Kotlin System Design Basics Tutorial: REST API Design, Microservices, Authentication, and Caching Strategies

This Kotlin System Design tutorial covers the fundamentals of designing scalable and maintainable systems. It includes REST API design principles, an overview of microservices, authentication and authorization strategies, and caching techniques. The chapter provides practical guidance for Kotlin backend development and high-level system architecture understanding.

System Design Basics (Complete Tutorial)

REST API Design

REST APIs allow clients to interact with the server using standard HTTP methods.

Key Principles

  1. Resource-based URLs: /users, /orders
  2. HTTP Methods:
  3. GET: fetch data
  4. POST: create resource
  5. PUT/PATCH: update resource
  6. DELETE: remove resource
  7. Stateless: Each request contains all necessary information
  8. Versioning: /api/v1/users

Example in Ktor


routing {
route("/api/v1/users") {
get { call.respond(listOf("User1", "User2")) }
post { call.respondText("User created") }
}
}

Best Practices

  1. Keep endpoints intuitive
  2. Return proper HTTP status codes
  3. Include meaningful error messages

Microservices Overview

Microservices architecture divides applications into small, independent services.

Characteristics

  1. Each service is autonomous
  2. Services communicate via HTTP/REST, gRPC, or message queues
  3. Easy to scale and deploy independently

Advantages

  1. Scalability
  2. Fault isolation
  3. Technology flexibility

Example Kotlin Stack

  1. Ktor or Spring Boot services
  2. REST APIs for communication
  3. Shared database avoided (use event-driven patterns)

Best Practices

  1. Keep services small and focused
  2. Use API gateways for routing
  3. Implement service discovery

Authentication and Authorization

Authentication

Verifies user identity.

Example: JWT


val token = JwtConfig.generateToken("user123")

Authorization

Controls access to resources.

Role-Based Access Example


fun hasAccess(user: User, resource: Resource): Boolean =
user.role == Role.ADMIN

Best Practices

  1. Use JWT for stateless authentication
  2. Use OAuth2/OpenID Connect for modern systems
  3. Never store sensitive data in JWT payload

Caching Strategies

Caching improves performance by storing frequently accessed data.

Common Strategies

  1. In-Memory Caching: Using ConcurrentHashMap or Caffeine
  2. Distributed Caching: Redis, Memcached
  3. HTTP Caching: Cache-Control headers

Example: Ktor with Caffeine


val cache = Caffeine.newBuilder()
.expireAfterWrite(10, TimeUnit.MINUTES)
.maximumSize(100)
.build<String, User>()

Best Practices

  1. Cache read-heavy, rarely changing data
  2. Use proper TTL (time-to-live)
  3. Avoid caching sensitive data directly

System Design Best Practices

  1. Design APIs first (contract-driven)
  2. Use microservices for large systems
  3. Secure endpoints with authentication and authorization
  4. Optimize performance using caching
  5. Monitor and log all services

Summary

This chapter covered system design basics for Kotlin developers, including REST API design, microservices overview, authentication and authorization, and caching strategies. These fundamentals are critical for building scalable, secure, and maintainable Kotlin backend systems.