40 System Design Concepts Everyone Should Know
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- Ram Simran G
- twitter @rgarimella0124
Hi there! 👋 I’m someone who’s spent the last 3 years working with 3 different startups, building products, solving problems, and learning a lot about system design. In startups, you don’t always have the luxury of big teams or endless resources — you learn by doing, and quickly! Along the way, I picked up some essential concepts that helped me design better, scalable systems.
Today, I’m sharing 40 important system design concepts with easy explanations and links to detailed blogs you can check out. If you’re just getting started or looking to strengthen your basics, this is for you!
Content Delivery Network (CDN) — Delivers content quickly to users by using servers close to them.
👉 Read hereCaching — Storing frequently accessed data so it’s faster to fetch next time.
👉 Read hereDistributed Caching — Caching across multiple servers to handle big traffic.
👉 Read hereLatency vs Throughput — Latency is delay; throughput is how much work is done in a time frame.
👉 Read hereCAP Theorem — A system can only guarantee two of Consistency, Availability, and Partition Tolerance.
👉 Read hereLoad Balancing — Distributing traffic across multiple servers so no single one is overloaded.
👉 Read hereACID Transactions — Guarantees for database operations (Atomicity, Consistency, Isolation, Durability).
👉 Read hereSQL vs NoSQL — Structured (SQL) vs flexible (NoSQL) databases.
👉 Read hereConsistent Hashing — A technique to evenly distribute data when adding/removing servers.
👉 Read hereDatabase Index — Makes searching data faster, like a book index.
👉 Read hereRate Limiting — Controls how many requests a user/system can make in a time frame.
👉 Read hereMicroservices Architecture — Breaking applications into smaller, independent services.
👉 Read hereStrong vs Eventual Consistency — Immediate vs delayed correctness of data across systems.
👉 Read hereREST vs RPC — Two ways services communicate; REST uses URLs, RPC is direct function calling.
👉 Read hereBatch Processing vs Stream Processing — Batch processes data in chunks, stream processes continuously.
👉 Read hereHeartBeat — A signal sent regularly to check if a service/server is alive.
👉 Read hereCircuit Breaker — Stops making requests to a failing service to prevent system crash.
👉 Read hereIdempotency — Making sure doing the same operation multiple times has the same effect.
👉 Read hereDatabase Scaling — Making databases handle more traffic by scaling up or out.
👉 Read hereData Replication — Copying data across servers for backup or faster access.
👉 Read hereData Redundancy — Storing extra copies of data to avoid loss.
👉 Read hereDatabase Sharding — Splitting a big database into smaller, manageable pieces.
👉 Read hereProxy Server — A middleman between the client and server, often for security or load balancing.
👉 Read hereDomain Name System (DNS) — Converts website names into IP addresses computers understand.
👉 Read hereMessage Queues — Hold messages until the receiving service is ready to process them.
👉 Read hereWebSockets — A way to have real-time two-way communication between client and server.
👉 Read hereConsensus Algorithms — Make sure all servers in a distributed system agree on the same data.
👉 Read hereFault Tolerance — The ability of a system to keep working even if part of it fails.
👉 Read hereFailover — Automatically switching to a backup system when the main one fails.
👉 Read hereGossip Protocol — A way systems share state or data updates, like gossip spreading among people.
👉 Read hereAPI Gateway — A single entry point for APIs, handling routing, security, and rate limiting.
👉 Read hereDistributed Locking — Prevents multiple services from changing the same data at the same time.
👉 Read hereDistributed Tracing — Helps track requests as they move through multiple services.
👉 Read hereBloom Filters — A space-efficient way to test if an element is in a set (with some chance of false positives).
👉 Read hereChecksum — A value used to check data integrity after transfer or storage.
👉 Read hereAPI Design — The process of designing clean, scalable, and easy-to-use APIs.
👉 Read hereServerless Architecture — Running code without managing servers — the cloud provider takes care of that.
👉 Read hereConcurrency vs Parallelism — Concurrency handles many tasks at once, parallelism does them literally at the same time.
👉 Read hereDisaster Recovery — Strategies to recover from failures, disasters, or data loss.
👉 Read hereService Discovery — How services find and connect to each other in a system.
👉 Read here
✨ Final Thoughts
System design can seem overwhelming at first, but once you break it down, it becomes manageable — especially when you’ve got good resources like these. I’ve personally learned a lot through real-world problems at startups, where systems need to scale, stay online, and be built quickly.
If you’re starting your system design journey — start small, be curious, and bookmark this list!
Cheers,
Sim