System Design
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Mon, Oct 19
10 items found
Stop Rambling in System Design Interviews — 3 Frameworks That Fix It
The RADIO Framework: How to Structure Any System Design Interview Answer Writing good code alone doesn't clear Senior SDE / IC-level system design rounds anymore. What separates strong candidates from everyone else isn't raw knowledge of architectures — it's the ability to think out loud in a structured way under pressure. A few hard truths about system design rounds: you can't walk in and improvise, hoping structure will emerge on its own. You can't rely on your resume or past projects to...
From AI Agent Demos to Production: 6 Essential Concepts for Agentic AI System Design
Building an AI agent demo is easy. Building one that is reliable, scalable, secure, and production-ready is much harder. I recently watched Agentic AI System Design was HARD until I Learned these 6 Concepts and summarized six important concepts for designing production AI agents. Let's use a customer support agent as an example. Imagine a customer asking: "I never received my order. Please cancel it and refund me." The agent needs to understand the request, retrieve the order, check ref...
Share a Kafka Topic Only When Order Matters
We merged Kafka topics because the same services consumed the messages together. It felt simpler. Two incidents showed what we had really done: one shared topic means one shared queue, one failure domain, and one on-call problem—not a tidy folder in a repo. My default rule: share a topic only when order matters for a clear stream (same partition key, same lifecycle). If urgency, retries, batch vs live traffic, or ownership differ, split the topics. Below I explain why we merged, what broke i...
YouTube System Design: Upload, Transcoding, CDN & Video Streaming
YouTube System Design: From Video Upload to Global Playback A viewer presses Play. A few seconds later, video is streaming smoothly, even on a changing mobile network. That looks simple until you consider what happened before the first frame: a creator uploaded a large file over an unreliable connection; the platform validated it, transcoded it into compatible formats, published a consistent set of segments, and distributed those bytes across a global caching network. Designing a YouTube...
The Customer Who Said "Delete Me" (and the 420 Million Events That Said "No")
A system design story about GDPR, event sourcing, and a very long Tuesday. It was a normal Tuesday. The coffee was fine. The build was green. Nothing was on fire. Then Legal sent me a Slack message: "Hey, quick one 🙂 A user sent a GDPR erasure request. We have 30 days to answer. It's been 20. Can you delete her data? Should be easy, right?" I read it three times. Twenty days. The request had been sitting in a shared inbox for twenty days. Nobody's fault. Everybody's fault. That's ho...
Stop Routing Reads to Primary: Building Causal Consistency in Java with Postgres LSN Tokens
Stop Routing Reads to Primary: Building Causal Consistency in Java with Postgres LSN Tokens Falling back to your primary database for reads right after a mutation is a lazy architectural crutch that kills your write capacity at scale. In 2026, if you aren't using causal session tokens across your edge and read replicas, you're needlessly setting money on fire with oversized primary instances. Want to go deeper? javalld.com — machine coding interview problems with working Java code and ful...
Message Queues Explained Using a Cafe Example
What Is a Message Queue? Imagine a busy café during lunch time. Many customers place orders at once, but the café has only four chefs. If the cashier had to wait for a chef to finish every order before accepting the next one, the line would move very slowly. Instead, the cashier writes each order on a ticket and puts it on a rack. The chefs pick up tickets when they are ready to cook. The cashier can keep accepting orders while the chefs work through the queue. That ticket rack is like a ...
Payment Gateway Architecture: Idempotency, Webhooks, Security, and Scaling Beyond the Happy Path
A payment gateway integration can look deceptively simple. A customer clicks Pay, the application sends a request, the provider processes the transaction, and the interface displays success. Real payment systems are rarely that predictable. Network timeouts, duplicate webhook events, delayed settlement, interrupted checkouts, fraud checks, and inconsistent transaction states can turn a basic integration into a reliability problem. The most important payment engineering decisions are often...
Monolith vs Microservices: 9 Questions to Answer Before Splitting Your App
Microservices can solve real architectural problems, but splitting a working monolith too early can turn a simple application into a…Continue reading on Skill Stuff »
Article: From Microservices to Agents: The Next Evolution of Distributed Systems
The article examines the transition from microservices to agentic AI architecture in distributed systems. Microservices allow for functional decomposition, while agentic systems focus on decision decomposition. This shift introduces new complexities in observability, reliability, and system design, highlighting the need for updated architectural patterns and practices. By Mallika Rao