What You Will Learn

• What is Event Driven Architecture?
• Why EDA is Needed
• Events, Producers, Consumers
• Event Brokers
• Kafka Architecture
• RabbitMQ Architecture
• Event Streaming
• CQRS Integration
• Event Sourcing Integration
• Saga Integration
• Enterprise Use Cases
• Interview Questions

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Introduction

Traditional systems use:

Request

↓

Response

↓

Request

↓

Response

Example:

Order Service

↓

Inventory Service

↓

Payment Service

↓

Notification Service

Services directly call each other.

Problems:

Tight Coupling

Slow Response Time

Poor Scalability

Failure Propagation

Event Driven Architecture solves these problems.

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What is Event Driven Architecture?

Event Driven Architecture (EDA) is a software architecture where systems communicate using events.

Instead of:

Service A Calls Service B

Use:

Service A Publishes Event

↓

Interested Services Consume Event

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Purpose of EDA

Primary Goal:

Loose Coupling

Through Events

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Traditional Architecture

flowchart LR

A[Order Service]

B[Inventory Service]

C[Payment Service]

D[Notification Service]

A --> B
B --> C
C --> D

Strong dependencies.

---

Event Driven Architecture

flowchart LR

A[Order Service]

B[Event Broker]

C[Inventory Service]

D[Payment Service]

E[Notification Service]

A --> B

B --> C
B --> D
B --> E

Loosely coupled.

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Real World Analogy

Think about:

Airport Announcement System

Announcement:

Flight Delayed

Listeners:

Passengers

Airport Staff

Ground Crew

Announcement doesn't know who listens.

Same concept in EDA.

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Core Components

Events

Producers

Consumers

Event Broker

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What is an Event?

An event represents:

Something That Happened

Examples:

OrderCreated

PaymentCompleted

ClaimApproved

AccountOpened

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Event Characteristics

Immutable

Past Tense

Business Meaningful

Timestamped

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Event Example

{
  "event":"OrderCreated",
  "orderId":"1001",
  "amount":500
}

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Event Producer

Producer creates events.

Example:

Order Service

publishes:

OrderCreated

---

Producer Flow

flowchart LR

A[Order Service]

B[OrderCreated Event]

A --> B

---

Event Consumer

Consumer receives events.

Examples:

Inventory Service

Payment Service

Notification Service

---

Consumer Flow

flowchart LR

A[OrderCreated Event]

B[Inventory Service]

C[Payment Service]

D[Notification Service]

A --> B
A --> C
A --> D

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Event Broker

Acts as:

Middle Layer

between producers and consumers.

Popular Brokers:

Kafka

RabbitMQ

ActiveMQ

AWS SNS

Google PubSub

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Event Broker Architecture

flowchart LR

A[Producer]

B[Broker]

C[Consumer]

A --> B
B --> C

---

Event Lifecycle

Generate Event

↓

Publish Event

↓

Store Event

↓

Consume Event

↓

Process Event

---

Event Flow

flowchart LR

A[Business Action]

B[Create Event]

C[Broker]

D[Consumers]

A --> B
B --> C
C --> D

---

Order Processing Example

Customer places order.

---

Event Produced

OrderCreated

---

Consumers

Inventory Service

Payment Service

Shipping Service

Analytics Service

---

Order Workflow

flowchart LR

A[Order Service]

B[OrderCreated Event]

C[Inventory Service]

D[Payment Service]

E[Shipping Service]

F[Analytics Service]

A --> B

B --> C
B --> D
B --> E
B --> F

---

Kafka Overview

Kafka is the most popular EDA platform.

Key Concepts:

Producer

Topic

Partition

Consumer

Consumer Group

---

Kafka Architecture

flowchart LR

A[Producer]

B[Kafka Topic]

C[Consumer 1]

D[Consumer 2]

A --> B

B --> C
B --> D

---

Kafka Topic

Topic stores events.

Example:

orders

payments

customers

---

Kafka Topic Flow

flowchart LR

A[Order Service]

B[Orders Topic]

C[Inventory Consumer]

D[Analytics Consumer]

A --> B

B --> C
B --> D

---

Kafka Consumer Groups

Multiple consumers.

Example:

Inventory Group

Analytics Group

Notification Group

Each receives events independently.

---

Consumer Group Architecture

flowchart LR

A[Kafka Topic]

B[Inventory Group]

C[Analytics Group]

D[Notification Group]

A --> B
A --> C
A --> D

---

RabbitMQ Overview

RabbitMQ uses:

Exchange

Queue

Consumer

---

RabbitMQ Architecture

flowchart LR

A[Producer]

B[Exchange]

C[Queue 1]

D[Queue 2]

E[Consumer]

A --> B

B --> C
B --> D

C --> E

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Kafka vs RabbitMQ

Feature	Kafka	RabbitMQ
Throughput	Very High	High
Event Replay	Yes	Limited
Streaming	Excellent	Moderate
Ordering	Strong	Moderate

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Event Streaming

Events continuously flow.

Example:

Order Events

Payment Events

User Events

Inventory Events

---

Streaming Flow

flowchart LR

A[Producer]

B[Event Stream]

C[Consumers]

A --> B
B --> C

---

Banking Example

Fund Transfer Completed.

Event:

TransferCompleted

Consumers:

Fraud Service

Audit Service

Notification Service

---

Banking Architecture

flowchart LR

A[Transfer Service]

B[Transfer Event]

C[Fraud Service]

D[Audit Service]

E[Notification Service]

A --> B

B --> C
B --> D
B --> E

---

Insurance Example

Claim Approved.

Event:

ClaimApproved

Consumers:

Payment Service

Audit Service

Email Service

---

Insurance Workflow

flowchart LR

A[Claim Service]

B[ClaimApproved]

C[Payment Service]

D[Email Service]

E[Audit Service]

A --> B

B --> C
B --> D
B --> E

---

Retail Example

Order Created.

Consumers:

Inventory

Shipping

Analytics

Recommendations

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Retail Architecture

flowchart LR

A[Order Service]

B[Order Event]

C[Inventory]

D[Shipping]

E[Analytics]

A --> B

B --> C
B --> D
B --> E

---

EDA + CQRS

Commands generate events.

Queries read projections.

---

CQRS Integration

flowchart LR

A[Command]

B[Event]

C[Projection]

D[Read Model]

A --> B
B --> C
C --> D

---

EDA + Event Sourcing

Events become source of truth.

---

Event Sourcing Integration

flowchart LR

A[Events]

B[Event Store]

C[Current State]

A --> B
B --> C

---

EDA + Saga

Saga coordinates distributed transactions through events.

---

Saga Flow

flowchart LR

A[OrderCreated]

B[InventoryReserved]

C[PaymentCompleted]

D[ShipmentCreated]

A --> B
B --> C
C --> D

---

Real Enterprise Architecture

flowchart LR

A[API Gateway]

B[Order Service]

C[Kafka]

D[Inventory Service]

E[Payment Service]

F[Notification Service]

G[Analytics Service]

A --> B

B --> C

C --> D
C --> E
C --> F
C --> G

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Benefits

✅ Loose Coupling

✅ Scalability

✅ High Throughput

✅ Fault Tolerance

✅ Event Replay

✅ Asynchronous Processing

✅ Cloud Native Friendly

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Challenges

❌ Eventual Consistency

❌ Complex Debugging

❌ Event Ordering

❌ Monitoring Complexity

❌ Distributed Tracing

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Enterprise Use Cases

Banking

Payments

Transfers

Fraud Detection

---

Insurance

Claims

Policies

Premium Processing

---

Retail

Orders

Inventory

Shipping

---

Healthcare

Patient Events

Medical Records

---

Travel

Bookings

Notifications

Payments

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When To Use EDA

Use when:

Microservices

Kafka

High Throughput

Asynchronous Workflows

Cloud Native Applications

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When NOT To Use

Avoid when:

Simple CRUD Applications

Small Monoliths

Synchronous Business Flows

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Interview Questions

What is Event Driven Architecture?

An architecture where services communicate through events.

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Main Components?

Producer

Consumer

Event

Broker

---

Kafka Role?

Acts as event broker and streaming platform.

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Benefits?

Loose coupling and scalability.

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Drawbacks?

Eventual consistency and complexity.

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Difference Between REST and EDA?

REST is synchronous.

EDA is asynchronous.

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EDA and CQRS Relationship?

CQRS often uses EDA for communication.

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Key Takeaways

• Event Driven Architecture is the foundation of modern distributed systems.
• Services communicate using events instead of direct calls.
• Kafka and RabbitMQ are common implementations.
• Enables loose coupling, scalability, and resilience.
• Works naturally with CQRS, Event Sourcing, Saga, and Outbox patterns.
• Widely used in Banking, Insurance, Retail, Healthcare, and Cloud Native platforms.
• One of the most important architecture patterns for modern microservices.

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