项目介绍

arpitbbhayani/system-design-questions 是一个托管在 GitHub 上的开源项目,主要使用 Python 编写,目前获得 3.2k 个 Star、650 次 Fork。

仓库全名
arpitbbhayani/system-design-questions
Star 数
3.2k
Fork 数
650
未关闭 Issue
3

README 摘要

System Design Questions === The repository contains a set of problem statements around Software Architecture and System Design as conducted by Arpit's System Design Masterclass. Questions Design a Blogging Platform Design Online Offline Indicator Design Airline Check-in Design SQL backed KV Store Design Slack's Realtime Communication - NEW Design a Load Balancer Design Synchronized Queue Consumers Design an Image…

完整内容见 GitHub 原始 README 或本页 。

常见问题

system-design-questions 用什么语言开发?

主要使用 Python 编写,目前有 3.2k 个 Star。

如何获取 system-design-questions 的源码?

可以直接克隆仓库:git clone https://github.com/arpitbbhayani/system-design-questions.git,默认分支为 master;安装与运行步骤见仓库 README。

system-design-questions 最近还在维护吗?

仓库最近一次更新为 7月14日,当前有 3 个未关闭 Issue;Star 数为 3.2k,可作为社区活跃度的参考。

语言占比

Python
Shell

贡献者

README

System Design Questions

The repository contains a set of problem statements around Software Architecture and System Design as conducted by Arpit’s System Design Masterclass.

Questions


Arpit’s System Design Masterclass

A no-fluff and highly practical masterclass that reignites engineering curiosity and helps SDE-2, SDE-3, and above become great at designing, implementing, and shipping scalable, fault-tolerant, and highly available systems at the workplace.

Key Details

  • Every single system will be ideated, brainstormed, and designed practically
  • The design will be how similar systems are actually built in production
  • We will cover key implementation details and prototype every single system discussed
  • Sessions are brainstorming-heavy and we naturally evolve our solution instead of going from question to answer
  • We discuss all possible trade-offs and understand the right intuition for opting a trade-off over another
  • Sessions go on for a minimum 3 hours and do not end until every single question is answered
  • You will have lifetime access to the recordings irrespective of which course you choose
  • The course is language agnostic, the prototypes will be in Go, but nothing very Go specific required to get the most out of it.

Hey, I am Arpit

engineering, databases, and systems. always building.

I am a software engineer and engineering leader passionate about applied AI and databases. Currently, I am a Principal Engineer II at Razorpay, working at the intersection of Data and AI, where I am building Agent Studio, which enables merchants to create AI agents while we provide the infrastructure and harness to run them reliably. I am also working on the Customer Data Platform and leading Merchant Developer Experience.

I am also building px0.ai, an open-source prompt infrastructure toolkit that lets you version, update, and govern prompts in production, eliminating the need to hardcode prompts or redeploy your application for prompt changes.

Previously, I was a Staff Engineer at Google, where I worked on GCP Memorystore and GCP Dataproc. On the side, I am building - DiceDB, a fork of Valkey with multi-tiering and query subscriptions. I also spend time on independent research, publishing my work on ArXiv. My areas of interest include databases, approximate algorithms, and distributed systems.

In 2024, I took a leap of faith and co-founded Profile.fyi, which was later acquired by Mercor. I was part of Amazon’s Fast Data Team, where I worked on cold tiering of hot data and developed a seamless query interface across all storage tiers.

I held engineering leadership positions (both IC and management) at Unacademy, where I built, grew, and led Search, Site Reliability Engineering (SRE) teams, and Data Engineering teams. I hold a total of 12+ years of experience in scaling backend services, taking products and teams from 0 to 1, and beyond.

I keep diving deep into engineering details and share my learnings through 166+ blogs, socials and, 250+ no-fluff engineering videos on YouTube, breaking down System Design, Database Internals, Microservices, BitTorrent Internals, Redis Internals, Research Papers, and the trade-offs behind real-world production systems.

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