High-performance applications live or die by the speed of their data. As datasets grow and user expectations rise, even milliseconds matter. This is why SQL indexing remains one of the most valuable yet underutilized optimization techniques in modern data engineering. Indexing is not simply a feature. It is a performance strategy that shapes how your […]

Apache Kafka is the backbone of modern real-time data platforms, powering event-driven microservices, streaming analytics, log aggregation, and data pipelines at internet scale. This deep-dive guide is written for software engineers and architects who want a clear, implementation-level understanding of Kafka internals and production design patterns. 1. Apache Kafka Architecture Overview At its core, Kafka

When a production bug appears after deployment, the most critical question every engineering team asks is: Which Git commit caused the failure? Manually reviewing dozens of commits is slow, risky, and error-prone. The professional, battle-tested solution used by top engineering teams is git bisect. What Is git bisect? git bisect is a Git debugging command

Learn how banks and payment systems check whether a credit or debit card number is valid using the Luhn Algorithm (Mod-10 check), explained in the simplest way possible. What Is the Luhn Algorithm? The Luhn Algorithm, also called the Mod-10 algorithm, is a simple mathematical formula used to validate credit card and debit card numbers.

When designing a microservices architecture, one of the most critical decisions engineers face is: Should the Order Service and Payment Service communicate synchronously or asynchronously? This choice directly impacts system performance, scalability, data consistency, fault tolerance, and user experience. A poor decision can lead to failed payments, duplicate charges, stuck orders, and revenue loss. A

n today’s world of cloud-native applications and microservices architecture, managing communication between dozens of backend services is a major challenge. This is where the API Gateway becomes the backbone of modern distributed systems. Whether you are building applications in Python, Java, or C# (.NET), choosing the right API Gateway for microservices is critical for security,

If you think Git is just about commit, push, and pull, you’re missing one of its most powerful features: Git tags. For companies like Google and Netflix, Git tags are not optional. They’re a safety line that protects millions of users from bad releases, broken features, and messy rollbacks. In this post, we’ll break down:

Most RAG tutorials stop at: “Load documents → Create embeddings → Ask questions.” That works for demos. But in real production systems, one missing piece decides whether your AI is: That piece is Metadata Filtering. And yes — it has a massive real-world impact. Let’s break it down simply and practically. What Is Metadata Filtering

If you are building real-world LLM systems using LangChain, RAG, or AI agents, prompt compression might be the single most underrated skill you can master today. As LLM adoption explodes, companies quickly realize one painful truth: Long prompts = High cost, slow latency, more hallucinations, and weaker security. This is where Prompt Compression becomes a

React 19 introduced a new render-time API: use(). If you’ve ever felt that handling async data with useEffect + useState + “loading” + “error” flags is too much boilerplate, use() is basically React saying: “What if you could just await a Promise directly inside your component?” In this post, we’ll cover: What is use() in