← Back to Questions
Microservices - Scenario based questions

How will you split a monolith into microservices?

Learn How will you split a monolith into microservices? with simple explanations, real-time examples, interview tips and practical use cases.

Updated: •

How Will You Split a Monolith Into Microservices?

Splitting a monolith into microservices is a gradual modernization process where a large tightly coupled application is decomposed into independently deployable, loosely coupled services based on business capabilities.

Main Goal

Convert Large Monolithic Application
Into Independent Scalable Services

What Is A Monolith?

A monolithic application is a single application where:

  • UI
  • Business logic
  • Database access
  • Authentication
  • Reporting
  • All modules

exist inside one deployable unit.

Example Monolith

E-Commerce Application

- User Module
- Order Module
- Payment Module
- Inventory Module
- Shipping Module

Single Codebase
Single Deployment
Single Database

Problems With Monolith

  • Slow deployments
  • Difficult scaling
  • Tight coupling
  • Large codebase
  • Single point of failure
  • Long release cycles
  • Technology limitations

Why Split Into Microservices?

  • Independent deployment
  • Better scalability
  • Fault isolation
  • Faster development
  • Cloud-native architecture
  • Technology flexibility
  • Team autonomy

Important Warning

Do NOT split a monolith blindly.

Wrong Migration Causes

  • Distributed monolith
  • Too many service calls
  • Latency issues
  • Operational complexity
  • Deployment failures

Correct Migration Strategy

Incremental Controlled Migration

Step-By-Step Process

  • Understand monolith
  • Identify business domains
  • Define bounded contexts
  • Choose decomposition strategy
  • Extract services gradually
  • Separate databases
  • Implement APIs/events
  • Add observability
  • Deploy incrementally

1. Understand The Existing Monolith

First analyze the current system completely.

Need To Understand

  • Business modules
  • Dependencies
  • Database schema
  • Transaction flows
  • Traffic patterns
  • Performance bottlenecks

Example

E-Commerce Monolith

- User Management
- Product Catalog
- Inventory
- Orders
- Payments
- Notifications

Important Question

Which Modules Can Be Independent?

2. Use Domain-Driven Design (DDD)

Most important principle.

Goal

Split Services Based On Business Domains

Example Domains

Business Domain Microservice
User Management User Service
Orders Order Service
Payments Payment Service
Inventory Inventory Service
Shipping Shipping Service

Benefits

  • Clear ownership
  • Loose coupling
  • Independent scaling

3. Identify Bounded Contexts

Each microservice should own one business capability.

Example

Payment Service

Owns:
- Payment Logic
- Payment Database
- Payment APIs

Important Rule

One Service Should Not Access
Another Service Database

4. Choose Decomposition Strategy

There are multiple ways to split a monolith.

Popular Strategies

  • Business capability decomposition
  • Subdomain decomposition
  • Transaction-based decomposition
  • Component decomposition

Best Production Approach

Business Capability Based Splitting

5. Start With Low-Risk Modules

Do not start with critical services.

Wrong Approach

Extract Payment System First

Correct Approach

Extract Notification Service First

Why?

  • Low business risk
  • Easy rollback
  • Team learning opportunity

6. Use Strangler Fig Pattern

Most popular migration strategy.

Concept

Gradually Replace Monolith Modules
One By One

Architecture

Client
   ↓
API Gateway
   ↓
Old Monolith
      +
New Microservices

Flow

Move One Feature
Test
Deploy
Repeat

Benefits

  • Reduced migration risk
  • Incremental modernization
  • Safer deployment

7. Separate Databases Carefully

Very difficult challenge.

Monolith

Single Shared Database

Microservices Principle

Database Per Service

Example

Service Database
User Service UserDB
Order Service OrderDB
Payment Service PaymentDB

Challenge

Removing Shared Tables And Joins

Solution

  • API communication
  • Event-driven architecture
  • Data replication

8. Implement Inter-Service Communication

Services must communicate safely.

Synchronous Communication

REST APIs
gRPC

Asynchronous Communication

Events
Queues
Messaging

Popular Messaging Tools

  • :contentReference[oaicite:0]{index=0}
  • :contentReference[oaicite:1]{index=1}

Example

Order Created Event
     ↓
Payment Service Consumes
     ↓
Inventory Service Consumes

Benefits

  • Loose coupling
  • Better scalability
  • Improved resilience

9. Handle Distributed Transactions

Transactions become difficult.

Monolith

Single Database Transaction

Microservices

Multiple Databases

Production Solution

  • Saga Pattern
  • Compensation transactions
  • Eventual consistency

Example

Order Created
      ↓
Payment Failed
      ↓
Cancel Order

10. Add API Gateway

Central entry point for clients.

Responsibilities

  • Routing
  • Authentication
  • Rate limiting
  • Load balancing
  • Security

Popular Tools

  • :contentReference[oaicite:2]{index=2}
  • :contentReference[oaicite:3]{index=3}

11. Implement Service Discovery

Dynamic environments require automatic discovery.

Problem

Containers Restart Frequently
IPs Change

Solution

Automatic Service Discovery

Popular Tools

  • :contentReference[oaicite:4]{index=4}
  • :contentReference[oaicite:5]{index=5}
  • :contentReference[oaicite:6]{index=6}

12. Add Resilience Patterns

Distributed systems fail frequently.

Need

  • Circuit breakers
  • Retries
  • Timeouts
  • Bulkhead isolation

Popular Tool

  • :contentReference[oaicite:7]{index=7}

13. Implement Centralized Logging

Debugging becomes difficult.

Need

Centralized Logs

Popular Tools

  • :contentReference[oaicite:8]{index=8}

Benefits

  • Production debugging
  • Log correlation

14. Add Distributed Tracing

Track requests across services.

Popular Tools

  • :contentReference[oaicite:9]{index=9}
  • :contentReference[oaicite:10]{index=10}

Benefits

  • Find bottlenecks
  • Trace failures

15. Containerize Services

Microservices are usually containerized.

Popular Platform

  • :contentReference[oaicite:11]{index=11}

Benefits

  • Portable deployments
  • Environment consistency

16. Use Kubernetes For Orchestration

Production microservices require orchestration.

Capabilities

  • Auto scaling
  • Self-healing
  • Rolling deployments
  • Service discovery
  • Load balancing

Popular Platform

  • :contentReference[oaicite:12]{index=12}

17. CI/CD Automation

Microservices require deployment automation.

Need

  • Automated builds
  • Automated testing
  • Automated deployment
  • Rollback support

Popular Tools

  • :contentReference[oaicite:13]{index=13}
  • :contentReference[oaicite:14]{index=14}

18. Real Production Migration Example

Banking Monolith

Large Banking Application

Step 1

Extract Notification Service

Step 2

Extract User Service

Step 3

Extract Payment Service

Communication

Kafka Event-Driven Architecture

Challenges Faced

  • Shared Oracle database
  • Distributed transactions
  • API latency
  • Logging complexity

Solutions

  • Saga pattern
  • Kafka async events
  • Kubernetes deployment
  • Centralized observability

Final Result

  • Independent scaling
  • Faster deployments
  • Improved resilience
  • Cloud-native platform

Migration Anti-Patterns

Anti-Pattern Problem
Big Bang Migration High risk
Shared Database Tight coupling
Too Many Small Services Operational complexity
Synchronous Communication Everywhere High latency
No Observability Production debugging issues

Production Best Practices

Practice Purpose
DDD Correct service boundaries
Strangler Pattern Incremental migration
Database Per Service Loose coupling
Event-Driven Architecture Scalability
Saga Pattern Distributed transactions
Centralized Logging Troubleshooting
Kubernetes Orchestration
CI/CD Deployment automation

Final Interview Answer

To split a monolith into microservices, I would first analyze the existing application thoroughly to understand business domains, dependencies, database structure, and transaction flows. Then I would use Domain-Driven Design principles to identify bounded contexts and split services based on business capabilities such as User Service, Order Service, Payment Service, and Inventory Service. Instead of performing a risky big-bang migration, I would use the Strangler Fig pattern to gradually extract modules one by one. Each microservice would own its database to avoid tight coupling, and communication between services would happen through REST APIs or asynchronous event-driven messaging using tools like :contentReference[oaicite:15]{index=15} or :contentReference[oaicite:16]{index=16}. For distributed transaction management, I would implement Saga patterns and eventual consistency mechanisms. I would also introduce API gateways, service discovery, centralized logging, distributed tracing, and resilience patterns like circuit breakers using :contentReference[oaicite:17]{index=17}. Finally, I would containerize services using :contentReference[oaicite:18]{index=18} and deploy them on :contentReference[oaicite:19]{index=19} with automated CI/CD pipelines for scalable and reliable production deployments.

Why this Microservices - Scenario based questions question is important?

This interview question helps candidates understand real-time backend development concepts, practical problem solving, coding fundamentals, system design basics and production-ready application behavior.

Practice this question carefully for Java backend roles, Spring Boot developer interviews, microservices interviews, company interviews and full-stack developer preparation.

About the Author

Naresh Kumar is a Senior Java Backend Engineer with experience building enterprise applications using Java, Spring Boot, Microservices, Docker, Kubernetes and Cloud technologies.