Synchronous: Request waits. Thread blocks. Asynchronous: Request moves on. Work continues in background. Blocking: • Simple • Predictable Non-blocking: • Efficient • Scalable But here’s the catch: Async adds complexity: • Debugging • Error handling • Thread management Don’t use async everywhere. Use it where it matters. #Java #Concurrency #SpringBoot
Async Programming: When to Use and Its Trade-Offs
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A small habit that saved me countless debugging hours: Always add meaningful logs. Not just: “Error occurred” But: “Payment service failed while calling order service – orderId:123” Future you (or another developer) will thank you. #Java #CleanCode #SoftwareDevelopment
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Day 42 of consistency 💻🔥 Solved Add Two Numbers using linked lists — a classic problem that really tests understanding of pointers, carry handling, and edge cases. Key takeaways: Handling carry efficiently is crucial Dummy nodes make list problems much cleaner Iterative approach keeps space optimal Not the fastest runtime yet, but improvement is a process — optimizing step by step. Consistency > Perfection. #Day42 #LeetCode #DSA #Java #CodingJourney #ProblemSolving #100DaysOfCode
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https://lnkd.in/d2QuDRvF Most “exciting” releases break your code. #Java26 doesn’t. It compiles, runs, and improves performance—thanks to G1 GC and HTTP/3. Lutske de Leeuw & Johannes Bechberger explain why boring wins. See why boring tech is a competitive advantage. Read their article! #Java #JVM
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Virtual threads Traditional thread-per-request models were expensive. Virtual threads make concurrency cheap, scalable, and easier to reason about. Every new Spring Boot service has spring.threads.virtual.enabled=true set by default. The era of reactive-by-default for I/O-bound work is fading fast — teams are writing straightforward, blocking-style code and still achieving WebFlux-level concurrency. Before Virtual Threads: → You needed reactive programming (WebFlux, RxJava) to handle high concurrency → Reactive code is hard to read, hard to debug, hard to onboard → Context switching between threads was expensive at scale After Virtual Threads: → Write simple, imperative code → JVM handles millions of lightweight threads natively → Same or better throughput — zero reactive complexity Why this matters: → Reactive code was powerful but painful to write and debug → Virtual threads give you the same performance with half the complexity #Java #SpringBoot #BackendDevelopment #Microservices #VirtualThreads
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The real reason legacy systems become painful Legacy is often not “old code” — it’s code nobody can safely change. A system is not legacy because it’s 5 or 10 years old. It becomes legacy when: - nobody understands the side effects - changes feel dangerous - deployments create fear - debugging takes too long - the architecture stopped communicating intent That’s why I don’t judge code only by syntax or age. I judge it by one question: How safely can a team change it? That’s why things like these matter so much: - clear boundaries - good naming - testability - observability - domain clarity A codebase becomes expensive long before it becomes “outdated”. #LegacyCode #SoftwareEngineering #Java #SpringBoot #Refactoring #BackendDevelopment
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Most developers think @Autowired is just dependency injection. It's not ❌ It's Reflection + Proxies + Runtime Wiring. Which means : ⭕ Dependencies are injected at runtime (not compile time) ⭕ You might be calling a proxy, not your actual class ⭕ Field injection hides dependencies and hurts testability ⭕ Startup time increases as your app grows The biggest surprise : 👉 this.method() can bypass Spring logic completely (broken @Transactional) Lesson : "Convenience annotations often hide real complexity." Do you still use Field Injection in production ? #SpringBoot #Java #BackendEngineering #SoftwareArchitecture
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Day 73/100 Logging (Very Important) 📝 Today I focused on something that often gets ignored but is critical in real-world applications — logging. Learned: Why logging is important for debugging and monitoring applications Different log levels and when to use them (INFO, WARN, ERROR) Key takeaway: Logs are not just for debugging, they help understand what’s happening inside the application without stopping it. Starting to realize that good logging is a must for building reliable backend systems. #BackendDevelopment #Java #Logging #LearningInPublic #100DaysOfCode
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Async improves throughput, but not latency, and that’s where many teams get it wrong. In real systems I’ve seen async pipelines overwhelm downstream services because backpressure wasn’t handled, leading to cascading failures. The real decision point is workload type, CPU bound vs IO bound, not just scalability buzzwords.