Anti-patterns (distributed monolith, chatty services) in Microservices - System Design Exercise

Design: Microservices Architecture with Anti-patterns

Focus on service design and communication patterns. Database design and UI are out of scope.

Functional Requirements

FR1: Design a microservices-based system for an e-commerce platform

FR2: Services should handle user management, product catalog, order processing, and payment

FR3: Each service should be independently deployable and scalable

FR4: Services must communicate to fulfill user requests

Non-Functional Requirements

NFR1: System should support 10,000 concurrent users

NFR2: API response time p99 under 300ms

NFR3: Availability target 99.9% uptime

NFR4: Avoid tight coupling between services

Think Before You Design

Questions to Ask

❓ Question 1

❓ Question 2

❓ Question 3

❓ Question 4

❓ Question 5

Key Components

API Gateway

Service Registry and Discovery

Message Broker for asynchronous communication

Individual microservices with own databases

Load Balancer

Design Patterns

Service Mesh

Event-driven architecture

Circuit Breaker

Bulkhead pattern

API Gateway pattern

Reference Architecture

          +----------------+          +----------------+
          |  API Gateway   |          |  Service Mesh  |
          +-------+--------+          +-------+--------+
                  |                           |
    +-------------+-------------+-------------+-------------+
    |                           |                           |
+---v---+                   +---v---+                   +---v---+
| User  |                   | Order |                   | Product|
|Service|                   |Service|                   |Service |
+---+---+                   +---+---+                   +---+---+
    |                           |                           |
+---v---+                   +---v---+                   +---v---+
| User  |                   | Order |                   | Product|
| DB    |                   | DB    |                   | DB     |
+-------+                   +-------+                   +-------+

Note: Services communicate asynchronously via message broker to reduce chatty calls.

Components

API Gateway

Nginx or Kong

Single entry point for clients, routes requests to services

User Service

Spring Boot microservice

Handles user registration, authentication, profile management

Order Service

Node.js microservice

Manages order creation, updates, and status

Product Service

Go microservice

Manages product catalog and inventory

Message Broker

Apache Kafka or RabbitMQ

Enables asynchronous communication between services to reduce chatty calls

Service Mesh

Istio or Linkerd

Manages service-to-service communication, retries, and circuit breaking

Databases

PostgreSQL per service

Each service owns its own database to avoid tight coupling

Request Flow

1. Client sends request to API Gateway

2. API Gateway routes request to appropriate microservice

3. Microservice processes request using its own database

4. If data from another service is needed, microservice publishes event to message broker

5. Other services consume events asynchronously to update their state or trigger actions

6. Service Mesh manages communication reliability and security

7. API Gateway returns response to client

Database Schema

UserService: User(id PK, name, email, password_hash) OrderService: Order(id PK, user_id FK, product_id FK, quantity, status) ProductService: Product(id PK, name, description, price, stock_quantity) Each service owns its schema with no shared tables to avoid distributed monolith.

Scaling Discussion

Bottlenecks

Excessive synchronous calls between services causing high latency (chatty services)

Tight coupling due to shared databases leading to deployment and scaling issues (distributed monolith)

Single API Gateway becoming a bottleneck under high load

Message broker overload if event volume grows rapidly

Solutions

Adopt asynchronous communication with event-driven architecture to reduce chatty calls

Ensure each service owns its database and data model to avoid distributed monolith

Scale API Gateway horizontally with load balancers

Partition message broker topics and scale brokers horizontally

Use service mesh features like circuit breakers and retries to improve resilience

Interview Tips

Time: Spend 10 minutes understanding requirements and clarifying scope, 20 minutes designing architecture and explaining anti-patterns, 10 minutes discussing scaling and trade-offs, 5 minutes for questions

Explain the difference between a distributed monolith and a true microservices architecture

Highlight problems caused by chatty services and how asynchronous communication helps

Discuss importance of service autonomy and database ownership

Mention use of service mesh for communication reliability

Address scaling bottlenecks realistically with practical solutions