Start with the fundamentals — scalability, load balancing, caching, SQL vs NoSQL databases, sharding, replication, message queues, and CAP theorem. Then work through 15–20 classic problems such as URL shortener, rate limiter, chat app, news feed, and ride-sharing or BookMyShow-style ticket booking. Practise the full flow out loud — requirements, estimation, API design, high-level diagram, deep dives, trade-offs — and do at least a couple of timed mock rounds with a peer or a mentor who has interviewed candidates to close communication gaps.

Never jump straight to the diagram. Clarify functional and non-functional requirements first, estimate scale (users, storage, bandwidth), define the core APIs, then draw the high-level architecture and deep-dive into two or three components the interviewer cares about, such as database choice, caching, or failure handling. Narrate your trade-offs at every step, because interviewers evaluate your reasoning far more than your final design.

The most frequent system design interview questions include designing a URL shortener, WhatsApp or Slack, an Instagram-style feed, Uber or Ola, BookMyShow, Dropbox, Twitter search, a rate limiter, and a distributed cache. Underlying concepts — consistent hashing, load balancing, caching strategies, and database sharding — repeat across almost every problem, so learn the reusable patterns instead of memorising individual solutions.

The System Design Interview book by Alex Xu (Volumes 1 and 2) is the best starting point because it walks through real interview questions step by step and teaches a repeatable framework. However, it is not sufficient on its own — supplement it with practice on problems it does not cover, and rehearse speaking your design out loud, since the interview is a two-way conversation rather than a memory test.

Grokking the System Design Interview is genuinely useful for its template-driven approach — it breaks popular questions like URL shortener, WhatsApp, and web crawler into a repeatable structure, which is ideal for a first pass over the topic. Use it to build your framework, but pair it with hands-on practice and mock rounds, because real interviewers routinely push beyond the canned solutions.

Begin by listing functional requirements and non-functional goals like scale, latency, and availability. Identify the major components — clients, load balancer, application servers, databases, caches, and queues — and map how data flows between them. Justify each decision with trade-offs (SQL vs NoSQL, push vs pull for feeds), then explain how your design behaves at 10x scale and during failures. Sketching this skeleton for well-known systems on paper makes HLD rounds feel mechanical rather than intimidating.

High level design (HLD) covers the overall architecture — components, tech stack, databases, and how services communicate. Low level design (LLD) zooms into one component and defines classes, their attributes, relationships, and design patterns — essentially a blueprint a developer could code from directly. Product companies often test both separately: HLD in system design rounds and LLD in machine-coding rounds, so preparing only one leaves a visible gap.

Low level design (LLD) is the stage where individual components of a system are designed in detail — class diagrams, object interactions, SOLID principles, and design patterns. In many Indian IT services and product companies, this detail is captured in a low level design document before coding begins, covering classes, interfaces, methods, and their relationships so the final implementation stays clean, testable, and maintainable.

If you are working out how to learn low level design, follow this sequence: first master OOP concepts and SOLID principles, then learn the widely used design patterns (Singleton, Factory, Strategy, Observer, Builder), then implement complete machine-coding problems like Parking Lot, Elevator System, Splitwise, and BookMyShow, and finally get your code reviewed and refactored. Around 6–8 weeks of consistent effort is realistic for most working engineers.

Pick one classic problem at a time — parking lot, LRU cache, vending machine, Splitwise, BookMyShow — and code it end-to-end in 60–90 minutes without looking at solutions. Afterwards, refactor using appropriate patterns and compare your version with reference implementations. Most low level design interview questions come from this well-known pool of problems, so completing 10–15 of them thoroughly beats skimming 50 superficially. A timed mock machine-coding round with an experienced engineer is the fastest way to expose gaps.

Focus on Singleton, Factory, Abstract Factory, Strategy, Observer, Builder, Decorator, and State — together these cover the vast majority of LLD scenarios. SOLID principles matter just as much, since interviewers judge whether your classes are extensible and loosely coupled. Learn each pattern by applying it inside a small working project rather than memorising definitions.

Search GitHub for curated LLD and machine-coding collections — community-maintained "awesome low level design" style repositories list problem statements along with reference solutions in Java, Python, and C++. The right way to use them is to attempt the problem yourself first, then compare your class structure and trade-offs against the solutions. Reading multiple implementations of the same problem, like Splitwise or Parking Lot, teaches you design trade-offs faster than any single solution.

Pick one language and stick to it, then build core data structures (arrays, strings, hashmaps, linked lists, stacks, trees, graphs, heaps) and algorithms (binary search, two pointers, sliding window, recursion, backtracking, dynamic programming). A realistic DSA interview preparation roadmap spans 3–4 months: fundamentals and arrays in month one, trees and graphs in month two, DP and heaps in month three, followed by revision and timed mock contests. Target 150–250 quality problems solved by pattern, not by raw count.

Choose one curated DSA interview preparation sheet and finish it completely — Blind 75 and NeetCode 150 are excellent for pattern-based learning, while Striver's SDE sheet is extremely popular among Indian students and working professionals targeting product companies. The most common mistake is collecting multiple sheets and finishing none; one completed sheet plus revision of your mistakes beats three abandoned ones.

Repeat the problem back, clarify constraints and edge cases, and state a brute-force solution with its complexity before optimising — interviewers want to hear your thought process, not watch silence. Identify the underlying pattern (sliding window, binary search on answer, DFS/BFS, DP states), explain your optimisation, code it cleanly, and dry-run against edge cases. Since most DSA interview questions are variations of 20–25 core patterns, asking yourself "which pattern is this?" works far better than trying to recall a memorised solution.