Microservices Architecture Guide

12 min read

Updated Jun 19, 2025

Introduction

Microservices architecture is an approach to developing software applications as a suite of independently deployable, small, modular services. Each service runs in its own process and communicates through well-defined APIs.

Key Benefit: Microservices enable teams to develop, deploy, and scale services independently, improving agility and reducing time to market.

Monolithic vs Microservices

Aspect	Monolithic	Microservices
Deployment	Single deployable unit	Multiple independent services
Scaling	Scale entire application	Scale individual services
Technology	Single technology stack	Polyglot programming
Team Structure	Large, centralized teams	Small, autonomous teams
Failure Impact	Can affect entire system	Isolated to service
Complexity	Simple deployment, complex codebase	Complex deployment, simple services

Core Principles

Successful microservices architectures are built on fundamental principles:

Single Responsibility: Each service should have one reason to change
Autonomous Teams: Teams own their services end-to-end
Decentralized Governance: Services choose their own tech stack
Failure Isolation: Service failures don't cascade
Data Decentralization: Each service manages its own data
Smart Endpoints: Business logic in services, not middleware
Design for Failure: Assume everything will fail

Architecture Overview

A typical microservices architecture consists of multiple components working together:

┌─────────────────────────────────────────────────────────┐
│                    Client Applications                    │
│         (Web, Mobile, Desktop, Third-party)              │
└────────────────────────┬────────────────────────────────┘
                         │
┌────────────────────────▼────────────────────────────────┐
│                    API Gateway                           │
│     (Authentication, Routing, Rate Limiting)            │
└────┬────────┬────────┬────────┬────────┬──────────────┘
     │        │        │        │        │
┌────▼───┐ ┌─▼───┐ ┌──▼──┐ ┌──▼──┐ ┌──▼──┐
│Service │ │ Svc │ │ Svc │ │ Svc │ │ Svc │
│   A    │ │  B  │ │  C  │ │  D  │ │  E  │
└────┬───┘ └──┬──┘ └──┬──┘ └──┬──┘ └──┬──┘
     │        │       │       │       │
┌────▼────────▼───────▼───────▼───────▼──┐
│         Service Mesh (Optional)         │
│    (Service Discovery, Load Balancing)  │
└─────────────────────────────────────────┘
     │        │       │       │       │
┌────▼───┐ ┌──▼──┐ ┌──▼──┐ ┌──▼──┐ ┌──▼──┐
│  DB A  │ │ DB B│ │Cache│ │Queue│ │Store│
└────────┘ └─────┘ └─────┘ └─────┘ └─────┘

Key Components

API Gateway: Single entry point for all client requests
Service Registry: Dynamic service discovery and health checking
Configuration Service: Centralized configuration management
Circuit Breaker: Prevents cascading failures
Service Mesh: Infrastructure layer for service-to-service communication

Service Design

Designing microservices requires careful consideration of boundaries and responsibilities:

Service Boundaries

Domain-Driven Design Example yaml

# E-commerce platform service boundaries
services:
  - name: user-service
    responsibilities:
      - User registration and authentication
      - Profile management
      - Preferences and settings
    
  - name: product-service
    responsibilities:
      - Product catalog management
      - Inventory tracking
      - Product search and filtering
    
  - name: order-service
    responsibilities:
      - Order placement and management
      - Order status tracking
      - Order history
    
  - name: payment-service
    responsibilities:
      - Payment processing
      - Payment method management
      - Transaction history
    
  - name: notification-service
    responsibilities:
      - Email notifications
      - SMS notifications
      - Push notifications

Service Interface Design

RESTful API Design yaml

openapi: 3.0.0
info:
  title: User Service API
  version: 1.0.0
  
paths:
  /users:
    post:
      summary: Create a new user
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CreateUserRequest'
      responses:
        '201':
          description: User created successfully
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/User'
                
  /users/{userId}:
    get:
      summary: Get user by ID
      parameters:
        - name: userId
          in: path
          required: true
          schema:
            type: string
      responses:
        '200':
          description: User found
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/User'

Service Communication

Microservices communicate through various patterns and protocols:

Synchronous Communication

REST Client with Circuit Breaker javascript

const CircuitBreaker = require('opossum');
const axios = require('axios');

class UserServiceClient {
  constructor() {
    const options = {
      timeout: 3000,
      errorThresholdPercentage: 50,
      resetTimeout: 30000
    };
    
    this.breaker = new CircuitBreaker(this.callUserService, options);
    
    this.breaker.on('open', () => 
      console.log('Circuit breaker is open'));
    this.breaker.on('halfOpen', () => 
      console.log('Circuit breaker is half-open'));
    this.breaker.on('close', () => 
      console.log('Circuit breaker is closed'));
  }
  
  async getUser(userId) {
    return this.breaker.fire(userId);
  }
  
  async callUserService(userId) {
    const response = await axios.get(
      `http://user-service:8080/users/${userId}`,
      {
        timeout: 2000,
        headers: {
          'X-Request-ID': generateRequestId(),
          'X-Caller-Service': 'order-service'
        }
      }
    );
    return response.data;
  }
}

Asynchronous Communication

Event-Driven Architecture javascript

// Event Publisher
class OrderService {
  async createOrder(orderData) {
    // Create order in database
    const order = await this.orderRepository.create(orderData);
    
    // Publish order created event
    await this.eventBus.publish('order.created', {
      orderId: order.id,
      userId: order.userId,
      items: order.items,
      total: order.total,
      timestamp: new Date().toISOString()
    });
    
    return order;
  }
}

// Event Consumer
class InventoryService {
  constructor() {
    this.eventBus.subscribe('order.created', this.handleOrderCreated);
  }
  
  async handleOrderCreated(event) {
    console.log(`Processing order ${event.orderId}`);
    
    // Update inventory
    for (const item of event.items) {
      await this.inventoryRepository.decrementStock(
        item.productId, 
        item.quantity
      );
    }
    
    // Publish inventory updated event
    await this.eventBus.publish('inventory.updated', {
      orderId: event.orderId,
      items: event.items,
      timestamp: new Date().toISOString()
    });
  }
}

Data Management

Each microservice should manage its own data to ensure loose coupling:

Database per Service Pattern

Each service owns its database schema
No direct database access between services
Data is accessed only through service APIs
Choose the right database for each service's needs

Data Consistency Patterns

Saga Pattern

Manage distributed transactions across multiple services using choreography or orchestration.

Learn more →

Event Sourcing

Store all changes as a sequence of events, enabling audit trails and temporal queries.

Learn more →

CQRS

Separate read and write models for optimized queries and command processing.

Learn more →

Deployment Patterns

Microservices can be deployed using various strategies:

Container Orchestration with Kubernetes

Kubernetes Deployment yaml

apiVersion: apps/v1
kind: Deployment
metadata:
  name: user-service
  labels:
    app: user-service
spec:
  replicas: 3
  selector:
    matchLabels:
      app: user-service
  template:
    metadata:
      labels:
        app: user-service
    spec:
      containers:
      - name: user-service
        image: myregistry/user-service:v1.0.0
        ports:
        - containerPort: 8080
        env:
        - name: DB_HOST
          valueFrom:
            secretKeyRef:
              name: user-db-secret
              key: host
        resources:
          requests:
            memory: "256Mi"
            cpu: "250m"
          limits:
            memory: "512Mi"
            cpu: "500m"
        livenessProbe:
          httpGet:
            path: /health
            port: 8080
          initialDelaySeconds: 30
          periodSeconds: 10
        readinessProbe:
          httpGet:
            path: /ready
            port: 8080
          initialDelaySeconds: 5
          periodSeconds: 5
---
apiVersion: v1
kind: Service
metadata:
  name: user-service
spec:
  selector:
    app: user-service
  ports:
  - protocol: TCP
    port: 80
    targetPort: 8080
  type: ClusterIP

Service Mesh Integration

Automatic service discovery and load balancing
Encrypted service-to-service communication
Advanced traffic management and routing
Distributed tracing and monitoring

Monitoring & Observability

Comprehensive monitoring is crucial for microservices architectures:

The Three Pillars of Observability

Metrics

Quantitative data about system performance: latency, throughput, error rates, and resource utilization.

Logs

Detailed records of events and errors, structured for easy searching and correlation across services.

Traces

End-to-end request flow across multiple services, showing latency and dependencies.

Distributed Tracing Implementation

OpenTelemetry Integration javascript

const { NodeTracerProvider } = require('@opentelemetry/node');
const { registerInstrumentations } = require('@opentelemetry/instrumentation');
const { HttpInstrumentation } = require('@opentelemetry/instrumentation-http');
const { ExpressInstrumentation } = require('@opentelemetry/instrumentation-express');

// Initialize tracing
const provider = new NodeTracerProvider();
provider.register();

registerInstrumentations({
  instrumentations: [
    new HttpInstrumentation(),
    new ExpressInstrumentation(),
  ],
});

// Middleware to add trace context
app.use((req, res, next) => {
  const span = tracer.startSpan('http_request', {
    attributes: {
      'http.method': req.method,
      'http.url': req.url,
      'http.target': req.path,
      'service.name': 'user-service'
    }
  });
  
  // Add trace ID to response headers
  res.setHeader('X-Trace-ID', span.spanContext().traceId);
  
  res.on('finish', () => {
    span.setAttributes({
      'http.status_code': res.statusCode
    });
    span.end();
  });
  
  next();
});

Common Patterns

Essential patterns for building resilient microservices:

Saga Pattern

Choreography-based Saga javascript

// Order Service - Initiates the saga
class OrderSaga {
  async createOrder(orderData) {
    const order = await this.orderService.create({
      ...orderData,
      status: 'PENDING'
    });
    
    // Start saga by publishing event
    await this.eventBus.publish('OrderCreated', {
      orderId: order.id,
      userId: order.userId,
      items: order.items,
      total: order.total
    });
    
    return order;
  }
  
  // Compensating transaction
  async cancelOrder(orderId, reason) {
    await this.orderService.updateStatus(orderId, 'CANCELLED');
    
    await this.eventBus.publish('OrderCancelled', {
      orderId,
      reason,
      timestamp: new Date()
    });
  }
}

// Payment Service - Participates in saga
class PaymentSaga {
  constructor() {
    this.eventBus.subscribe('OrderCreated', this.processPayment);
    this.eventBus.subscribe('InventoryReserved', this.confirmPayment);
    this.eventBus.subscribe('InventoryFailed', this.cancelPayment);
  }
  
  async processPayment(event) {
    try {
      const payment = await this.paymentService.charge({
        userId: event.userId,
        amount: event.total,
        orderId: event.orderId
      });
      
      await this.eventBus.publish('PaymentProcessed', {
        orderId: event.orderId,
        paymentId: payment.id,
        status: 'SUCCESS'
      });
    } catch (error) {
      await this.eventBus.publish('PaymentFailed', {
        orderId: event.orderId,
        reason: error.message
      });
    }
  }
}

API Gateway Pattern

Single entry point for all client requests
Request routing and load balancing
Authentication and authorization
Rate limiting and throttling
Request/response transformation
API versioning and deprecation

Bulkhead Pattern

Isolate resources to prevent cascading failures:

Thread Pool Isolation java

@Component
public class PaymentServiceClient {
    private final ExecutorService paymentExecutor = 
        Executors.newFixedThreadPool(10); // Bulkhead of 10 threads
    
    private final ExecutorService inventoryExecutor = 
        Executors.newFixedThreadPool(5); // Bulkhead of 5 threads
    
    public CompletableFuture processPayment(PaymentRequest request) {
        return CompletableFuture.supplyAsync(() -> {
            // Payment processing logic
            return paymentService.process(request);
        }, paymentExecutor)
        .orTimeout(5, TimeUnit.SECONDS);
    }
    
    public CompletableFuture checkInventory(String productId) {
        return CompletableFuture.supplyAsync(() -> {
            // Inventory check logic
            return inventoryService.check(productId);
        }, inventoryExecutor)
        .orTimeout(3, TimeUnit.SECONDS);
    }
}

Best Practices

Follow these practices for successful microservices implementations:

Design Best Practices

Design services around business capabilities
Keep services small and focused
Ensure services are independently deployable
Use domain-driven design principles
Implement proper API versioning
Document all service interfaces

Operational Best Practices

Implement comprehensive monitoring and logging
Use distributed tracing for debugging
Automate testing at all levels
Implement circuit breakers and retries
Use health checks and graceful shutdowns
Plan for service discovery and load balancing

Technology Stack

Spring Boot

Java microservices

Express.js

Node.js services

gRPC

High-performance RPC

Kubernetes

Container orchestration

Istio

Service mesh

Apache Kafka

Event streaming

Prometheus

Metrics monitoring

Jaeger

Distributed tracing

Remember: Microservices add complexity. Start with a monolith and evolve to microservices as your team and application grow.

Note: This documentation is provided for reference purposes only. It reflects general best practices and industry-aligned guidelines, and any examples, claims, or recommendations are intended as illustrative—not definitive or binding.

Introduction

Monolithic vs Microservices

Core Principles

Architecture Overview

Key Components

Service Design

Service Boundaries

Service Interface Design

Service Communication

Synchronous Communication

Asynchronous Communication

Data Management

Database per Service Pattern

Data Consistency Patterns

Saga Pattern

Event Sourcing

CQRS

Deployment Patterns

Container Orchestration with Kubernetes

Service Mesh Integration

Monitoring & Observability

The Three Pillars of Observability

Metrics

Logs

Traces

Distributed Tracing Implementation

Common Patterns

Saga Pattern

API Gateway Pattern

Bulkhead Pattern

Best Practices

Design Best Practices

Operational Best Practices

Technology Stack

Related Documentation

High Availability Patterns

Cloud Native Patterns

Architecture Guide