✨ Before you dive in Kafka

Imagine if you didn’t have to wait around for someone to reply before getting on with your day.
You just do your part, make a quick announcement — and move on.
Anyone who needs to know can pick it up when they're ready.

That’s how event-based communication works. It’s like living in a world where everyone’s tuned in to the right signals, and no one’s left waiting.

🍕 When You’re the Producer:

You just baked a pizza.

Instead of calling each family member:

• You ring the bell — “Pizza’s ready!”

• Everyone who’s hungry hears it and comes to the kitchen

• ✅ You don’t wait. You move on to cleaning up or watching TV.

📦 When You’re the Consumer:

You're waiting for a delivery.

Instead of checking the front door every 10 minutes:

• You relax.

• The doorbell rings when the package arrives.

• You get up, grab it, and carry on.

✅ You didn’t waste time waiting. You just reacted when the event happened.

🧠 Real-World Impact

You don’t constantly check, call, or coordinate.
You just send signals. Listen for signals. And act when it’s your turn.

That’s the power of event-driven systems.
That’s what Kafka makes possible — in tech and in life.

Visualise Kafka with Real Life Analogy

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🔄 #1 : A Busy Post Office

In a small town:

• People write letters (information)

• They drop them into the mailbox (a central place)

• The post office picks them up, sorts them, and delivers them to whoever needs them — maybe a person, a business, or even multiple recipients.

No one needs to call ahead. You just post it and trust the system.

🚫 Now Imagine the Town Without a Post Office

• You’d have to personally deliver every letter.

• If your friend wasn’t home, you’d have to try again later.

• You’d need to know everyone’s address and timing.

• If you needed to tell multiple people something, you’d go door to door.

It would be chaotic, slow, and error-prone — especially in a growing town.

✅ Kafka Is Like a Post Office for Software

In a digital system:

• Apps write messages (letters) and drop them into Kafka (mailbox).

• Kafka stores, sorts, and delivers those messages to whoever asked for them (other apps or systems).

• Everyone can work independently, without calling each other directly.

• Messages don’t get lost — they’re delivered, stored, and can be replayed later if needed.

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🔄 #2 : Airport Announcements

At an airport:

• When a gate change or delay is announced, everyone listening gets the update at once.

• The airline doesn’t go to each passenger individually.

• People hear what’s relevant and act on it.

Kafka works the same way — it broadcasts events, and different parts of your system respond only if it’s relevant to them.

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So What is Kafka ?

Apache Kafka is an open-source platform used to stream data in real time between different parts of a system.
Think of it like a central nervous system for your software — it lets apps talk to each other by sending messages/events.

Simply put, Kafka is a platform for:

• Publishing events (like user signup, payment done)

• Subscribing to events (like sending confirmation emails)

• Streaming data between services in real time

• Storing events safely for future use

💡 Why Was Kafka Needed?

Before Kafka, systems:

• Had to call each other directly (like going door to door)

• Would break if one system was slow or unavailable

• Couldn’t handle high volume or real-time needs

Kafka fixed this by introducing:

• One central hub for communication

• Speed, reliability, and independence

• A way to go back in time and see what happened

🏗️ Real-World Example: Kafka in Digital Banking

• User signs up → Event user.created is published

• Notification Service reads the event → Sends welcome SMS

• Audit Service reads the same event → Logs it for compliance

• Analytics Engine reads the event → Updates real-time dashboard

All these happen without any direct API calls between services.

Key Terminology:

• Service

• Producer

• Consumer

• Kafka Broker

• Kafka Topic

• Subscribe to a Topic

💼 Service

A software application or microservice that performs a specific job.

🔧 Example: A User Service creates accounts. A Payment Service processes payments.
It can produce, consume, or both in a Kafka setup.

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✉️ Producer

A program or service that sends messages (events) to Kafka.

🧠 Think: “I have something to say.”
E.g., User Service sends a user.created event to Kafka.

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👂 Consumer

A program or service that reads messages from Kafka.

🧠 Think: “I’m listening for updates.”
E.g., Notification Service listens for user.created events to send welcome emails.

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🏣 Kafka Broker

The central server in Kafka that stores and delivers messages.

🧠 Think: Like a smart post office — it holds all the messages and makes sure consumers get them reliably.

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🗂 Kafka Topic

A named category where Kafka messages are stored and grouped.

🧠 Think: A folder or mailbox for a specific type of event, like user.created, payment.successful, or order.cancelled.

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📬 Subscribe to a Topic

A consumer’s way of saying: “Give me all messages from this topic.”

🧠 Example: Notification Service subscribes to the user.created topic
→ Kafka gives it every new user signup event.

Here’s Simple and Clear mapping of Kafka terms to the two analogies we’ve been using: 

Post Office and Airport Announcements. 

This will help solidify your understanding with real-world visuals:

📮 POST OFFICE Analogy

📝 Example:

• Turtle Bank (Service) produces an event: "New account opened" → drops a message into the Accounts topic

• Notification Service subscribes to that topic → gets the message and sends a welcome SMS

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✈️ AIRPORT ANNOUNCEMENT Analogy

📝 Example:

• Airline staff announces: “Flight QF101 now boarding” on gate speakers (Topic = flight.qf101.status)

• Passengers and airport apps that subscribed to that flight instantly receive the update and react

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🎯 Quick Summary Table

Relationships ( Service, Broker & Topic )

Let’s break down the relationship between Service, Topic, Event, Broker, Producer, and Consumer in simple terms with a real-world analogy and a technical perspective.

🧩 Real-World Analogy: Town Radio Station

Imagine a town with:

• Several people making announcements (Producers)

• A radio station (Kafka Broker)

• Each topic has its own radio channel (Kafka Topic)

• Several tuned-in listeners (Consumers)

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🔗 Key Terms & Relationships (Simplified)

🔄 Recap: Relationships

• A Service can act as both Producer and Consumer

• A Producer sends Events to a Topic via a Kafka Broker

• A Consumer subscribes to a Topic and reacts to incoming Events

• The Kafka Broker acts as a smart middleman, ensuring durability, ordering, and distribution

🧾 User Journey: Making a Payment (End-to-End View with Kafka)

Let’s put it all together to understand a Payment user journey for payment made through an Digital Banking App implemented using event-based architecture

Same workflow explained via sequence diagram:

The sequence diagram version of the Kafka event flow for Sarah’s payment:

• It shows the flow from the user action, through Payment Service, to Kafka, and out to all consumer services.

• Each message and system action is shown in order, making it ideal for technical walkthroughs or architectural documentation.

👩‍💼 Step 1: User Makes a Payment

• A customer, Sarah, opens her banking app and pays her electricity bill.

• She taps "Pay Now."

🛠 Step 2: Payment Service kicks in

• The Payment Service receives the request.

• It starts processing: checks the amount, balance, and receiver.

• As soon as it begins, it generates an event called txn.initiated.

✉️ Step 3: Producer sends the event to Kafka

• Inside the Payment Service, a Producer component packages the message:

    {
      "type": "txn.initiated",
      "userId": "sarah123",
      "amount": 150,
      "timestamp": "2025-05-23T10:32:00Z"
    }
  

• It sends this to Kafka under the topic txn.initiated.

🗂 Step 4: Kafka Topic & Broker handle the event

• Kafka receives the event and stores it in the txn.initiated topic.

• The Kafka Broker:

  • Safely stores the message

  • Keeps track of which consumers have read it

  • Makes it available instantly to anyone subscribed

📥 Step 4.5: Services Subscribe to the Topic

Before any message can be delivered, each consumer service must subscribe to the topic.
This means:

• Notification Service subscribes to txn.initiated

• Fraud Detection, Analytics Engine, and Audit Service also subscribe

By subscribing, they’re saying:

“Hey Kafka, let me know whenever something new happens on this topic.”

Kafka will now automatically deliver new messages to each service as soon as they’re available.

📡 Step 5: Multiple Services (Consumers) React

All of these services are listening to the txn.initiated topic and act independently:

Hope, this gives an basic overall understanding of Kafka and it’s nuts and bolt. Next we’ll do a deep dive by looking an Sample Banking Application