Puneet Verma How to split a database across machines — the trade-offs, the strategies, and the failure modes that trip up real systems at scale. What sharding is A single database node has hard physical ceilings: disk capacity, RAM, CPU cycles, and write throughput are all finite. For most applications, this is fine for years. But at … Read full article: Sharding
Every system hits a wall eventually. Requests pile up, latency climbs, and the database starts sweating. At that moment, every engineer faces the same fork in the road: do you make the machine bigger, or do you add more machines? That choice — vertical scaling versus horizontal scaling — is one of the most consequential … Read full article: Vertical vs Horizontal Scaling: A Complete Guide for System Designers
Imagine you and your friend both open the same Google Doc at the same time. You type something. Does your friend see it instantly? After a delay? Ever? That question — when does everyone see the same thing? — is what consistency is all about. And it turns out, there’s no single right answer. Different … Read full article: A Simple Guide to Consistency
Imagine you are running a rapidly growing website like backendmesh.com. One morning, a post goes viral. Traffic skyrockets. Millions of clicks are pouring in, and your boss asks a simple question: “How many unique visitors did we get today?” Introduction In the early days of the web, this was an easy question to answer. You … Read full article: Demystifying HyperLogLog: How to Count Billions of Things in Kilobytes of Memory
The dual write problem is one of the most fundamental and tricky challenges in distributed systems engineering. It arises whenever a system needs to write data to two or more independent data stores (or systems) atomically, and the inherent impossibility of doing so reliably without careful design. Introduction As applications evolve from monolithic architectures to … Read full article: The Dual Write Problem: A Comprehensive Guide
Redis (Remote Dictionary Server) is an open-source, in-memory data structure store used as a database, cache, message broker, and streaming engine. What is Redis? Redis (Remote Dictionary Server) is an open-source, in-memory data store used as a database, cache, message broker, and queue. It stores everything in RAM, which is why operations are blazing fast … Read full article: Redis Complete Production Guide
At a small scale, a counter is nothing. Increment a number, store it, done. But the moment your product goes viral — a tweet blowing up, a video trending, a flash sale going live — that innocent little number becomes a thundering bottleneck that can bring your entire system down. Sharded counters are the standard … Read full article: Why a Simple Counter Breaks at Scale
This will be a complete deep understanding guide so you can use LCS intuition for many DP problems. Subsequence vs Substring Problem Definition Given two strings. Find the length of the longest subsequence common to both strings. Brute Force Thinking (Important for intuition) At each character we have two choices Key Insight Compare characters: text1[i] … Read full article: Longest Common Subsequence (LCS) — Complete Guide
Knapsack derives its name from the problem faced by someone who is constrained by a fixed-size knapsack and must fill it with the most valuable items. The problem often arises in resource allocation, where decision-makers must choose from a set of indivisible projects or tasks under a fixed budget or time constraint, respectively. What is … Read full article: Knapsack — The Master DP Pattern
Dynamic Programming (DP) is an optimisation technique that solves complex problems by breaking them down into smaller, overlapping subproblems and storing their results to avoid redundant calculations. About DP Why do we even need dynamic programming? Before DP, let’s understand the problem DP is solving. While solving a problem, we often end up solving the … Read full article: Dynamic Programming (DP): A Complete Guide