System Design Mastery

Buffered, Eventually is a system design podcast where two senior engineers break down how large-scale video platforms like YouTube are built—and the tradeoffs behind every layer.We discuss video upload pipelines, transcoding, storage, CDN delivery, feed and search indexing, recommendations, and view counting at scale. Each episode focuses on real-world constraints: latency vs quality, cost vs reliability, and consistency in systems that serve billions of hours of video.No hype, no buzzwords—just practical conversations about designing massive media systems.

Indexed, Eventually is a system design podcast where two senior engineers break down how large-scale post search systems are built—and where they break first.Using a Facebook-style post search as a running example, we dive into inverted indexes, write-heavy ingestion, ranking by likes vs recency, caching strategies, and the tradeoffs between freshness, cost, and performance. We talk through real constraints: high write volume, massive storage, hot vs cold data, and why “just sort at query time” never works.No buzzwords—just practical design decisions and honest tradeoffs.

Feed Meets Telemetry is a system design podcast where two senior engineers break down how fitness platforms like Strava are built—and the tradeoffs behind every design choice.We talk about activity tracking, GPS ingestion, real-time sync, feed generation, leaderboards, data accuracy, and scalability. No hype, no buzzwords—just clear conversations about designing large-scale fitness and activity systems.

Nearest cab is a system design podcast where two senior engineers break down how ride-hailing platforms like Uber are built—and the tradeoffs behind every decision.We discuss real-time matching, geo-indexing, dispatch algorithms, pricing, reliability, and scalability under extreme load. Each episode focuses on practical design choices, constraints, and failure scenarios drawn from real production systems.No hype, no theory dumps—just clear conversations about building large-scale, real-time systems.

Verified Review is a system design podcast where two senior engineers break down how local business review platforms are built—and the tradeoffs behind every design choice.The conversations are practical and experience-driven, focusing on real-world constraints rather than idealized solutions. No buzzwords, no hype—just clear explanations of complex systems and the tradeoffs engineers make when building review platforms used by millions.If you want to understand how reputation and review systems work under the hood, this podcast is for you.

A system design podcast where two senior engineers break down how messaging platforms like WhatsApp are built at scale—and the tradeoffs behind every architectural choice.We discuss core problems such as real-time messaging, message delivery guarantees, end-to-end encryption, scalability, latency, storage, and reliability. Each episode focuses on why certain decisions are made, what alternatives exist, and what you gain or lose with each approach.The conversations are practical and experience-driven—no fluff, no theory dumps. Just clear explanations of complex systems, real-world constraints, and the design tradeoffs that matter in production.If you want to understand how large-scale messaging systems work under the hood, this podcast is for you.

The Scroll is a system design podcast where two senior engineers break down how real-world systems are built—and the tradeoffs behind every decision. From news-feed architectures and recommendation systems to scalability, performance, and reliability, we talk through what actually works in production and why.If you’re an engineer who enjoys understanding how systems really work, this podcast is for you.

That price-drop alert didn’t come from vibes.This episode explains how price tracking systems like CamelCamelCamel work — from crawling and deduping product data to alerting users at scale — in a chill, no-textbook system design walkthrough.

That feed refresh is doing a lot of work.This episode breaks down how Instagram’s system design handles uploads, timelines, likes, and massive traffic — explained in a chill, no-textbook way.

That comment flying up the screen didn’t just magically appear.This episode explains how Facebook Live-style comment systems work — handling real-time writes, massive fanout, and ordering — all without killing latency.

Not every request deserves to get through.This episode explains how distributed rate limiters work — how systems track requests, stay consistent across nodes, and fail gracefully — all in a clean, no-overengineering system design walkthrough

That headline didn’t just show up by accident.In this episode, we explore how news aggregators like Google News work under the hood — from content ingestion and deduplication to ranking, freshness, and user personalization — all explained without corporate jargon

You solve the problems — but how does the platform work?This episode explores the system design behind a LeetCode-style platform, covering code execution, problem storage, user submissions, scaling, and reliability, all explained without the boring textbook energy.

In this episode, we break down how modern file storage systems like Dropbox and Google Drive work — from syncing and version control to scalability and reliability — in a way that doesn’t feel like a lecture. Real systems, real problems, zero boring slides.

Ever typed in Google Docs and watched someone else edit mid-sentence? We unpack the real-time magic behind collaborative editing—OT vs CRDTs, syncing state, conflict resolution, and how Docs stays smooth even when your group project is not.

YouTube’s recommendation engine works overtime to find your personal top picks. We explore how it filters candidates, scores them, and ranks the winners—kind of like a talent show, but with neural networks and way less singing.

Why does a simple “Buy Now” click trigger a whole fintech orchestra? We unpack the tech behind modern payment gateways—auth flows, settlement, risk checks, and the whole vibe. Secure payments, but make it digestible.

Ever wondered how websites get scraped, indexed, and turned into searchable magic? We break down web crawlers—how they think, how they roam, and why they occasionally break the internet. System design made fun, chaotic, and actually understandable.

YouTube’s recommendation engine is basically that friend who gets you. But how does it work? We decode the machine-learning magic, the watch-time traps, and the wild design behind what you click next. Nerdy, relatable, and dangerously bingeable.

Welcome to Cache Me If You Can, the podcast where we break down the chaotic, beautiful world of distributed caching—no gatekeeping, no buzzword soup. Just real talk about scaling apps, avoiding outages, and surviving the latency monster. If you’re a dev, an architect, or just cache-curious, this pod’s for you.