Techniques for Refactoring a Monolith to Microservices

Transforming a monolithic program into a microservices architecture is a big change that improves maintainability, scalability, and flexibility. To guarantee a seamless transition, it is not a simple process and calls for thorough planning, execution, and the application of the appropriate procedures. The main methods for converting a monolith to microservices will be covered in this post, along with helpful advice on how to handle the intricacy of this architectural shift.

Why Refactor from Monolith to Microservices?

Over time, maintaining and scaling monolithic applications—where the entire codebase is closely connected and deployed as a single unit—can become challenging. Development slows down, deployments become riskier, and scaling particular application components becomes difficult as the application gets larger.

The monolithic architecture, on the other hand, can be divided into smaller, independent services that can be created, implemented, and scaled independently thanks to microservices. This change facilitates more autonomous teamwork, increases fault separation, and improves scalability.

Key Techniques for Refactoring a Monolith to Microservices

1. Understand Your Domain (Domain-Driven Design - DDD)

Before starting the refactoring process, it’s essential to have a thorough understanding of your application’s domain. Domain-Driven Design (DDD) helps break down the monolith into smaller, logical components or bounded contexts, each representing a distinct part of your business domain.

↳ Bounded Context: Identify distinct boundaries within your application that can become microservices. For example, an e-commerce application might have separate bounded contexts for orders, payments, and user management.

↳ Domain Events: Use domain events to define how different parts of the system communicate.

Example: Identifying Bounded Contexts

In a monolithic e-commerce system:

👉🏻 Order Service: Handles order creation and management.
👉🏻 Payment Service: Processes payments and handles transactions.
👉🏻 User Service: Manages user authentication and profiles.

Each of these services can be identified as a bounded context and later refactored into a separate microservice.

2. Decompose the Monolith Gradually

Breaking a monolith all at once is risky and complex. Instead, a more practical approach is to refactor the system incrementally by decomposing it one piece at a time. This allows you to isolate and extract services without disrupting the entire application.

↳ Start with Non-Critical Components: Begin by extracting non-critical services (e.g., reporting, authentication) to minimize risk.

↳ Identify Service Boundaries: Look for natural boundaries in your code where services can be split (e.g., modular parts of the application like user management, and product catalog).

Example: Extracting the User Service

In the e-commerce application, start by moving the User Service out of the monolith into its own microservice. The monolith should communicate with the new service via API calls.

// Original monolith function
function getUserProfile(userId) {
  // Fetch user from monolithic database
  return db.getUserById(userId);
}

// Refactored microservice communication
async function getUserProfile(userId) {
  const response = await fetch(`https://userservice/api/users/${userId}`);
  return response.json();
}

3. Implement an API Gateway

When refactoring to microservices, each service typically has its own API. An API Gateway serves as a single entry point for client requests, routing them to the appropriate microservice. It can also handle cross-cutting concerns like authentication, logging, rate limiting, and load balancing.

Advantages: Simplifies client communication with the microservices, improves security, and centralizes API management.

Example: API Gateway Setup

// API Gateway routes requests to the appropriate service
app.get('/api/users/:id', (req, res) => {
  const userId = req.params.id;
  fetch(`https://userservice/api/users/${userId}`)
    .then(response => response.json())
    .then(userData => res.send(userData));
});

4. Use a Strangler Pattern

The strangler pattern is a technique that allows you to gradually replace the monolithic system with microservices by “strangling” the old monolith, piece by piece. As new services are created, the monolith is slowly phased out until it is completely replaced.

How it works: Redirect traffic from the monolithic system to new microservices for specific features or functionality, while leaving other parts of the monolith intact. Over time, the monolith is "strangled" as more functionality is moved to microservices.

Example: Strangler Pattern in Action

1️⃣ Original monolith handles user authentication.
2️⃣ New authentication microservice is developed.
3️⃣ API Gateway redirects authentication requests to the new microservice.
4️⃣ Gradually, the monolithic authentication code is deprecated.

5. Handle Data Management and Consistency

Microservices introduce a new challenge: distributed data management. In a monolith, you typically have a single database, but with microservices, each service often has its own database. To manage this:

↳ Database per Service: Each microservice should own its data and have its own database to prevent tight coupling between services.

↳ Event-Driven Communication: Use an event-driven architecture (via message queues like Kafka or RabbitMQ) to maintain data consistency across services.

Example: Event-Driven Architecture for Order Creation

1️⃣ User places an order, and the Order Service stores it in its database.
2️⃣ The Order Service emits an event (OrderPlaced).
3️⃣ The Inventory Service listens for OrderPlaced events and updates stock levels accordingly.

// Emit an event after order creation
function createOrder(order) {
  orderDb.save(order);
  eventEmitter.emit('OrderPlaced', order);
}

// Inventory service listens for order events
eventEmitter.on('OrderPlaced', (order) => {
  inventoryService.updateStock(order.items);
});

6. Implement Resilience and Fault Tolerance

With microservices, failures are inevitable, and each service must be resilient to failure. Techniques like circuit breakers, retry policies, and timeouts are essential to ensure the entire system doesn't fail when one microservice experiences issues.

↳ Circuit Breaker: Prevents cascading failures by halting requests to a failing service after a certain number of failed attempts.

↳ Retry Logic: Automatically retries failed requests based on a backoff policy.

Example: Circuit Breaker in Node.js

const circuitBreaker = require('opossum');

const options = {
  timeout: 3000, // 3 seconds
  errorThresholdPercentage: 50,
  resetTimeout: 30000, // 30 seconds
};

const userServiceBreaker = new circuitBreaker(fetchUserProfile, options);

async function fetchUserProfile(userId) {
  // External API call
  const response = await fetch(`https://userservice/api/users/${userId}`);
  return response.json();
}

Although converting a monolithic application to a microservices architecture is a complicated task, a scalable and maintainable architecture may be achieved by adhering to a carefully thought-out design. To successfully go from a monolith to microservices, you'll need to employ strategies like Domain-Driven Design, gradual deconstruction, the strangler pattern, handling distributed data, and establishing fault tolerance. Your system will be more able to manage expansion, support separate deployments, and withstand failures if it is divided into smaller, independent services.