# Client–Server Model, Stateless & Stateful Servers *A System Design Deep Dive* --- ## 1. Client–Server Model Overview The **Client–Server Model** is the foundational interaction pattern of modern computing systems. It defines how responsibilities are split between: - **Clients**: Initiators of requests - **Servers**: Providers of resources, services, or computation This model underpins: - Web applications - APIs - Distributed systems - Cloud services - Blockchain RPC nodes --- ## 2. Client Responsibilities Clients are typically responsible for: - Initiating requests - Providing user input - Rendering responses - Managing UI/UX state - Handling retries and timeouts Examples: - Browsers - Mobile apps - CLI tools - Smart contract clients --- ## 3. Server Responsibilities Servers handle: - Business logic - Data processing - Authentication & authorization - Persistence and state management - Scalability and availability concerns Servers are designed to be: - Concurrent - Fault-tolerant - Secure - Observable --- ## 4. What Is Server State? **State** refers to any data that a server must remember about a client across multiple requests. Examples: - User login sessions - Shopping carts - In-progress workflows - Connection-specific data How this state is handled defines whether a system is **stateful** or **stateless**. --- ## 5. Stateless Servers ### Definition A **stateless server** does not retain any client-specific state between requests. Each request is treated as **independent and complete**. All information required to process a request is included in the request itself. --- ### Characteristics - No session memory on the server - Easy horizontal scaling - Requests can hit any server instance - Simpler failure recovery --- ### Example ```text Client → Server Authorization: Bearer JWT Request Payload: Complete ``` The server validates the token, processes the request, and forgets the client afterward. ## Advantages - High scalability - Load balancer friendly - Easier fault tolerance - Ideal for microservices - Cloud-native by default ## Trade-offs - Larger request payloads - More work pushed to the client - Cryptographic overhead (JWT verification, signatures) - Harder to implement complex workflows # 6. Stateful Servers ## Definition A stateful server retains client-specific state across multiple requests. Subsequent requests depend on previously stored information. ## Characteristics - Server remembers session context - Client must reconnect to the same server - Often uses sticky sessions ### Example ``` Client → Server Session ID: 12345 ``` Server retrieves user context from memory or local storage. ## Advantages - Simpler application logic - Reduced payload size - Easier to implement multi-step flows - Lower cryptographic overhead ## Trade-offs - Poor horizontal scalability - Complex failover handling - Sticky load balancing - Higher availability risk # 7. Stateless vs Stateful Comparison | Dimension | Stateless | Stateful | | ------------------- | ------------ | --------------- | | Scalability | Excellent | Limited | | Fault Tolerance | High | Lower | | Load Balancing | Simple | Sticky sessions | | Complexity | Client-heavy | Server-heavy | | Cloud Native | Yes | No | | Cryptographic Usage | High | Low | # 8. Hybrid Approaches (Most Real Systems) Most production systems use hybrid designs: - Stateless application servers - Externalized state storage (Redis, DB, object storage) This pattern enables: - Horizontal scaling - Shared state - Controlled consistency # 9. Cryptography & Stateless Systems Stateless architectures often rely heavily on cryptography: - JWTs - HMAC signatures - Public-key verification - Token expiration and rotation This introduces: - Trust models - Replay protection - Token invalidation challenges # 10. Why This Matters in System Design Choosing stateless vs stateful impacts: - Cost - Latency - Availability - Security - Operational complexity There is no universally “correct” choice—only trade-offs. # Key Takeaways - Client–Server is the foundation of modern systems - Stateless servers scale better - Stateful servers simplify logic - Hybrid models dominate real-world architectures - Good system design starts with understanding state State management is where most systems either scale—or fail.