The Code Hut

Many developers think their Spring Boot REST APIs are already well-implemented, but subtle mistakes can cause performance issues, security vulnerabilities, and maintenance headaches. In this post, I’ll share 15 common pitfalls and practical tips to build APIs that are fast, secure, and maintainable. 1. 📝 Proper Exception Handling Returning raw exceptions or inconsistent error responses confuses API clients. Always use @ControllerAdvice to centralize exception handling and return consistent messages. @ControllerAdvice public class GlobalExceptionHandler { @ExceptionHandler(Exception.class) public ResponseEntity<ApiError> handleException(Exception ex) { ApiError apiError = new ApiError(HttpStatus.INTERNAL_SERVER_ERROR, ex.getMessage()); return new ResponseEntity<>(apiError, HttpStatus.INTERNAL_SERVER_ERROR); } } ✅ Ensures clients receive clear, consistent error messages and avoids exposing internal stack traces. 2. 🔢 Validate I...

Java interviews typically go far beyond simple syntax questions. They test your knowledge of core concepts, concurrency, JVM internals, and system design , while also evaluating how you solve problems under pressure. Below are 10 common questions you’re likely to encounter and how to approach them effectively. Round 1: Core Java — The “Filter the Pretenders” Stage 1. What’s the difference between == and .equals() in Java? What they’re really testing: understanding object identity vs. logical equality. == checks if two references point to the same object. .equals() checks if two objects are logically equivalent (depending on how it's overridden). String a = new String("foo"); String b = new String("foo"); System.out.println(a == b); // false System.out.println(a.equals(b)); // true 2. Explain the relationship between hashCode() and equals() . What they’re really testing: Java’s equality contract. If two o...

SQL performance problems often arise from common anti-patterns. Understanding these 10 mistakes will help you write faster, cleaner, and more maintainable SQL queries. 1. 🚫 SELECT * (Lazy Column Fetching) Selecting all columns fetches unnecessary data and increases memory and network load. -- BAD SELECT * FROM users; -- GOOD SELECT id, username FROM users; ✅ Always select only the columns you need. 2. 📦 Storing Comma-Separated Values Storing multiple values in one column violates normalization and makes queries slow and complex. -- BAD -- hobbies column: "reading,swimming,gaming" SELECT * FROM users WHERE hobbies LIKE '%swimming%'; -- GOOD: normalized table CREATE TABLE user_hobbies ( user_id INT, hobby VARCHAR(50) ); ✅ Normalize data for better performance and maintainability. 3. 🔍 Using LIKE with Leading Wildcards Leading wildcards prevent indexes from being used, causing full table scans. -- BAD SELECT * FROM products WHER...

Many developers think their Java code is already fast, but subtle performance issues can accumulate and slow down applications. In this post, I’ll share 18 proven techniques 1. 📝 Efficient String Handling In Java, Strings are immutable. Concatenating strings with + in a loop creates a new object each time, which consumes memory and CPU. Use StringBuilder or StringJoiner for repeated concatenation. // BAD: creates many temporary String objects String result = ""; for(String s : list) { result += s; } // GOOD: uses a mutable object StringBuilder sb = new StringBuilder(); for(String s : list) { sb.append(s); } String result = sb.toString(); ✅ Use this in loops or repeated concatenation. For simple, one-time concatenations, + is fine. 2. 🔢 Use Primitives When Possible Wrapper classes like Integer or Long create extra objects (autoboxing), which slows down loops and increases garbage collection. Primitives ( int , long , double ) ar...

🌐 Distributed Systems Series 📖 Distributed Systems with Java (Series Intro) 📖 Intro to Distributed Systems ☁️ Cloud-Native Considerations ⚠️ Distributed System Anti-Patterns 🧪 Testing Strategies for Distributed Systems 🛡️ Advanced Fault Tolerance 🔗 Distributed Transactions Deep Dive 📈 Microservices Scaling Patterns 🔔 Monitoring & Alerting 📡 Event-Driven Architecture 🔐 Security in Distributed Systems 👀 Observability ⚡ Caching Strategies 📊 Consistency Models 🔍 Service Discovery & Load Balancing 💪 Resilience Patterns 💬 Communication Patterns 🧱 Fault Tolerance & Reliability 🔄 Transactions & Sagas 🤝 Consensus & Coordination 🔒 Concurrency & Locking 🏗️ Microservices & Architecture 🧩 Key Microservices Design Patterns 📐 Applying SOLID Principles ☕ Java & Design / Performance / Interview 🎨 Most Important Java Design Patterns 🚀 Java 17 Features You Need to Kn...