2. An Event is an Immutable Object containing details of
something that has happened
3. Businesses need to Respond to Events
● before the moment passes
● Predict and get Data to where it is needed
And move from Event-driven to
Event-streaming Architectures
4. Shopping Cart Example:
1. Added to cart (
Cust id=123, prod
id=34, quantity 2 )
Event key=1,
value {
Custid: 123,
Activity: Add,
Prodid: 34,
Quantity: 2
TimeStamp:
12:34:04
}
2. Updated cart (
Cust id=123, prod id=45
quantity 3 )
Event key=2,
value {
Custid: 123,
Activity: Add,
Prodid: 45,
Quantity: 3,
TimeStamp:
12:34:15
}
3. Delete cart (
Cust id=123, prod id=34
quantity 2 )
Event key=3,
value {
Custid: 123,
Activity: Delete,
Prodid: 34,
Quantity: 2,
TimeStamp:
12:34:50
}
3. Placed the order (
Cust id=123, prod id=34
quantity 4 )
Event key=4
value {
Custid: 123,
Activity: Order,
Prodid: 45,
Quantity: 3,
TimeStamp:
12:35:06
}
All of your Data is a Stream of events. It is the history of any entity
5.
6. Business uses of event streaming
Process payments and financial transactions in real-time
Track and monitor cars, trucks, fleets, and shipments in real-time
Continuously capture and analyze sensor data from IoT devices or other equipment
Collect and immediately react to customer interactions and orders
Monitor patients in hospital care and predict changes in condition to ensure timely
treatment in emergencies
Connect, store, and make available data produced by different divisions of a company
Serve as the foundation for data platforms, event-driven architectures, and
microservices.
Generate Real Time data-insights
8. What Does Kafka do ?
Publish and
Subscribe
Store Process
streams of events
9. Kafka Terminologies
Topic
Producer
Consumer
Broker
Partition
ZooKeeper
Any application who can publish Events (messages) to a topic
Any application that subscribes to a topic and consume these Events
Category or feed name to which records are published ( Folders in File System)-Container for Partitions
Each Server in a Kafka cluster
Topics are broken up into ordered commit logs called partitions/Units of storage for messages
Manages and coordinates a Kafka Broker
