Spring Boot - Bean LifeCycle

 Here is a clear, step-by-step lifecycle of a Spring Boot application, explained in a simple + interview-ready way.

---

🔄 Spring Boot Application Lifecycle

1️⃣ Application Start (Bootstrap Phase)

public static void main(String[] args) {
    SpringApplication.run(MyApp.class, args);
}

What happens internally:

1. SpringApplication object created

2. Application type detected

   • Servlet (Tomcat)

   • Reactive (Netty)

3. Environment prepared

   • application.properties / yml

   • Profiles (dev, test, prod)

4. Banner printed

5. ApplicationContext created

---

2️⃣ ApplicationContext Initialization

Spring creates the IoC container.

Key steps:

• Classpath scanning

• Load @Configuration classes

• Process @EnableAutoConfiguration

• Apply @ComponentScan

📌 Beans are defined, not created yet.

---

3️⃣ Bean Creation Phase (Core Lifecycle)

For each bean, Spring follows this order:

1. Instantiate Bean
2. Populate Properties (@Autowired)
3. Aware Interfaces
4. BeanPostProcessor (Before Init)
5. @PostConstruct / init-method
6. BeanPostProcessor (After Init)

Detailed Order:

🔹 1. Bean Instantiation

• Object is created using constructor

🔹 2. Dependency Injection

• @Autowired

• @Value

🔹 3. Aware Interfaces (Optional)

BeanNameAware
ApplicationContextAware
EnvironmentAware

🔹 4. BeanPostProcessor (Before Init)

postProcessBeforeInitialization()

🔹 5. Initialization

• @PostConstruct

• InitializingBean.afterPropertiesSet()

• init-method

🔹 6. BeanPostProcessor (After Init)

postProcessAfterInitialization()

📌 Bean is now ready to use

---

4️⃣ Embedded Server Startup

• Embedded Tomcat / Jetty / Netty starts

• DispatcherServlet initialized

• Application is ready to serve requests

Log example:

Started MyApp in 4.5 seconds

---

5️⃣ Application Ready Events

Spring fires lifecycle events:

Event	Purpose
ApplicationStartingEvent	App starting
ApplicationEnvironmentPreparedEvent	Env ready
ApplicationContextInitializedEvent	Context created
ApplicationPreparedEvent	Beans loaded
ApplicationReadyEvent	App ready

Example:

@EventListener(ApplicationReadyEvent.class)
public void onReady() {
    System.out.println("App is ready");
}

---

6️⃣ Request Processing Lifecycle (Runtime)

Client Request
   ↓
Filter
   ↓
Interceptor (preHandle)
   ↓
Controller
   ↓
Service
   ↓
Repository
   ↓
Response

---

7️⃣ Graceful Shutdown (End of Lifecycle)

Triggered by:

• Ctrl+C

• SIGTERM

• Kubernetes pod termination

Steps:

1. ContextClosedEvent

2. @PreDestroy

3. DisposableBean.destroy()

4. destroy-method

5. Embedded server stops

Example:

@PreDestroy
public void cleanup() {
    System.out.println("App shutting down");
}

---

🧠 Complete Lifecycle Diagram (Text)

main()
 ↓
SpringApplication.run()
 ↓
Prepare Environment
 ↓
Create ApplicationContext
 ↓
Bean Definition Load
 ↓
Bean Creation & Initialization
 ↓
Embedded Server Start
 ↓
ApplicationReadyEvent
 ↓
Application Running
 ↓
Shutdown Trigger
 ↓
Bean Destruction
 ↓
Context Closed

---

🎯 Interview One-Liner Answer

“Spring Boot lifecycle starts with SpringApplication.run, prepares the environment, initializes the ApplicationContext, creates and initializes beans, starts the embedded server, handles requests, and finally performs graceful shutdown by destroying beans.”

---

⚠️ Common Interview Follow-Ups

Q. Difference between @PostConstruct and @Bean init-method?
👉 @PostConstruct is JSR-250, init-method is Spring-specific.

Q. When are BeanPostProcessors executed?
👉 Before and after bean initialization.

Q. When does embedded Tomcat start?
👉 After ApplicationContext is refreshed.

---

If you want:

• 📌 Lifecycle diagram image

• 📌 Lifecycle vs Spring Framework comparison

• 📌 Real production troubleshooting examples

• 📌 Bean lifecycle coding question

Just tell me 👍

Microservices - Event Driven Architecture (EDA)

 Here is a clear, practical, and interview-ready explanation of Microservices with Event-Driven Architecture (EDA) 👇

---

🌐 Microservices – Event-Driven Architecture (EDA)

🔹 What is Event-Driven Architecture?

In EDA, microservices communicate by publishing and consuming events instead of calling each other directly.

👉 An event = “Something important happened”

Example:
OrderPlaced, PaymentCompleted, InventoryReserved

---

🤔 Why EDA with Microservices?

Problems with REST-only microservices ❌

• Tight coupling

• Service dependencies

• Cascade failures

• Poor scalability

EDA Benefits ✅

• Loose coupling

• High scalability

• Better fault tolerance

• Async communication

• Easy extensibility

---

🧩 Core Components of EDA

1️⃣ Event Producer

• Service that publishes an event

Order Service → OrderPlacedEvent

---

2️⃣ Event Broker

Message system:

• Kafka

• RabbitMQ

• AWS SNS/SQS

• Azure Event Hub

Acts as:

• Buffer

• Router

• Durable storage

---

3️⃣ Event Consumer

• Services that react to events

Inventory Service
Payment Service
Notification Service

---

🔄 Event Flow (Example)

Order Service
   |
   | OrderPlacedEvent
   v
Kafka Topic
   |
   |------------------|
Inventory Service   Payment Service

---

🛒 Real-World Example: E-Commerce

Scenario: Place Order

1. User places order

2. Order Service saves order

3. Publishes OrderPlacedEvent

4. Inventory Service reserves stock

5. Payment Service charges payment

6. Notification Service sends email

👉 No service calls another directly

---

🧠 Event Types

🔹 Domain Events (Most Common ⭐)

• Represent business facts

• Immutable

Example:

{
  "eventType": "OrderPlaced",
  "orderId": "123",
  "amount": 5000
}

---

🔹 Integration Events

• For cross-service communication

---

⚠️ Key Design Challenges (Very Important)

1️⃣ Eventual Consistency

• No immediate consistency

• Data sync happens over time

👉 Use Saga Pattern

---

2️⃣ Idempotency

• Same event processed multiple times

• Consumer must handle duplicates

---

3️⃣ Message Ordering

• Important for financial flows

• Use partitioning (Kafka)

---

4️⃣ Schema Evolution

• Backward compatible changes

• Use schema registry (Avro / Protobuf)

---

🔁 Saga Pattern (Brief)

🔹 Choreography-based Saga (Common ⭐)

• Services react to events

• No central controller

OrderPlaced → Payment → Inventory → OrderConfirmed

🔹 Orchestration-based Saga

• Central Saga manager controls flow

---

🧪 Failure Handling

• Dead Letter Queue (DLQ)

• Retry mechanism

• Circuit breaker (for sync parts)

---

🔐 Best Practices ⭐

• One event = one business fact

• Don’t share databases

• Use async wherever possible

• Keep events immutable

• Version events carefully

---

🎯 Interview One-Liners

Q: Why Event-Driven Microservices?
👉 To achieve loose coupling, scalability, and fault tolerance.

Q: Difference between REST and EDA?
👉 REST is synchronous; EDA is asynchronous and decoupled.

Q: What is eventual consistency?
👉 Data becomes consistent over time via events.

Q: Kafka vs RabbitMQ?
👉 Kafka = high-throughput event streaming
RabbitMQ = message-oriented queue

---

🛠️ Tech Stack Example

• Spring Boot

• Kafka

• Schema Registry

• Docker

• Kubernetes

• OpenTelemetry

---

If you want, I can:

• Draw EDA architecture diagram

• Show Spring Boot + Kafka example

• Explain Saga with code

• Share real interview Q&A PDF

Just tell me 👍