I'm passionate about contributing my knowledge and experience to the community. I thrive on collaborating to solve problems, exploring optimal abstractions, and refining architectures for successful outcomes. Below, you'll discover a compilation of my articles and insights on various topics. For deeper engagement beyond summaries and titles, click on each entry to access the content!
A curated collection of 300+ engineering blog articles from top tech companies. Learn how the best engineering teams solve real-world problems at scale.
A curated collection of 300+ engineering blog articles from top tech companies. Learn how the best engineering teams solve real-world problems at scale.
Being good at coding and writing good code are two different skills. I learned it the hard way after one of my pull requests at Amazon received 30+ comments.
During my Software Engineering career, I have come across and read many coding and software engineering books, but there are a few that I keep coming back to and try to re-read them every year.
Object-Oriented Programming (OOP) gives you a practical way to structure software around real-world “things” like Users, Orders, Payments, and Notifications.
This is a guest post by Shayan, an International Grandmaster on Codeforces and a PhD Candidate at the University of Maryland.
Whether you are chatting with a friend or playing an online game, updates show up in real time without hitting “refresh”.
Scaling is a complex topic, but after working at big tech on services handling millions of requests and scaling my own startup (AlgoMaster.io) from scratch, I’ve realized that most systems evolve through a surprisingly similar set of stages as they grow.
I’ve solved over 2,000 coding problems across LeetCode and other platforms, and if there’s one thing I’ve learned, it’s this:
Most of us treat Git like a black box: memorize a few commands like git add, git commit, and git push, copy-paste the rest, and hope nothing breaks.
A load balancer is one of the most foundational building blocks in distributed systems. It sits between clients and your backend servers and spreads incoming traffic across a pool of machines, so no single server becomes the bottleneck (or the single point of failure).
“Just add an index.”
I’m excited to launch my premium pattern-focused System Design interview resource.
Software architecture patterns form the backbone of modern application development.
AI coding assistants are everywhere now.
When you’re working on a distributed system and need components to communicate asynchronously, you’ll hear terms like: “pub-sub”, “message queue”, and “message broker”.
You’re starting a new project. You’ve read about how Netflix, Amazon, and Uber use microservices to handle millions of requests.
Linked List is one of the most fundamental data structures in computer science and a must-know topic for coding interviews.
Latency, throughput, and bandwidth are the core metrics that describe the performance of a network or distributed system.
Big O Notation is a way to measure how efficiently your code performs as the input size grows.
An API (Application Programming Interface) defines how two systems communicate, what data can be shared, and in what format.
A password is meant to be secret. If someone steals it, they do not just break into one account, they often get access to every other place where the user reused that same password.
When you try to sign up on a platform like Instagram and type in your username, the system almost instantly tells you whether it’s available or not. If it’s taken, it even suggests alternatives on the spot.
In a single-node database, indexing is relatively simple. Databases use data structures such as B-Trees, Hash Maps, or Bitmap indexes to create shortcuts that allows them to quickly locate rows without scanning the entire table.
When you type a website address into your browser, something almost magical happens. Within seconds, your screen fills with content from servers that might be thousands of miles away.
Imagine you’re watching a stock market dashboard. Prices keep changing every second, sometimes multiple times in a second.
Every time you're browsing your favorite website, streaming a show, or sending an email, you’re interacting with a system designed around the client-server model.
System design is often misunderstood as a simple exercise of sketching boxes and arrows on a whiteboard. In reality, it’s much more than that.
This is a guest post by Ritankar Saha who has contributed to over 30 open-source repositories and participated in multiple open source programs, including Google Summer of Code (GSoC).
Imagine you’re building a system like Uber, Google Maps, or a nearby restaurant finder.
In system design discussions, the terms Load Balancer, API Gateway, and Reverse Proxy often come up.
When it comes to storing large volumes of unstructured data such as images, documents, and videos, there are three commonly used storage solutions:
A rate limiter is a mechanism used to control the number of requests or operations a user, client, or system can perform within a specific time window.
A JSON Web Token (JWT) is an open standard for securely authenticating users and sending information between a client (like a web or mobile app) and a server.
A web crawler (also known as a spider) is an automated bot that systematically browses the internet, following links from page to page to discover and collect web content.
In today’s distributed systems, data is almost never stored in a single place. It’s replicated across multiple servers, often spread across data centers around the world to ensure high availability, fault tolerance, and performance.
Real-time features are everywhere—chat apps, live dashboards, collaborative editors, multiplayer games. Behind the scenes, one technology powers these seamless interactions: WebSockets.
Choosing the right database is one of the most critical decisions you’ll make in a system design interview.
Redis (Remote Dictionary Server) is a blazing-fast, open-source, in-memory key-value store that’s become a go-to choice for building real-time, high-performance applications.
Services like Yelp, Zomato, or Google Maps have become an essential part of how we discover the world around us.
If you want to become a great developer, you need to master Git.
Google Docs is a cloud-based word processor that allows multiple users to create, edit, and share documents in real-time via a web or mobile interface.
Sharding and partitioning are two of the most commonly confused concepts in system design.
When you open your favorite social media app like Instagram, Facebook, LinkedIn or Twitter, you're instantly shown a personalized stream of posts.
One of the things that make databases truly powerful is their ability to protect your data even in the face of unexpected failures.
Latency is the time it takes for a system to respond to a user's action. In simple terms, it’s the delay between:
Imagine you're building an e-commerce platform and using an external payment processor like Stripe to collect payments from users.
At first glance, counting “likes” on a social media post seems simple, just increment a number, right?
Modern applications often rely on multiple systems (e.g., search engines, caches, data lakes, microservices), all of which need up-to-date data.
A key-value store is a simple type of database where data is stored as {key: value} pairs. Clients can retrieve or update values by providing the corresponding key, similar to how a hash table works.
This post is written in collaboration with Alexandre Zajac — Engineer at Amazon, tech creator, and author of the Hungry Minds newsletter.
In a distributed system, failures aren’t a possibility—they’re a certainty.
System Design can feel overwhelming especially when you're just starting out and don’t know where to begin.
Apache Kafka began its journey at LinkedIn as an internal tool designed to collect and process massive amounts of log data efficiently. But over the years, Kafka has evolved far beyond that initial use case.
With over 2 billion monthly active users, Instagram is the 3rd most popular social network after Facebook and YouTube.
Cracking a coding interview isn’t just about writing code—it’s about solving problems efficiently. And to do that, you need to think in terms of data structures.
When your application is small, with just a few hundred users, a single database server is usually enough to handle all the reads, writes, and transactions.
APIs are the backbone of modern applications, acting as the bridge between client applications and backend servers.
Distributed Databases are the backbone of modern large-scale applications, powering everything from real-time analytics to global e-commerce platforms.
Imagine you've built an app that serves video content to millions of users worldwide.
The concept of ride-hailing has transformed how we travel. Platforms like Uber, Lyft, and Ola seamlessly connect riders with drivers through intuitive smartphone apps.
Redis (Remote Dictionary Server) is an open source, in-memory key-value data store that provides sub-millisecond latency, making it an excellent choice for high-performance applications.
In a distributed system where nodes (servers) are frequently added or removed, efficiently routing requests becomes challenging.
Today’s newsletter features a special guest, Ryan Peterman, who was promoted from Junior to Staff Engineer at Meta in just 3 years.
I gave my first coding interview in 2016—and failed. I failed the next five interviews as well before finally landing my first job at Morgan Stanley.
When a client interacts with a server, there are two ways to handle it:
A Gaming Leaderboard is a ranked list of players, typically sorted by a specific metric such as score, points or level.
Imagine you’re running an e-commerce application.
With over 2.5 billion monthly active users, YouTube is the second most visited website in the world—trailing only Google.
Whether you are playing an online game or chatting with a friend—updates appear in real-time without hitting “refresh”.
API Design is one of the most crucial steps in software development and a key topic of discussion in system design interviews.
API stands for Application Programming Interface.
When I started preparing for system design interviews for the first time in 2019, I felt completely overwhelmed. It wasn’t a subject covered in college, and I had no prior experience building scalable systems.
It’s 2025 and most top tech companies are still asking LeetCode style questions in coding interviews.
Caching is a technique to make applications lightning fast, reduce database load, and improve user experience.
In system design interviews, the quality of your design and its ability to scale depends heavily on the database you choose.
Latency is the time between a user taking an action—like clicking a button or loading a webpage—and receiving a response from the system.
If you’re like most people, you probably didn’t start coding because you were genuinely passionate about it.
APIs, or Application Programming Interfaces, are a set of rules and protocols that allows two software applications or services to communicate with each other.
Back when applications ran on a single server, life was simple.
Concurrency and parallelism are two of the most misunderstood concepts in system design.
Have you ever wondered how Netflix knows which shows you've already watched? Or how Amazon avoids showing you products you've already purchased?
Have you ever wondered why modern databases are so fast and efficient, even when managing terabytes of data?
Any distributed system that operates at scale often relies on unique ids.
Nearly everyone uses a chat application to send messages and stay connected.
Imagine you're making a purchase from an online store.
Proxies and reverse proxies are servers that sit between clients and servers to improve security, privacy and performance.
Caching is a powerful technique to reduce latency and improve system performance.
Solving 500+ LeetCode problems doesn’t mean that you can pass any coding interview.
In the world of big data, batch processing and stream processing are the two common approaches to process large amounts of data.
System design can feel complex, but once you understand its fundamental building blocks and how to stitch them together, everything falls into place.
A Single Point of Failure (SPOF) is a component in your system whose failure can bring down the entire system, causing downtime, potential data loss, and unhappy users.
Spotify is the most popular music streaming platform in the world, with over 600 million monthly active users (MAU) and 200 million paid users.
Graph algorithms can seem intimidating at first but once you understand the fundamental traversal algorithms, patterns and practice few problems, they get much easier.
One of the biggest decisions we make while designing a system is choosing between a relational (SQL) or non-relational (NoSQL) database.
A notification service is a system responsible for delivering timely and relevant information to users across various channels such as SMS, email, push notifications, and in-app messages.
Over the past 7 years, I’ve given 80+ interviews and cleared interviews at multiple big tech companies including Adobe, Amazon, Google and Microsoft.
A distributed job scheduler is a system designed to manage, schedule, and execute tasks (referred to as "jobs") across multiple computers or nodes in a distributed network.
Caching is used to temporarily store copies of frequently accessed data in high-speed storage layers (such as RAM) to reduce latency and load on the server or database.
Websockets are a communication protocol used to build real-time features by establishing a two-way connection between a client and a server.
In software development, certain principles stand as the bedrock for writing code that is not only functional but also clean, maintainable, and efficient.
A message queue is a communication mechanism that enables different parts of a system to send and receive messages asynchronously.
A URL shortener is a service that takes a long URL and returns a shorter, unique alias that redirects to the original URL.
The CAP theorem, introduced by Eric Brewer in 2000, provides a fundamental framework for understanding the trade-offs that must be made when designing distributed systems.
Dynamic Programming (DP) is arguably the most difficult topic for coding interviews.
In this blog, we'll explore the concept of availability, availability tiers, strategies to improve availability, and best practices for achieving high availability.
Having solved more than 1500 LeetCode problems, if there is one thing I have learned, it’s this:
Rate limiting helps protects services from being overwhelmed by too many requests from a single user or client.
Low Level Design (LLD) or Object Oriented Design (OOD) interview tests your ability to translate high-level requirements into detailed class structures, methods and their interactions using object-oriented design principles.
Let’s say you are building an application that needs to store user information.
In software development, we often require classes that can only have one object. For example: thread pools, caches, loggers etc.
Getting good at Data Structures and Algorithms (DSA) helped me clear interviews at Amazon, Google and Microsoft.
Unified Modeling Language (UML) is a standard way to visualize the design of a software system.
Load balancing is the process of distributing incoming network traffic across multiple servers to ensure that no single server is overwhelmed.
Imagine you're sending an important letter to your friend through the mail.
I have been coding for more than 10 years now and spent last 6 years working as a Software Engineer.
Imagine a social media site like Instagram, which has over 1 billion active users.
Consider a large Book of 1000 pages.
Object-Oriented Programming (OOP) is a fundamental concept in software development that revolves around the concept of classes and objects.
In a distributed system, things fail.
When your application gets bigger, it needs more resources.
One of the first things I do after getting a new laptop or joining a new company is setting up my terminal.
System design interviews can be one of the most challenging but with a structured approach, you can navigate these interviews more effectively.
Databases are foundational building blocks of System Design used to store, manage and retrieve data efficiently.
Writing clean, maintainable code is just as important as writing code that works.
Rule No.1 of System Design: It’s all about tradeoffs.
As a system grows, the performance starts to degrade unless we adapt it to deal with that growth.