameras Ultrasonic Sensors Crash Sensors Front Camera Infrared Camera Front and Rear Radar Sensors Traffic Alerts Hazard Alerts Personalizatio n Anomaly Detection
MQTT MQTT MQTT MQTT MQTT MQTT
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Royal Bank of Canada Event-Driven Banking
30+ Use-cases 50+ apps 10+ different lines
- f businesses
Digital Marketing Security Consumer Credit Services SaaS Corporate Real Estate Investor Services Treasury Services …. Fraud Data Warehouse Microservices
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Internet of Things
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Banking
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Retail
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What is a Streaming Platform?
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The Streaming Platform
Technical Capabilities
Store Process Publish & Subscribe
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Three Lenses
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Messaging done right.
Lens 01
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Way More Than Message Queue
Lens 01
True Storage Real-time Processing Scalability
Messaging done right.
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Hadoop made fast.
Lens 02
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Stream Processing
Lens 02
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Lens 02
Applications are different Hadoop made fast.
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ETL and Data Integration as a platform.
Lens 03
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Lens 03
Scalable Streaming Data Pipelines
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Lens 03
Stream Processing is for more than data pipelines
ETL and Data Integration as a platform.
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Streaming Platform
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Journey to an Event-Driven Enterprise
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Streaming Adoption Journey
Pre-Streaming Streaming Awareness and Pilot Early Production Streaming Mission Critical, Integrated Streaming Global Streaming Central Nervous System
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What does the Event-Driven Architecture look like in its end state?
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An Event-Driven Enterprise
What are the possibilities?
- Everything is an event
- Available instantly to all applications
in a company
- Ability to query data as it arrives vs
when it is too late
- Simplifying the data architecture by
deploying a single platform
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Management Representing Data Connectors Support Apps RDBMS K/V Monitoring Search
DWH HADOOP Stream Processing Real-Time Analytics
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Management Representing Data Connectors Support
Apps RDBMS K/V Monitoring Search DWH HADOOP Stream Processing Real-Time Analytics
An open streaming platform around Kafka and it’s ecosystem
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Apps RDBMS K/V Monitoring Search DWH HADOOP Stream Processing Real-Time Analytics
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