Otavio Santana’s Post

If you want long-term impact, especially in roles like staff engineer or architect, you must learn how to express complex concepts clearly. Read more 👉 https://lttr.ai/AqFLg #mongodb #java #career

My favorite content is the one that helps senior and staff engineers design scalable systems using MongoDB within real-world architectures. Read more 👉 https://lttr.ai/Ap1Rm #mongodb #java #career

Quick one. When you hit an API with curl… what do you think actually happens inside? Most people just think “request → response”. But internally it’s more like: curl → Tomcat → DispatcherServlet → Controller → Service → Repository → Database → Response It hits Tomcat first. Then Spring routes it using DispatcherServlet. Controller picks it up, service runs the logic, repository talks to the DB and then the response comes back the same way. That’s it. That’s the actual path. Once you see this clearly, a lot of backend stuff stops feeling confusing. #DevOps #SRE #CloudEngineer #Hiring #OpenToWork #JobSearch #TechJobs #Backend #SystemDesign #Java #SpringBoot #Kubernetes #Docker #AWS #Observability #Monitoring #EntryLevelJobs

Most people think scaling systems is just about handling more users. In reality, it’s about handling complexity without breaking under pressure. Over the past few months, I’ve been diving deeper into Java backend engineering, focusing on problems that actually show up in production systems: • Why a simple API suddenly takes 5–8 seconds under load • How poor database indexing silently kills performance • What really happens when multiple threads compete for shared resources • Why “it works on my machine” is meaningless without proper concurrency handling One thing I’ve realized: Writing code is easy. Writing code that performs, scales, and survives real-world traffic is a completely different game. Lately, I’ve been exploring: Java Multithreading & Concurrency (Executors, Locks, Thread Pools) Building REST APIs with Spring Boot Debugging real production-like issues (latency, bottlenecks, query optimization) Structuring backend systems with clean, maintainable design My goal is simple: To become the kind of engineer who doesn’t just build features — but builds systems that don’t fail when it matters most. I’ll be sharing more learnings from real-world backend scenarios as I continue this journey. If you’re working on similar problems or hiring for backend roles, I’d love to connect. #Java #BackendDevelopment #SystemDesign #Concurrency #SpringBoot #SoftwareEngineering #OpenToWork #Careers #JobSearch #Developers #Programming #Coding #TechJobs #APIDevelopment #DistributedSystems #Scalability #PerformanceEngineering

🧠 What separates a good Java developer from a great one? It’s not just coding skills. A good developer can: ✔️ Write clean code ✔️ Build APIs ✔️ Fix bugs But a great developer thinks differently 👇 💡 1. Thinks in systems, not just code Good: writes a working service Great: understands how it behaves under load, failure and scale 💡 2. Designs for failure Good: assumes everything will work Great: assumes everything will break → Adds retries, circuit breakers, timeouts 💡 3. Understands trade-offs Good: follows best practices Great: knows when not to → Sync vs Async → Monolith vs Microservices → Cache vs DB 💡 4. Focuses on performance early Good: optimizes later Great: designs with performance in mind → Efficient queries → Caching strategies → Thread management 💡 5. Cares about observability Good: checks logs when something breaks Great: builds systems that are easy to debug → Metrics, tracing, monitoring ⚡ Real difference 👉 Good developers write code that works 👉 Great developers build systems that last As someone working with Java, Spring Boot, Kafka and distributed systems, this shift in mindset made the biggest difference in how I approach backend engineering. If you're hiring engineers who think beyond code, let’s connect 🤝 #Java #BackendDevelopment #Microservices #SystemDesign #DistributedSystems #SpringBoot #Kafka #TechCareers #backend #javabackend #fullstack #angular #react

Real talk: most backend engineers I've mentored don't fail because of bad code. They fail interviews because they can't explain WHY they made the decisions they did. Here's a thing I've noticed in technical interviews for remote roles — the question isn't just "can you build this?" It's "can you explain what happens when this breaks at 3 AM?" So here are 5 NestJS/Node.js concepts that trip people up, and how to actually think about them: 1. Guards vs Middleware vs Interceptors Not the same thing. Guards are about authorization. Middleware runs before routing. Interceptors wrap the whole response. Mixing these up in an interview is a red flag. 2. Why use Redis with Bull queues instead of a DB scheduler? Because you want retries, concurrency control, and visibility — without hammering your Postgres at scale. 3. HIPAA-compliant multi-tenant data isolation Row-level security in Postgres + tenant ID on every query. Don't rely on just app-level filtering. 4. When NOT to use microservices When your team is under 10 people and you're still figuring out the domain model. Monolith first, extract later. 5. TypeORM vs Prisma in 2026 Both work. Prisma wins on DX and type safety. TypeORM wins if you need more raw SQL control. Pick based on team, not hype. These aren't just interview prep. This is the thinking that makes you a better lead. What's one thing you always ask candidates in backend interviews? #NestJS #NodeJS #BackendDevelopment #SoftwareEngineering #RemoteJobs #TechInterviews

Something shifted in the Java ecosystem over the last 12 months and most developers have not fully processed it yet. The reactive programming debate is largely over. Not because WebFlux lost. But because virtual threads made the argument irrelevant for most use cases. For 12 years I watched teams wrestle with the reactive programming decision. WebFlux gave you non-blocking throughput but the learning curve was steep, stack traces were painful to read, and onboarding new developers onto a reactive codebase added real friction. Most teams chose it because they felt they had to, not because they wanted to. Virtual threads changed the calculus. One property in your application.yml and your Spring Boot service handles I/O-bound concurrency at WebFlux scale while your team keeps writing the blocking imperative code they already understand. Simpler code. Easier debugging. Fewer ThreadLocal memory leaks. Better tail latencies. Java 26 just dropped. Spring AI with MCP is moving fast. Agentic architectures are making their way into production Java systems. Records and sealed classes have stopped feeling new and started feeling normal. The Java ecosystem in 2026 is genuinely exciting in a way it has not been for a long time. Not because it is chasing trends. Because it is solving real production problems that teams have been working around for years. The developers who are thriving right now are the ones who kept building and kept shipping while everyone else debated whether Java was still relevant. It was. It is. The platform just caught up to where the problems actually are. What is the one Java or Spring Boot change in the last 12 months that has had the most impact on how you build systems? #Java #JavaDeveloper #CoreJava #Java21 #Java26 #SpringBoot #SpringAI #Microservices #VirtualThreads #ProjectLoom #BackendDevelopment #CloudNative #DevOps #Docker #Kubernetes #RESTAPI #Kafka #PostgreSQL #Oracle #MongoDB #Redis #MCP #AgenticAI #LLM #C2C #CorpToCorp #ContractJobs #ContractToHire #ITContracting #ITRecruiter #TechRecruiter #Hiring #Recruitment #TechJobs #ITJobs #TalentAcquisition #Careers #JobSearch #RemoteWork #usjobs #opentowork #DeveloperLife #SoftwareEngineering #ITStaffing #HiringDevelopers #ConsultingJobs #RemoteContractor #FreelanceDeveloper #ContractEngineer Amazon Web Services (AWS) Beacon Hill CVS Health Dexian Insight Global TEKsystems eTeam

Most people think 10+ years in tech means you’ve “seen it all.” Honestly? It just means you’ve seen what doesn’t work — many times. Early in my career, I thought being a great Full Stack Java developer meant: writing clean code, learning frameworks, and delivering features fast. Now I know — that’s just the baseline. Real engineering starts when: your system breaks at 2 AM your API can’t handle production traffic your “perfect design” fails in real-world usage and quick fixes today become tech debt tomorrow That’s where experience kicks in. Over the years, working with Java, Spring Boot, Microservices, Angular/React, Kafka, and cloud platforms — one mindset changed everything for me: 👉 Don’t just build for functionality. Build for failure. Because systems WILL fail. Services WILL go down. Traffic WILL spike. The question is — did you design for it? Now, I focus more on: resilience over perfection scalability over shortcuts clarity over complexity Anyone can write code that works. Experienced engineers write systems that keep working. Still evolving. Still solving. Still enjoying the process. #Java #FullStackDeveloper #Microservices #SystemDesign #SoftwareEngineering #TechLeadership #BackendDevelopment #CloudArchitecture #DistributedSystems #EngineeringMindset #DevelopersLife

If you're preparing for a Java Backend Developer role, focus on this 👇 📌 Must-have skills: Spring Boot (core + advanced concepts) REST API design Microservices architecture SQL & query optimization Basic system design 💡 Bonus: Understanding Kafka, Docker, AWS = 🚀 career boost Most people overprepare theory. Top candidates focus on practical problem solving. #JavaDeveloper #BackendEngineer #InterviewPrep #TechCareers