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Event streaming is the real-time processing and distribution of event data—discrete records that represent state changes or actions. Modern systems like Apache Kafka leverage durable, high-throughput logs to store and forward these events, enabling reactive architectures, analytics, and collaboration across distributed services.

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Key Concepts

  • Event: A record of an occurrence (often a key-value pair) such as a user action, sensor reading, or system update.
  • Stream: An ordered, append-only sequence of events.
  • Stream Processing: The continuous transformation, enrichment, or routing of events as they arrive.
Event streaming differs from batch processing by handling data instantly rather than in periodic chunks. This low-latency approach powers use cases like fraud detection, monitoring, and live dashboards.

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How It Works: Live News Example

Imagine you’re watching live news on your TV. Behind the scenes:
  1. A news server generates packets of data—each packet is an event (e.g., breaking news, weather alert).
  2. These events are published continuously to a streaming platform (like Kafka).
  3. Your TV client subscribes to the news topic and renders each packet in real time.
The image illustrates the concept of event streaming, showing data packets moving from a server to a television where a person is watching breaking news.
In this scenario, each video frame or text bulletin is an event flowing through a durable log, ensuring you never miss a moment.

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Real-World Use Case: Taxi Booking App

A taxi-hailing app uses event streaming to coordinate riders, drivers, and billing services:
StepEvent TypeDescription
1. Request Rideride_requestedCustomer selects pickup/drop-off and sends a ride_requested event.
2. Broadcast to Driversride_offeredThe platform emits ride_offered to nearby drivers.
3. Driver Acceptsride_acceptedA driver returns ride_accepted, updating the customer’s UI with ETA and driver info.
4. Arrival & Startarrival, trip_startDriver arrives (arrival), passenger boards, then trip_start triggers billing.
5. Telemetry During TriptelemetryContinuous events like GPS coordinates, speed, and traffic data are streamed for analytics.
6. Trip Completiontrip_endOn drop-off, trip_end fires. The system calculates fare, charges the wallet, and pays out.
The image illustrates the fundamentals of event streaming through a sequence of events in a taxi booking process, from booking to the trip's completion. It includes six events: booking a taxi, driver acceptance, arrival at pickup, journey through the city, and reaching the destination.

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Benefits of Event Streaming

BenefitImpact
ScalabilityPartitioned logs enable horizontal scale for high-throughput loads.
DurabilityEvents persist on disk, surviving failures and time-window replays.
DecouplingProducers and consumers operate independently, improving agility.
Real-Time InsightsInstant analytics on live data for monitoring and alerting.

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Getting Started with Kafka

  1. Install Kafka
    Follow the Apache Kafka quickstart to set up a single-node cluster.
  2. Create a Topic 
    kafka-topics.sh --create --topic events --bootstrap-server localhost:9092 --partitions 3 --replication-factor 1
  3. Produce Events 
    kafka-console-producer.sh --topic events --broker-list localhost:9092
> {"eventType":"ride_requested","userId":"1234","pickup":"A","dropoff":"B"}
  4. Consume Events 
    kafka-console-consumer.sh --topic events --from-beginning --bootstrap-server localhost:9092

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