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How I'd Prepare for a System Design Interview if I Were Starting From Scratch

By Evan King

May 15, 2025

You just got an email from your dream company—an interview scheduled for a month from today. While you know how to prepare for coding interviews (hello, LeetCode), the looming system design interview has you nervous.

Maybe you're a mid-level engineer facing your first system-design challenge, or perhaps you're a senior who's been out of the interview circuit for a while. You've worked at big companies, but only ever focused on your narrow part of the system. The more you read online, the more overwhelming it seems.

Take a deep breath, you're not alone. As someone who has conducted 500+ system-design interviews, I can tell you that this anxiety melts away once you have a clear plan.

The Four-Step Preparation Plan

Understand what the system design interview is assessing
Refresh the fundamentals
Master the building blocks
Work backwards from common problems

Let's break down each step.

1. What is the System Design Interview?

A system-design interview evaluates your ability to architect complex, scalable systems that solve real-world problems. Unlike coding interviews that test algorithms, system design assesses:

Technical breadth
Communication clarity
Decision-making & trade-offs

Your interviewer isn't looking for a perfect answer (there usually isn't one!). They want to see how you frame ambiguous problems, reason about trade-offs, and think about scalability & performance.

There are a few flavors of system design:

Flavour	Example Question
Product Design	"Design Uber's backend"
Infrastructure Design	"Design a rate-limiter"
Object-Oriented Design	"Design a parking-lot system"
Frontend Design	"Design a spreadsheet app"

This guide focuses on the first two – Product and Infrastructure – which account for the vast majority of interviews.

Across companies, you're judged on permutations of the same four axes:

Problem Solving – How well you identify, understand, and prioritize the core challenges in a system.
Solution Design – Your ability to create scalable architectures while balancing performance, maintainability, and cost trade-offs.
Technical Excellence – Your depth of technical knowledge and mastery of relevant tools and best practices.
Communication – How clearly you explain complex technical concepts and design decisions to various stakeholders.

If you need a structure for the actual interview, follow our Delivery Framework so you stay focused and on-track.

2. Refresh the Fundamentals

Before diving into complex system design, you need to master certain fundamentals. Most online guides will overwhelm you with endless lists of rarely used theorems or algorithms, but here's what actually matters to build a solid foundation:

Storage Fundamentals

You should be able to discuss various data storage models and their appropriate use cases. Be prepared to explain how data is organized in relational databases (normalized tables with relationships) versus document stores (nested JSON-like structures), and key-value stores (simple lookup mechanisms). Your interviewer will expect you to understand ACID properties for transactional systems versus BASE principles for distributed databases, and to articulate when each storage paradigm makes sense based on access patterns and consistency requirements.

Scalability Fundamentals

You should be comfortable explaining both vertical scaling (beefier machines) and horizontal scaling (more machines) approaches. Be ready to discuss read/write segregation strategies and how they optimize different workloads. Your knowledge should include partitioning/sharding techniques for distributing data effectively across nodes. When the "celebrity problem" (handling hotspots) comes up, you'll want to articulate solutions clearly. Load balancing algorithms and consistent hashing techniques should be in your toolkit for distributing traffic and data efficiently.

Networking Essentials

You should be conversant in HTTP/HTTPS protocols, TCP/UDP differences, DNS resolution, and API design principles. Expect to discuss the request-response lifecycle and common network topologies. Your interviewer will appreciate it when you can clearly differentiate between REST, GraphQL, gRPC, and understand the role Websockets and SSE play in real-time communication systems.

Latency, Throughput & Capacity Planning

You should be able to recall approximate latency numbers for common operations (memory access, disk reads, network calls). When discussing system requirements, demonstrate your ability to understand throughput limitations and perform basic capacity planning calculations. Be prepared to identify potential performance bottlenecks and propose solutions across a distributed architecture, ie. caching, sharding writes, etc.

Fault Tolerance & Redundancy

You should recognize and communicate that failures are inevitable in distributed systems. Be ready to discuss replication strategies and failure detection mechanisms. Your design should incorporate redundancy at appropriate levels (server, rack, datacenter) and be able to recover from failures gracefully.

CAP Theorem (Consistency vs. Availability)

You should be able to explain the fundamental trade-offs between Consistency, Availability, and Partition tolerance in distributed systems. When discussing database technologies, demonstrate your ability to classify them according to CAP characteristics and articulate which properties to prioritize based on specific business requirements and use cases. To make this simpler, given partition tolerance is a must, you just need to be able to decide whether your system needs strong consistency (like ticketbooking or banking apps) or whether eventual consistency is fine (everything else).

3. Understand the Building Blocks

Think of system design as Lego® for engineers – you just need to know which pieces exists. There are a lot of components and technologies out there, but these 7 will get you 90% of the way to solving just about any problem.

Components

Building Block	Purpose
Server / Compute	Executes business logic (monolith, microservice, serverless)
Database	Persists structured data (relational, document, key-value, column)
Cache	Speed layer (Redis/Memcached) with cache-aside, read-through, write-through patterns
Message Queue	Async communication & back-pressure (Kafka, RabbitMQ, SQS)
Load Balancer	Distributes traffic (round-robin, least-conn, consistent hashing)
Blob Storage	Unstructured objects (S3, GCS) with lifecycle policies
CDN	Edge caching to cut latency and protect origin

Master the pros/cons and common failure modes of each.

4. Work Backwards from Common Problems

With the fundamentals in place, you should work bottom-up from common problems. The key is to not passively consume content though. Watching videos and reading breakdowns will only get you so far.

Each time you come across a concept you don't know, dig deeper, fan out and ask ChatGPT, Google, etc. to close the gap. Once you've done the first 3-4 problems, then start to try them on your own before jumping to reading a solution.

This tests your ability to apply theoretical knowledge to practical scenarios, identify bottlenecks, and make reasonable trade-offs under constraints. It also reveals gaps in your understanding that you might not discover through passive learning.

The 10 problems we recommend, in order, are:

Design a URL Shortener (Bitly) - Tests your understanding of hashing, databases, and caching.
Design Dropbox - Tests file storage, synchronization, and metadata management.
Design Ticketmaster - Tests concurrency, race conditions, and transactional integrity.
Design a News Feed - Tests content delivery, personalization, and real-time updates.
Design WhatsApp - Tests real-time communication, presence detection, and message delivery.
Design LeetCode - Tests code execution environments, scaling compute, and security.
Design Uber - Tests geospatial indexing, matching algorithms, and real-time updates.
Design a Web Crawler - Tests distributed systems, scheduling, and politeness policies.
Design an Ad Click Aggregator - Tests high-throughput event processing and analytics.
Design Facebook's Post Search - Tests indexing, ranking, and search optimization.

For Hello Interview Premium users, I highly recommend practicing each of these problems yourself with our interactive Guided Practice. If you don’t have Premium, no sweat, open up an Excalidraw whiteboard and start a timer, working through each problem on your own. While you won’t get the benefit of instant feedback, you can still read the breakdowns or watch the videos afterward to see where you might have made missteps.

As you work through these problems, you'll start to notice patterns emerge. By the time you've solved 5-6 design challenges, things will begin to feel more intuitive, and you'll quickly recognize which components and approaches fit specific scenarios. System design interviews, much like data structures and algorithms questions, ultimately test your ability to recognize problem patterns and apply appropriate solutions. Each new challenge is rarely completely novel, it's typically a recombination of familiar elements with specific constraints and trade-offs that you'll become increasingly comfortable navigating. It just takes repetition.

Lastly, consider scheduling mock interviews to test your knowledge in a realistic setting. Feedback from candidates consistently shows that practice interviews are often the catalyst that makes theoretical knowledge click in practical application. The opportunity to receive real-time feedback from experienced interviewers can reveal blind spots in your preparation that might otherwise go unnoticed until your actual interview.

Most importantly, good luck! It’s a grind, but you’ve got this!

About The Author

Evan, Co-founder of Hello Interview and former Staff engineer at Meta, possesses a unique vantage point having been on both sides of the tech hiring process. With a track record of conducting hundreds of interviews and securing offers from top tech companies himself, he is now on a mission to help others do the same.

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