Author: Arunangshu Das

Automation tools have revolutionized the way businesses and developers handle repetitive tasks, improving efficiency, accuracy, and scalability. From workflow automation to software development pipelines, automation plays a crucial role in modern tech stacks. However, while these tools promise efficiency, they are not without their downsides. Some come with steep learning curves, hidden costs, or inflexibility that can lead to unexpected bottlenecks. 1. Selenium – The King of UI Test Automation with Fragility Issues What is Selenium? Selenium is the go-to automation tool for browser testing. It allows developers to write test scripts in multiple programming languages (Java, Python, JavaScript, etc.)…

In today’s fast-paced software development world, automation is no longer a luxury—it’s a necessity. Whether you’re coding, testing, deploying, or managing infrastructure, automating repetitive tasks can save time, reduce errors, and improve efficiency. As a software developer, you don’t want to spend hours on manual debugging, repetitive code formatting, or deploying applications manually. That’s where automation tools come in. 1. GitHub Actions – Automate Your CI/CD Workflows Category: Continuous Integration & Deployment (CI/CD) When it comes to automating software builds, testing, and deployment, GitHub Actions is a game-changer. Instead of manually running tests and deployments, you can create custom workflows…

Databases are the backbone of almost every modern application, from small websites to massive enterprise systems. However, as data grows, so does the challenge of retrieving it efficiently. That’s where database indexing comes into play. An index is a data structure that improves the speed of data retrieval operations at the cost of additional storage and maintenance overhead. Think of it like an index in a book—it helps you quickly find what you’re looking for without scanning every page. But not all indexes are the same. Different databases offer different types of indexes, each optimized for specific query patterns. 1.…

Database indexing is one of those things that can make or break your application’s performance. When done right, it significantly boosts query speed and reduces database load. But when done wrong? It can lead to slow queries, bloated storage, and even system crashes at scale. 1. Not Having Any Indexes at All Yes, this happens more often than you’d think. Many developers assume that modern databases are fast enough by default and forget that indexes are what make queries truly efficient. → Why It’s a Problem Without indexes, your database has to scan every row in a table to find the…

Databases power almost every modern application, from social media platforms to financial systems. At the core of reliable databases lies the concept of ACID properties—Atomicity, Consistency, Isolation, and Durability. These properties ensure data integrity, even in the face of system failures, concurrent transactions, or crashes. However, despite ACID’s importance, many developers misunderstand how it works in real-world database management systems (DBMS). These misconceptions often lead to incorrect assumptions about how transactions behave, which can cause performance issues, data corruption, or unnecessary complexity in application logic. 1. Misconception: Atomicity Means “All or Nothing” Always Happens Instantly Many developers think that atomicity…

Have you ever worked with a database that seemed chaotic, filled with redundant data, making queries slow and frustrating? If so, then normalization is your best friend. Database normalization is the process of organizing data efficiently to eliminate redundancy and ensure data integrity. Without proper normalization, databases become bloated, slow, and error-prone, leading to inconsistent records, unnecessary storage consumption, and performance bottlenecks. However, normalization isn’t a one-size-fits-all solution; over-normalization can lead to excessive joins, making queries complex and slow. 1. First Normal Form (1NF) – Eliminating Duplicate Data The first step in normalization is ensuring that each column in a…

When designing a database, you don’t just throw data into tables and hope for the best. If you do, you’ll likely end up with redundancy, inconsistencies, and inefficient queries that slow down your application. This is where database normalization comes in. Think of normalization as decluttering your database—breaking down complex, messy structures into well-organized, efficient ones. It’s like turning a cluttered warehouse into a neatly arranged inventory system, where everything has its place. What is Database Normalization? Normalization is the process of organizing a database to minimize redundancy and dependency. It involves breaking down large tables into smaller, related tables…

When it comes to databases, one of the biggest debates in the tech world revolves around SQL vs. NoSQL. Both have their strengths, and the right choice depends on the specific needs of your project. SQL databases, also known as relational databases, have been around for decades and are great for structured data and complex queries. On the other hand, NoSQL databases (which include document stores, key-value stores, column-family stores, and graph databases) are designed to handle unstructured or semi-structured data with high scalability. So, when should you use SQL, and when should you use NoSQL? Use Cases for SQL…

Software architecture plays a crucial role in how applications are built, scaled, and maintained. For years, the monolithic architecture was the dominant approach, where an entire application was developed as a single, unified codebase. However, with the rise of microservices architecture, companies have started shifting toward a more modular and scalable way of building applications. But why exactly are microservices gaining so much traction? What makes them better than monolithic architecture in modern software development? 1. Scalability: Scale What You Need, When You Need One of the biggest advantages of microservices is scalability. In a monolithic architecture, scaling an application…

When it comes to modern web development, the smooth integration between the backend and frontend is what makes an application function seamlessly. A well-integrated system ensures data consistency, performance efficiency, and a better user experience. But here’s the challenge—how do you pick the right technology to bridge the gap between the frontend and backend? Should you go for GraphQL or REST APIs? What about WebSockets for real-time communication? 1. REST APIs (Representational State Transfer) Best for: Standardized web services, mobile apps, and most modern web applications. REST APIs have been the go-to method for backend-frontend integration for years. Based on…