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What Is System Design?
System design is planning the architecture, components, and data flow of a scalable software system.
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AiTechWorlds
AiTechWorlds
System design is the process of architecting scalable, reliable software systems. This visual guide covers scalability, load balancing, caching, CDNs, SQL vs NoSQL, sharding, microservices, message queues, the CAP theorem, and how to approach a design interview.
System design is planning the architecture, components, and data flow of a scalable software system.
Vertical scaling adds power to one machine; horizontal scaling adds more machines.
A load balancer distributes incoming traffic across multiple servers to avoid overload.
Caching stores frequently used data in fast memory to reduce latency and database load.
A Content Delivery Network serves content from servers near the user for faster load times.
SQL is structured and relational; NoSQL is flexible and scales well for unstructured data.
Indexes speed up reads by letting the database find rows without scanning the whole table.
Sharding splits data across multiple databases to scale storage and throughput.
Replication copies data to backups so the system survives a server failure.
An API gateway is a single entry point that routes, authenticates, and rate-limits requests.
A monolith is one big app; microservices split it into small, independently deployable services.
Queues decouple services by passing messages asynchronously between them.
Rate limiting caps how many requests a client can make to protect the system from abuse.
In a network partition, you must trade off between consistency and availability.
Data becomes consistent across replicas over time, not instantly — fine for many large systems.
Use redundancy, replication, and failover so the system stays up despite failures.
Latency is time per request; throughput is requests handled per second.
A reverse proxy sits in front of servers to handle routing, TLS, caching, and security.
Clarify requirements, estimate scale, sketch components, then deep-dive and discuss tradeoffs.
Hash long URLs to short codes, store the mapping, and redirect — adding caching and scale.
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