Spring Boot Global Exception Handling with @ControllerAdvice

Learning and implementing REST APIs with Spring Boot What's happening here: @RestController :- marks this class as a REST API handler @RequestMapping("/employee") :- base URL for all endpoints @Autowired :- injects the Service layer dependency GET /display :- a simple test endpoint to verify the API is live POST /save :- accepts Employee data as JSON and saves to DB GET /getAll :- fetches all employee records from the database Implementing Dependency Injection and a structured Layered Architecture has highlighted the importance of writing clean, maintainable code. #REST #API #BackendDevelopment #SpringBoot #Java

@Service in Spring Boot @Service is used to define the business logic layer in a Spring Boot application. It tells Spring: “This class contains the core logic of the application.” Key idea: • Processes data • Applies business rules • Connects Controller and Repository Works closely with: • @Repository → Fetches data • @RestController → Handles requests In simple terms: @Service → Handles Logic Understanding @Service helps you keep your application clean, organized, and maintainable. #SpringBoot #Java #BackendDevelopment #LearningInPublic

When updating data in a Spring Boot API, standard validation can be too restrictive, often requiring all fields to be sent even for minor changes. A more flexible solution is to use @Validated with validation groups. This approach allows you to define separate sets of rules. For example, you can have a "create" group that requires all fields to be present, and a "default" group that only checks the format of fields that are actually provided in the request. In your controller, you then apply the appropriate rule set: the strict rules for creating new items and the flexible rules for updating them. This allows your API to handle both full and partial updates cleanly while reusing the same data object, resulting in more efficient code. #SpringBoot #Java #API #Validation #SoftwareDevelopment

🚀 Spring Boot – User API Upgrade (Full CRUD) Took my mini project to the next level by implementing complete CRUD operations in Spring Boot. 🧠 What I added: ✔️ GET "/users" → Fetch all users ✔️ PUT "/user/{id}" → Update user ✔️ DELETE "/user/{id}" → Delete user 💡 Now the API supports full lifecycle operations: Create • Read • Update • Delete 🔁 Architecture in action: Controller → Service → In-memory data → JSON response 🧪 Tested all endpoints using Postman and verified the complete flow. ⚠️ Also understood the importance of proper error handling (next step: exception handling instead of returning null). 💻 DSA Practice: • Move zeros to end (array manipulation) • First non-repeating character (HashMap concept) ✨ This step helped me understand how real backend systems manage and manipulate data efficiently. #SpringBoot #Java #BackendDevelopment #RESTAPI #CRUD #DSA #LearningInPublic #SoftwareEngineering

🚨 Fetching all data from DB is a silent performance killer I once saw an API fetching 50,000 records in one go. 💥 Result: High memory usage Slow response Occasional crashes ✅ Fix: Used pagination: Pageable pageable = PageRequest.of(page, size); 💡 Bonus: Added sorting + limit control from API 💡 Takeaway: Never trust frontend to “handle large data” Backend should enforce limits. #Java #SpringBoot #BackendDevelopment #SoftwareEngineering  #Microservices #JPA #RESTAPI  #DeveloperLife #CareerGrowth

🚀 Understanding HTTP Status Codes in REST APIs While building APIs, one important thing is not just sending data… 👉 It’s also about sending the right response status. These are called HTTP Status Codes. They help the client understand what happened with the request. 🔹 Common Status Codes ✔ 200 – OK Request was successful Example: Data fetched successfully ✔ 201 – Created New resource created Example: User registered successfully ✔ 400 – Bad Request Invalid input from client Example: Missing or wrong data ✔ 404 – Not Found Requested resource not found Example: User ID does not exist ✔ 500 – Internal Server Error Something went wrong on the server 🔹 Example in Spring Boot @GetMapping("/users/{id}") public ResponseEntity<User> getUser(@PathVariable Long id) { User user = userService.findById(id); return ResponseEntity.ok(user); } If user is not found, we can return: return ResponseEntity.status(HttpStatus.NOT_FOUND).build(); 💡 Why Status Codes are important ✔ Help frontend understand response ✔ Improve API communication ✔ Make APIs more professional ✔ Very common in interviews Understanding status codes helped me connect concepts like exception handling, validation, and API design. #Java #SpringBoot #BackendDevelopment #APIDesign #Learning

How Spring Boot Handles Requests Internally (Deep Dive) Ever wondered what happens when you hit an API in Spring Boot? 🤔 Here’s the real flow 👇 🔹 DispatcherServlet Acts as the front controller receives all incoming requests 🔹 Handler Mapping Maps the request to the correct controller method 🔹 Controller Layer Handles request & sends response 🔹 Service Layer Contains business logic 🔹 Repository Layer Interacts with database using JPA/Hibernate 🔹 Response Handling Spring converts response into JSON using Jackson 🔹 Exception Handling Handled globally using @ControllerAdvice 💡 Understanding this flow helped me debug issues faster and design better APIs. #Java #SpringBoot #BackendDeveloper #Microservices #RESTAPI #FullStackDeveloper #LearningInPublic

Day 24. My API was fast. Until it wasn't. I had this: return ResponseEntity.ok(userRepository.findAll()); 10 users in development. Works instantly. Feels perfect. Then production happened: → 50,000 users in the database → One API call loads everything → Response time: 40ms → 8 seconds → Memory spikes → API crashes That's not a performance issue. That's a design mistake. And it was there from day one. I just couldn't see it yet. That's when it clicked: Your API should never decide how much data to return. The client should. So I added pagination. (see implementation below 👇) What changed: → Performance — stable response time → Scalability — works at 100 or 100,000 rows → Stability — no memory spikes The hard truth: → findAll() works in tutorials → It breaks in production → Pagination is not an optimization — it's a requirement Fetching data is easy. Controlling how much you fetch is what makes your API scalable. Are you still using findAll() in production? 👇 Drop it below #SpringBoot #Java #BackendDevelopment #Performance #JavaDeveloper

🚨 Without connection pooling, your DB will struggle under load Spring Boot uses HikariCP by default. But default config isn’t always optimal. 💥 Issue I faced: Under load → DB connections exhausted Root cause: Pool size too small for concurrent traffic ✅ Fix: - Tuned max pool size - Monitored active connections 💡 Takeaway: Database is often the bottleneck. Connection pooling decides how well you scale. #Java #SpringBoot #BackendDevelopment #SoftwareEngineering  #Microservices #JPA #RESTAPI  #DeveloperLife #CareerGrowth

#Post8 In the previous post, we learned how to create custom exceptions. Now the next question is 👇 How do we validate incoming request data? That’s where validation comes in 🔥 In Spring Boot, we use @Valid along with validation annotations. Example 👇 public class User { @NotNull private String name; @Min(18) private int age; } Controller: @PostMapping("/user") public User addUser(@Valid @RequestBody User user) { return user; } 👉 If invalid data is sent, Spring automatically triggers validation errors 💡 Common validation annotations: • @NotNull • @NotEmpty • @Size • @Min / @Max 💡 Why use validation? • Prevent invalid data • Improve API reliability • Reduce manual checks Key takeaway: Always validate incoming data to build robust APIs 🚀 In the next post, we will handle these validation errors globally 🔥 #Java #SpringBoot #BackendDevelopment #RESTAPI #LearnInPublic