User Service Microservice Update: User Repositories and DTOs

One of the most valuable Java patterns in production: Immutable DTOs with Records + Builder: In real-world Java applications (Spring Boot APIs, microservices, event systems), we create hundreds of DTOs. The best modern pattern in 2026: Records (immutable by default) + Builder pattern for flexible construction.Benefits:Immutable → thread-safe and predictable No boilerplate getters/setters Builder gives nice fluent API for optional fields Excellent integration with Jackson, validation, and MapStruct Realistic production example below #Java #SpringBoot

Devlog #14 - PulseNotify Service layer for user-service done. Today: - UserNotFoundException and UserAlreadyExistsException for specific error handling and GlobalExceptionHandler with @ControllerAdvice for structured API responses - UpdateUserRequest DTO as Java Record - UserService with full CRUD + deactivate method Tomorrow I can start with the controller and probably the tests. Step by step the project keeps growing, consistency is key. Link to Github in comments #Java #SpringBoot #Microservices #BuildingInPublic #TechJobs

Exciting to see how this company unified its fragmented Java environment with Azul Core, reducing overhead and complexity. Great example of modernization done right. Check it out here: https://bit.ly/40dEP24 #Java #AzulCore #IT

🚨 Hot take: Most “async” Java code isn’t actually asynchronous — it’s just parallel blocking. I recently reviewed a service using CompletableFuture everywhere… ⚠️ but response time was still bad. ❓ Why? Because .get() was called almost immediately after supplyAsync(). 👉 At that point, the code not doing async — the code just adding complexity. 💡 What actually made a difference: ✅ Letting futures complete without blocking 🔗 Combining results instead of waiting on each call ⚙️ Controlling thread pools instead of relying on defaults 🚫 Async done wrong = harder debugging, unstable latency, pressure on downstream systems 🚀 Async done right = better orchestration, not just faster code 🧠 Most systems don’t have a performance problem — they have a design problem disguised as async. 💬 Curious — how often have you seen “fake async” in real projects? #Java #SystemDesign #Microservices #BackendEngineering #AsyncProgramming #TechLeadership

From fragmentation to efficiency: this company transformed its Java environment with Azul Core, simplifying operations across regions and saving 80% in costs. A must-read case study. https://bit.ly/40dEP24 #Java #AzulCore #IT

https://lnkd.in/dg9WBdXM Runtime upgrades in enterprise Java mean broken deps, code changes, testing. Grace Robinson & Laura Cowen introduce “zero migration”—upgrade runtimes without touching code. See how apps move across 80+ releases unchanged! #OpenLiberty #Java #API @OpenLibertyIO

HTTP status codes made more sense when I started using them in real APIs 👇 They’re not just numbers — they tell you exactly what happened with a request Using the right status codes makes your APIs easier to debug and more predictable Still learning, but this small detail makes a big difference 💡 #BackendDevelopment #APIs #Java #Developers #WebDevelopment #LearningInPublic

Ever tried adding two numbers in Java… and it failed? 🤯 I recently hit this: existingValue + proposedValue ❌ Compilation error! Reason? They were not primitives… they were BigDecimal. Fix was simple, but important: existingValue.add(proposedValue) ✔ That’s when it clicked 👇 In financial or precision-based systems, BigDecimal is not just a choice — it’s a necessity. Also learned: Null handling + proper scaling (setScale) can save you from hidden production bugs. Small issue. Big lesson. Have you faced this before? #ProductionIssues #JavaDeveloper #Java #Debugging

When a Java application runs, the JVM organizes memory into well-defined regions—each with a distinct responsibility and lifecycle. Understanding this memory model is key to writing efficient, scalable, and high-performing applications. From object allocation in the Heap, to method execution in the Stack, and metadata management in Metaspace—every part plays a critical role in how your application behaves at runtime. Sharing a simple visual to break it down 👇 #Java #JVM #MemoryManagement #SoftwareEngineering #PerformanceOptimization

Devlog #5 - PulseNotify: When building microservices, "it works" isn't enough, you have to design for failure and consistency. Today I focused on the template-service: -@Transactional to keep DB writes and Kafka events in sync -Repository and Service layers -DTOs as Java 21 Records with @Valid -@ControllerAdvice for structured exception handling -Flyway migration for schema versioning Small decisions. Big difference in production. Repository: https://lnkd.in/d4rtYMAa #Java #SpringBoot #Microservices #SoftwareArchitecture #BuildingInPublic