System design involves creating the architecture of a system to meet specific requirements. It includes defining components, their interactions, scalability, and fault tolerance. A system designer needs to consider aspects like high availability, performance, maintainability, and security. In interviews, you're typically asked to design large-scale, real-world systems, such as an e-commerce platform, search engine, or social network.

The process involves gathering requirements, breaking down the system into components, choosing appropriate databases, designing APIs, and considering scaling and optimization techniques. Key goals are creating efficient, reliable, and scalable systems that can handle traffic growth and deliver a good user experience.

• Requirements gathering: Understanding functional and non-functional requirements, such as user stories and performance constraints.Architecture: Choosing the right architecture (e.g., monolithic vs. microservices).
• Databases: Deciding between SQL vs. NoSQL and modeling data.
• APIs: Designing communication between components.
• Caching: Implementing caching mechanisms for fast data retrieval.
• Load balancing: Distributing traffic evenly across servers.
• Scalability: Ensuring the system can handle increased load.

• User management: User authentication (OAuth, JWT) and authorization.
• Product catalog: A database for product information (SQL/NoSQL).
• Order management: Handling orders and payments with transactional integrity.
• Search functionality: Using a search engine (e.g., Elasticsearch) for fast querying.
• Cart management: Temporary storage (e.g., Redis) to hold items before checkout.

Vertical scaling: Increasing the power of a single machine (CPU, RAM), but it has limitations.Horizontal scaling: Adding more machines to distribute the load, offering greater flexibility.

Load balancing: Distributing traffic across multiple servers to avoid overloading any one server.Sharding: Splitting data into smaller chunks distributed across different servers.Caching: Using systems like Redis to reduce database load.Microservices architecture: Breaking down the system into smaller, independently scalable services.

 Load balancing is the process of distributing incoming network traffic across multiple servers to ensure no single server becomes overwhelmed, improving system performance and availability. It can be done via hardware or software-based load balancers. Round-robin is the simplest method, where each request is sent to the next server in line.

Least connections sends requests to the server with the least active connections. IP Hash routes requests based on the client’s IP address. Load balancing ensures high availability by detecting server failures and rerouting traffic to healthy servers. Common tools include AWS Elastic Load Balancer, HAProxy, and NGINX.