What is a System Design Interview?
Unlike coding interviews with a single correct answer, system design interviews are open-ended conversations about building scalable, reliable distributed systems.
Backend / Distributed
Design scalable services: URL shorteners, social feeds, payment systems, and real-time applications.
API Design
Define clean REST or gRPC contracts, versioning strategies, and pagination patterns.
Object-Oriented Design
Design class hierarchies, apply SOLID principles, and implement design patterns like Strategy or Observer.
Database Design
Schema design for scale - SQL vs NoSQL trade-offs, normalization vs denormalization, indexing, sharding, and replication strategies.
How Interviewers Score You
Your design is evaluated across four dimensions. Knowing the weights helps you allocate time and energy during the interview.
Problem Solving
Breaking down ambiguous requirements, asking the right clarifying questions, and structuring a coherent solution path.
Technical Design
Choosing appropriate components, data stores, protocols, and infrastructure patterns for the problem at hand.
Trade-off Analysis
Articulating the why behind every decision - consistency vs. availability, latency vs. cost, SQL vs. NoSQL.
Communication
Thinking out loud, collaborating with the interviewer, and drawing clear diagrams that tell the story of your design.
The 8-Step HLD Framework
A repeatable structure you can apply to any High-Level Design question. Follow these steps in order - skipping one is the most common reason candidates lose points.
Clarify Requirements
Gather functional requirements and non-functional constraints. Pin down SLAs, read/write ratio, and the features that actually matter before drawing anything.
Capacity Estimation
Back-of-the-envelope math: QPS, daily volume, storage, and bandwidth. Capacity numbers are often the first thing an interviewer probes - a wrong order of magnitude loses points fast.
API Design
Define endpoints and request/response contracts - REST, GraphQL, gRPC, WebSocket, or async messaging. Establish the contract before touching internals.
High-Level Design
Sketch services, load balancers, message queues, and data stores. Show the data flow end-to-end and that it handles your estimated scale.
Database Design
Choose SQL vs. NoSQL. Design schemas, define indexes, and plan sharding and replication - and justify every choice.
Deep Dive: Caching
Identify hot paths. Design read-through / write-behind caches, choose an eviction policy, and plan invalidation.
Deep Dive: Scaling
Horizontal scaling, sharding, partitioning, and the throughput bottlenecks that surface at 10x load.
Bottlenecks & Trade-offs
Name the failure modes, the monitoring and alerting you would add, and the design trade-offs you consciously accepted.
Time allocation: ~5 min requirements · ~5 min API design · ~15 min architecture + data model · remaining time on deep dives the interviewer signals interest in.
The 6-Step LLD Framework
Low-Level Design tests object-oriented thinking, not system architecture. Most candidates skip straight to class diagrams and miss 40% of the available marks.
Clarify Requirements
Define what the system must do at the class level. Identify functional scope, edge cases, and what is explicitly out of scope before touching any diagrams.
Core Entities
Surface the core domain objects - attributes, relationships, and cardinality. Getting entities right prevents redesigning your entire class hierarchy midway.
Classes & Relationships
Build class diagrams with the right abstractions: inheritance vs. composition, interfaces, and design patterns. Every structural choice is a trade-off the interviewer listens for.
Code Implementation
Implement key methods with proper error handling and SOLID principles. Getting the structure right is half the mark - implementation quality is the other half.
Edge Cases & Tests
Define the validation rules, error model, and the key test scenarios that prove the design holds. Naming the cases that break naive solutions separates senior candidates.
Extensibility & Trade-offs
Show how the design extends without modification (Open/Closed Principle) and articulate the complexity trade-offs you made.
LLD vs HLD timing: LLD rounds run 45–60 min. Spend ~5 min on requirements, ~10 min on entities, ~15 min on class design, and the remaining time writing code for the 2–3 most important methods. Code quality matters more than completeness.
8 Concepts Every Engineer Must Know
These building blocks appear in almost every system design interview. Understand them deeply - not just by name.
Load Balancing
Distributes traffic across servers using Round Robin, Least Connections, or consistent hashing. Prevents single points of failure.
Caching
In-memory stores (Redis, Memcached) reduce database load. Eviction: LRU, LFU. Invalidation: TTL, write-through, cache-aside.
CDN
Serves static assets from edge locations geographically close to users, slashing latency for media-heavy applications.
Databases
SQL for ACID transactions and relational data. NoSQL (Cassandra, DynamoDB, MongoDB) for scale, flexibility, or high write throughput.
Message Queues
Kafka and SQS decouple producers from consumers, enable async processing, and provide durability and backpressure.
Consistent Hashing
Minimal key redistribution when nodes are added or removed. Powers distributed caches and databases like DynamoDB.
Rate Limiting
Protects services from abuse with Token Bucket, Sliding Window, or Fixed Window algorithms at the API gateway.
CAP Theorem
A distributed system can guarantee only two of Consistency, Availability, Partition Tolerance at the same time.
Reference Numbers Every Engineer Must Have Cold
Interviewers expect you to reason about latency and scale without pausing to calculate. Know these numbers the same way you know your own phone number.
Latency Reference
Know these cold. Interviewers expect you to reason about latency without pausing to calculate.
Throughput Reference
Use these as sanity checks when estimating how many servers or partitions you need.
Capacity Estimation
Capacity math is often the first thing an interviewer probes. A wrong order of magnitude loses points immediately.
Estimation trick: Start from the number of users, multiply by requests/day, divide by 86,400 to get QPS. Then check whether a single server handles it or you need sharding.
Master the Key Trade-offs
Interviewers are evaluating your judgment - not your ability to pick the 'right' answer. Show you understand the implications of each choice.
CP systems (Zookeeper, HBase) sacrifice availability during partitions. AP systems (Cassandra, DynamoDB) allow stale reads to stay up.
SQL gives ACID guarantees and relational modeling. NoSQL trades joins for horizontal scale, schema flexibility, and write throughput.
Monoliths are simple to develop and deploy early on. Microservices enable independent scaling and deployment but add operational overhead.
Sync calls are simple but create tight coupling and cascade failures. Async (queues, events) improves resilience and throughput.
Read-heavy systems benefit from replicas and caching. Write-heavy systems need partitioning, LSM trees, and eventual consistency.
Normalized schemas reduce redundancy and anomalies. Denormalization improves query performance by trading storage for joins.
5 Mistakes That Cost Engineers the Offer
These are easy to make and costly to recover from in a 45-minute session. Know them so you catch yourself in real time.
Jumping to Solutions
Starting to draw architecture before asking clarifying questions. Interviewers want to see how you scope problems first.
Buzzword Overload
Dropping Kafka, Kubernetes, and Redis without justifying why. Every component must earn its place in the design.
Ignoring Bottlenecks
Not identifying where the system will break at scale. Always estimate QPS and work backwards to capacity requirements.
Single Points of Failure
Designing without redundancy. Every layer needs failover thinking: replication, health checks, auto-scaling.
Going Silent
Not thinking out loud. Interviewers want to follow your reasoning. Narrate your decisions even when uncertain.
Expectations by Interview Level
The bar shifts significantly between levels. Know exactly what is expected at your target level - the difference between L5 and L6 is not more knowledge, it is more ownership.
Mid-level Engineer
- Design a system you have worked on before with minimal guidance
- Identify the main components and data flows correctly
- Basic trade-off awareness (SQL vs NoSQL, sync vs async)
- Reasonable non-functional requirement estimates (QPS, storage)
Senior Engineer
- Handle ambiguity and drive requirements gathering independently
- Deep-dive on at least one component (caching, DB sharding, queuing)
- Proactively identify failure modes and design for resilience
- Articulate multiple valid approaches and justify the chosen one
Staff / Principal Engineer
- Drive the entire design space with minimal interviewer prompting
- Reason about cross-cutting concerns: security, compliance, cost
- Demonstrate awareness of org-level constraints and team topology
- Surface second-order effects: data migration, versioning, rollouts
The 4-Week System Design Study Plan
Most engineers over-study concepts and under-practise execution. This plan is structured around the opposite - concepts first, then deliberate practice under real conditions.
Build the Foundation
No practice questions yet. Learn the framework and concepts deeply first.
- Internalise the 8-step HLD framework - write it out from memory daily
- Study all 8 core concepts: caching, load balancing, queues, consistent hashing, CAP, CDN, databases, rate limiting
- Memorise the latency and capacity reference numbers on this page
- Read 2 real engineering blogs from the curated index - Netflix, Instagram scaling, or Uber dispatch are great starts
First Practice Round
Start with Easy questions. Focus on following the framework, not on getting it perfect.
- Complete 3 Easy HLD questions with a strict 35-minute timer
- Review AI feedback after each session - identify 1 recurring gap
- Deep-dive that gap: read about it, then do 1 more targeted session
- Complete 2 LLD questions using the 6-step LLD framework
Go Deeper on Trade-offs
Medium questions expose gaps in your reasoning that easy questions do not.
- Complete 4 Medium HLD questions - focus on trade-off explanations, not just the diagram
- Run 1 mock interview in the AlgoInsight Interview Portal
- Review level expectations for your target role (L4/L5/L6)
- Practise explaining the WHY for every component - say it out loud
Pressure Test & Close Gaps
Hard questions and mock interviews reveal what weekly practice hides.
- Complete 2 Hard HLD questions and compare your design against model answers
- Run 2 mock interviews back-to-back to simulate a real interview day
- Find the step where your AI scores are consistently lowest - do 3 targeted sessions on it
- Write your personal cheat sheet: key numbers, framework steps, and 3 trade-offs you explain well
Track your progress: After each AlgoInsight session the AI gives you a score per step. Use those scores - not self-assessment - to decide where to focus next.
Further reading: Browse the Engineering Blog Index — 450+ posts from Netflix, Uber, Stripe, Razorpay and 50+ more, filterable by topic. The single best source of system-design intuition.
Top FAANG System Design Questions
The most frequently asked questions at top tech companies, grouped by difficulty. Start with Easy, build confidence, then move to Hard under a timer.
- URL Shortener (TinyURL)
- Key-Value Store
- Rate Limiter
- Unique ID Generator
- Twitter / Social Media Feed
- Chat Application (WhatsApp)
- Notification Service
- File Storage (Dropbox)
- Web Crawler
- YouTube / Video Streaming
- Uber / Ride Sharing
- Google Typeahead
- Payment Gateway
- Distributed Task Scheduler
Architecture Canvas - your interview whiteboard
The diagram is half your answer in an HLD round. Architecture Canvas is the freeform whiteboard built for exactly that - free with your account, syncs across devices.
System-design shapes
Load balancer, API gateway, queue, cache, CDN, microservice, lambda, S3 - drag straight from the palette. No generic boxes pretending to be infra.
Quick-connect edges
Four handles per shape. Drag from any one to start an arrow. Dashed for a fallback path, animated for streams, recoloured to mark a hot codepath.
Auto-save + cloud sync
Every edit syncs to your account. Sketched on a laptop, finished on a tablet, glanced at on a phone before the interview. No save button.
Import & export Mermaid
Paste any Mermaid flowchart and the editor parses it onto the canvas as editable shapes. Export back to Mermaid for PR descriptions or PNG for docs.
Highlighter + laser pointer
Highlight the hot path while walking through the design. Laser pointer for live screen shares so the interviewer follows what you're pointing at.
Built for screen-share interviews
Nodes stay legible when projected to a Zoom share. Inline label editing means you can rename a box mid-sentence without breaking eye contact.
When to reach for it: The moment you finish Step 1 (clarify requirements) and start Step 4 (high-level design), the Canvas is where the picture goes. Treat it as the visible artifact of your thinking — interviewers grade what they can see.
Frequently Asked Questions
Answers to the questions candidates ask most often about system design interviews.
You've Read the Guide. Now Build the Skill.
Understanding the framework is not the same as executing it under a 45-minute clock with an AI evaluating every trade-off. AlgoInsight's AI-graded simulations put you inside a real interview - timed, step-by-step, with personalised feedback on every decision.