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
Many brute-force solutions run in O(N²) or worse, which is unacceptable for large inputs. The Sliding Window technique is one of the most powerful ways to cut down unnecessary work and bring solutions down to O(N) or O(N log N). If you’ve ever solved problems around subarrays, substrings, or continuous segments, chances are you’ve already … Read full article: Mastering the Sliding Window Technique
Apache Kafka has become the backbone of modern real-time data pipelines and event-driven architectures. Originally developed at LinkedIn and later open-sourced, Kafka is now one of the most widely adopted distributed streaming platforms. It is designed to handle high-throughput, fault-tolerant, and scalable event streaming across diverse industries. What is Kafka? At its core, Kafka is … Read full article: Apache Kafka: A Complete Guide
Let’s go deep into Prefix Sum (Pre Sum) from a competitive programming perspective.This is one of the fundamental techniques you’ll repeatedly use in array, string, DP, and number theory problems. What is Prefix Sum? For an array arr[0..n-1], the prefix sum array pre[i] is defined as: That is, the cumulative sum up to index i. … Read full article: Prefix Sum (Pre Sum) in Competitive Programming