Ganesh Guntanala’s Post

Spent 20 minutes wondering why my Spring Boot app was starting slow. Checked everything. Database connections. External APIs. Nothing obvious. Then I found this: @SpringBootApplication @ComponentScan(basePackages = "com") Scanning "com" means Spring scans every package starting with com. Including third party libraries. The fix: @SpringBootApplication @ComponentScan(basePackages = "com.myapp") Be specific. Only scan your packages. Startup time dropped from 45 seconds to 12 seconds. Small change. Big difference. #SpringBoot #Java #Performance #BackendDevelopment #Programming

Spent 10 minutes wondering why my Spring Boot app wasn't picking up my application.yml values. The config looked fine: server: port: 8081 But the app kept starting on 8080. The problem: My application.yml was in src/main/resources but I also had an application-properties file in the same folder. Spring Boot loads both. Properties file wins. The fix: Delete the duplicate or merge them. Don't mix both unless you know the load order. Spring Boot priority: properties file > yml file Small overlap. Silent failure. Easy to miss. #SpringBoot #Java #BackendDevelopment #Programming

⚙️ Phase 2: What’s Inside a Spring Boot App? When you add spring-boot-starter-web, something interesting happens… You’re not just getting libraries. You’re getting: ✔️ A web server ✔️ Servlet container ✔️ Auto-configuration ✔️ Production-ready defaults By default, Spring Boot includes an embedded server. That means: 👉 No need to install anything manually 👉 Your app becomes self-contained Even better: You can switch servers easily by changing dependencies. Your app is no longer tied to a single runtime environment. 💡 This abstraction is what makes Spring Boot flexible and production-friendly. Next post: What actually happens when you run your Spring Boot app? #SpringBoot #Java #BackendDevelopment #SoftwareEngineering  #SystemDesign #WebDevelopment #Programming #Developers #SpringFramework #Microservices #JavaBackend #TechDeepDive  #APIDevelopment

Your API is slow. But your code looks fine. Common Spring Boot issue: N+1 queries. 1 query for parent • N queries for children Suddenly: • More DB calls • Higher latency • Poor performance Fix: • Use JOIN FETCH • Use DTO projections • Monitor queries Spring Boot didn’t slow your app. Your data access did. #SpringBoot #Java #Performance #Backend #SystemDesign #Debugging

Most beginners use Spring Boot… but don’t really understand how it works. Here’s the simple breakdown, When you run a Spring Boot app: • It starts an embedded server (Tomcat by default) • Scans your project for components (@Controller, @Service, etc.) • Automatically configures things using AutoConfiguration That’s the magic — you don’t write boilerplate configs. 💡 Example: Instead of manually setting up a server, Spring Boot does it for you. Why this matters: If you don’t understand this, debugging becomes painful later. I’m currently diving deeper into how Spring Boot simplifies backend development — and honestly, it's powerful when used right. #SpringBoot #Java #BackendDevelopment

Ever wondered why your app slows down as your database grows? 🐢 Chances are, you've hit the N+1 problem — and you might not even know it. Here's what happens: ✅ You fetch 100 users → 1 query ❌ Then fetch each user's posts one by one → 100 more queries That's 101 queries for something that should take just 1. The fix? A simple JOIN or batch query can reduce hundreds of round trips to the database down to a single request — making your app dramatically faster and easier to scale. I wrote a full breakdown with code examples covering: → What the N+1 problem actually is → Why it kills performance at scale. → 2 ways to fix it (JOINs and batch queries) 🔗 Read it here: https://slugy.co/id49CqI #WebDevelopment #Database #JavaScript #BackendDevelopment #SoftwareEngineering #Programming

Most Spring Boot developers ship to production without knowing if their app is truly healthy. 🩺 You test your endpoints. Your CI passes. You deploy. But the moment something silently breaks, a database connection drops, an external API becomes unreachable, disk space runs out , your application keeps running, no errors, no alerts, just quietly serving failures to your users. That's the problem Health Checks solve. And Spring Boot makes it almost too easy to get right. 🩺 What is a Health Check? A simple mechanism that answers one question on a schedule: "Is this service actually ready to serve traffic?" Not just "is the JVM running?" — but "are all the pieces this app depends on working?" ⚡ Spring Boot Actuator , built-in and ready Add one dependency and you instantly get a /actuator/health endpoint that checks your database, MongoDB, disk space and more, automatically. UP ➡️ all good, serve traffic. DOWN ➡️ something is wrong, alert immediately. No custom code needed to get started. 🔧 But the real power is in custom indicators The default tells you if the app is alive. Custom health indicators tell you if your app is useful. You can write checks for anything: an external payment API, a message queue, a critical cache, if that dependency is down, your health endpoint reflects it, and your infrastructure reacts automatically. 💡 Two checks every production app needs: Liveness ➡️Is the app alive? Should it be restarted? Readiness➡️ Is the app ready to receive traffic? These two signals are especially critical in Kubernetes, they drive automatic restarts and traffic routing without any manual intervention. Are you using custom health indicators in your Spring Boot apps? Or just relying on the defaults? 👇 #Java #SpringBoot #HealthCheck #BackendDevelopment #SoftwareArchitecture #LearningInPublic #Kubernetes #Programming

Your Spring Boot app works fine… Dependencies are getting injected… Everything looks clean. But there’s a hidden problem @𝗔𝘂𝘁𝗼𝘄𝗶𝗿𝗲𝗱 field injection Most beginners use it like this: @𝗔𝘂𝘁𝗼𝘄𝗶𝗿𝗲𝗱 𝗽𝗿𝗶𝘃𝗮𝘁𝗲 𝗨𝘀𝗲𝗿𝗦𝗲𝗿𝘃𝗶𝗰𝗲 𝘂𝘀𝗲𝗿𝗦𝗲𝗿𝘃𝗶𝗰𝗲; It works. But that doesn’t mean it’s right. What’s the hidden cost? 🔸 Harder to test You can’t easily mock dependencies without reflection or Spring context 🔸 Breaks immutability Fields can’t be final → objects become mutable 🔸 Hidden dependencies From outside, it’s not clear what your class depends on 🔸 Tight coupling with Spring Your class depends on the framework to work properly Now here’s the better approach: 𝗖𝗼𝗻𝘀𝘁𝗿𝘂𝗰𝘁𝗼𝗿 𝗜𝗻𝗷𝗲𝗰𝘁𝗶𝗼𝗻 𝗽𝗿𝗶𝘃𝗮𝘁𝗲 𝗳𝗶𝗻𝗮𝗹 𝗨𝘀𝗲𝗿𝗦𝗲𝗿𝘃𝗶𝗰𝗲 𝘂𝘀𝗲𝗿𝗦𝗲𝗿𝘃𝗶𝗰𝗲; 𝗽𝘂𝗯𝗹𝗶𝗰 𝗨𝘀𝗲𝗿𝗖𝗼𝗻𝘁𝗿𝗼𝗹𝗹𝗲𝗿(𝗨𝘀𝗲𝗿𝗦𝗲𝗿𝘃𝗶𝗰𝗲 𝘂𝘀𝗲𝗿𝗦𝗲𝗿𝘃𝗶𝗰𝗲) {   𝘁𝗵𝗶𝘀.𝘂𝘀𝗲𝗿𝗦𝗲𝗿𝘃𝗶𝗰𝗲 = 𝘂𝘀𝗲𝗿𝗦𝗲𝗿𝘃𝗶𝗰𝗲; } Why this is better:  • Makes dependencies explicit  • Easy unit testing (no Spring needed)  • Supports immutability (final fields)  • Fails fast if dependency is missing ⚡ And the best part? In modern Spring Boot, you don’t even need @Autowired on constructors. It just works. 💡 Real insight Field injection is convenient for small demos. Constructor injection is what survives in 𝗿𝗲𝗮𝗹 𝗽𝗿𝗼𝗷𝗲𝗰𝘁𝘀. Next time you write @Autowired, pause for a second… And ask: “Is there a better way?” #SpringBoot #CoreJava #SpringFramework #BackendDevelopment #BackEnd #SoftwareEngineering #SpringAnnotations #Programming #Developers #RealtimeProjects #Microservices #systemdesign #aswintech

Your Spring Boot app has 200 threads. Only 20 are doing real work. Here's what those 200 threads are actually doing: → 30 waiting for a DB connection. HikariCP pool = 10. 20 threads just standing in line. → 40 waiting for an external API. No read timeout set. Threads stuck in TIMED_WAITING. → 20 held by @Transactional. Method calls external service + sends email while holding a DB connection for 5+ seconds. → 10 blocked on synchronized code. One thread has the lock. 9 waiting. → 80 idle. No requests. Just consuming 1MB stack each = 80MB doing nothing. → 20 actually working. 200 threads. 20 working. 100 waiting. 80 idle. How to see this yourself: → jstack <pid> > thread-dump.txt → Or /actuator/threaddump → RUNNABLE = doing work. WAITING = stuck. BLOCKED = waiting for lock. → If WAITING > RUNNABLE — your app isn't slow because it lacks threads. It's slow because most threads are waiting. The fix: → Match HikariCP pool size to actual concurrency → Set read timeout on ALL HTTP clients → Keep @Transactional short — DB only, external calls outside → Consider Virtual Threads (Java 21) — waiting becomes cheap More threads won't fix a thread utilization problem. It'll just give you more threads doing nothing. #threads

🚨 Ever wondered what actually happens when a Spring Boot app starts? Most developers just run the app and move on. But understanding this helped me debug startup issues faster. Here’s the simplified flow 👇 Spring Boot initializes the ApplicationContext Auto-configuration kicks in (based on classpath) Beans are created and wired Embedded server (Tomcat) starts Application is ready to serve requests 💥 Real issue I faced: A misconfigured bean was slowing startup by ~20 seconds. Root cause? Unnecessary component scanning + heavy initialization logic inside a bean. ✅ Fix: Reduced scan scope Moved heavy logic to lazy initialization 💡 Takeaway: Startup time matters more than you think in microservices. Have you ever debugged a slow Spring Boot startup? #Java #SpringBoot #BackendDevelopment #SoftwareEngineering  #Microservices #RESTAPI #SystemDesign  #DeveloperLife #100DaysOfCode