Backend Tech Stack Options for Developers

──────────────────────── │ 𝙳𝚊𝚢 – 𝟺 │ ʀ ᴇ ꜱ ᴛ ᴀ ᴘ ɪ ꜱ | ──────────────────────── | ᴍ ɪ ᴅ ᴅ ʟ ᴇ ᴡ ᴀ ʀ ᴇ │ ────────────────────── ⚡ What was learned ➜ ────────────────────── • Learned the fundamentals of REST APIs and how they help in structuring backend applications in a clean and standard way 🌐📘 • Understood the role of middleware and how it processes requests before they reach the final route, helping in extracting and handling data efficiently 🔄🧠 • Implemented the DELETE method to remove data from APIs, understanding proper API operations 🗑️⚙️ • Learned how to update data using IDs and route params, modifying specific fields like description in existing API data ✏️📦 • Explored how params help in identifying and updating specific resources dynamically 🔍🔁 • Took the first steps toward deployment, starting to learn how to deploy backend applications on Render 🚀☁️ Backend concepts are slowly coming together. Strong basics, real practice, and patience paving the way forward 🌱 ────────────────────────── ➜ Sheryians Coding School | 𝙲𝚘𝚑𝚘𝚛𝚝 2.0 ────────────────────────── #SheryiansCodingSchool #BackendDevelopment #RESTAPI #ExpressJS #NodeJS #Middleware #Deployment #LearningJourney #Consistency

🚦 LLD Case Study: Designing a Rate Limiter in Node.js Rate Limiter is a very common Low-Level Design (LLD) interview question for backend roles. Instead of explaining it only in theory, I decided to design and implement it end-to-end with a production mindset. 🔗 GitHub: https://lnkd.in/drD79sfY What this project covers (LLD-focused) • Token Bucket, Fixed Window, and Sliding Window algorithms • Strategy Pattern to switch algorithms without changing client code • Redis + Lua scripts for atomic operations • Express middleware–based design • RFC-style rate-limit headers • Handling real-world scenarios like burst traffic and concurrency Why I built this In interviews, the expectation is not just: “Do you know the algorithm?” But also: • Can you structure clean, maintainable classes? • Can you extend the design without breaking existing code? • Can you handle race conditions? • Can you think about failure scenarios? This project answers those questions with actual working code, not just diagrams. Key design takeaway Algorithms change. Good design should not. Using the Strategy Pattern, each rate-limiting algorithm is isolated, testable, and replaceable without touching the rest of the system. If you’re preparing for backend LLD interviews or working on API design, this might be useful. Feedback and discussions are welcome 🙂 #LowLevelDesign #SystemDesign #NodeJS #BackendEngineering #Redis #InterviewPrep #OpenSource

📘 NodeJS Handwritten Notes Sharing my handwritten notes on NodeJS, created to explain backend development concepts in a simple and structured way. Covers Node basics, core modules, npm, Express fundamentals, REST APIs, and asynchronous programming. Ideal for beginners, revision, and interview preparation. Here is unlimited access to 7,000+ top-tier courses🚀 imp.i384100.net/xLBzBA 𝗚𝗼𝗼𝗴𝗹𝗲 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝘆𝗼𝘂 𝘄𝗶𝗹𝗹 𝗿𝗲𝗴𝗿𝗲𝘁 𝗻𝗼𝘁 𝘁𝗮𝗸𝗶𝗻𝗴 𝗶𝗻 2026 Introduction to Generative AI: imp.i384100.net/Vxn5XM Google AI Specialization https://lnkd.in/gTES4qvm Google Prompting Essentials Specialization: https://lnkd.in/gS-UFMpd Crash Course for Python https://lnkd.in/eNPZE74F Google Cloud Fundamentals https://lnkd.in/eMbczkqy IBM Python for Data Science https://lnkd.in/gg2i4Wn4 IBM Full Stack Software Developer https://lnkd.in/ga_H7C9A IBM Introduction to Web Development with HTML, CSS, JavaScript https://lnkd.in/gseSxSqx IBM Back-End Development https://lnkd.in/g7XQmshE Full Stack Developer https://lnkd.in/g36hihS2 Data Structures and Algorithms (DSA) https://lnkd.in/gYvwwsp9 Machine Learning https://lnkd.in/grm6JQEa Deep Learning https://lnkd.in/gjGvcVjM Python for Data Science https://lnkd.in/gg2i4Wn4 Web Developers https://lnkd.in/gxH5J4pC Java Programming https://lnkd.in/gbTsiBsd Cloud Computing https://lnkd.in/gec-FCm9 All credit goes to the original creator.

📘 NodeJS Handwritten Notes Sharing my handwritten notes on NodeJS, created to explain backend development concepts in a simple and structured way. Covers Node basics, core modules, npm, Express fundamentals, REST APIs, and asynchronous programming. Ideal for beginners, revision, and interview preparation. Here is unlimited access to 7,000+ top-tier courses🚀 imp.i384100.net/xLBzBA 𝗚𝗼𝗼𝗴𝗹𝗲 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝘆𝗼𝘂 𝘄𝗶𝗹𝗹 𝗿𝗲𝗴𝗿𝗲𝘁 𝗻𝗼𝘁 𝘁𝗮𝗸𝗶𝗻𝗴 𝗶𝗻 2026 Introduction to Generative AI: imp.i384100.net/Vxn5XM Google AI Specialization https://lnkd.in/gTES4qvm Google Prompting Essentials Specialization: https://lnkd.in/gS-UFMpd Crash Course for Python https://lnkd.in/eNPZE74F Google Cloud Fundamentals https://lnkd.in/eMbczkqy IBM Python for Data Science https://lnkd.in/gg2i4Wn4 IBM Full Stack Software Developer https://lnkd.in/ga_H7C9A IBM Introduction to Web Development with HTML, CSS, JavaScript https://lnkd.in/gseSxSqx IBM Back-End Development https://lnkd.in/g7XQmshE Full Stack Developer https://lnkd.in/g36hihS2 Data Structures and Algorithms (DSA) https://lnkd.in/gYvwwsp9 Machine Learning https://lnkd.in/grm6JQEa Deep Learning https://lnkd.in/gjGvcVjM Python for Data Science https://lnkd.in/gg2i4Wn4 Web Developers https://lnkd.in/gxH5J4pC Java Programming https://lnkd.in/gbTsiBsd Cloud Computing https://lnkd.in/gec-FCm9 All credit goes to the original creator.

DISTRIBUTED SYSTEM? It’s not that deep.  There’s a term that keeps coming up in tech conversations: Distributed Systems. But when is a system actually distributed? Let’s say I build a simple project: -- Frontend → React -- Backend → Python + Django -- Database → Postgres or MySQL Could that be a distributed system? It depends. If everything runs on the same machine (same VM, same laptop), that’s not really a distributed system. This can be called a monolith with clearly separated layers. Now if you change just one thing such as deploying the React frontend separately (CDN or hosting service), the Django backend on its own server, and the database on another. Suddenly: -- Requests travel across networks -- Latency becomes a real deal -- CORS, retries, and timeouts matter -- One part can fail without taking everything down The moment your system can fail in more than one place independently, you are building a distributed system. Now when scalability gets into the conversation, a distributed system becomes even more complex, but that is a subject for another conversation. 

Stop memorizing syntax. Start learning Architecture. 🏗️ In my 5+ years as a Software Engineer, I’ve seen too many developers get stuck in the "Tutorial Loop" of learning frameworks. But if you want to move from "Coder" to "Engineer" (or build scalable SaaS products), your roadmap needs to change. Here is the technical hierarchy that actually matters: (1) The Foundation (Beyond Basics) It’s not just about knowing PHP or Node.js. It’s about how you structure them. • OOP (Object-Oriented Programming) • SOLID Principles (This is non-negotiable) • Design Patterns (Singleton, Factory, Strategy) (2) The Data Layer Don’t just "store" data. Design it. • Database Normalization • Complex Queries & Indexing • Caching Strategies (Redis) (3) The Architecture This is where the real scale happens. • RESTful APIs vs. GraphQL • Microservices Architecture • Message Queues (RabbitMQ/Kafka) (4) The "Invisible" Skills • Debugging without console.log • Writing clean, maintainable documentation • Understanding the business logic behind the code Frameworks like Laravel or Express are just tools. The engineering is in how you use them to solve problems. 👇 What’s one "advanced" concept that finally clicked for you recently? #BackendDeveloper #SoftwareEngineering #PHP #NodeJS #SystemDesign #Coding #FrameWorks #Learning #Programming #RoadMap

Backend Developer Skills – What You Really Need to Master 🚀 Backend development is more than writing APIs. It’s about performance, security, scalability, and clean architecture. This infographic highlights the core skill areas every backend developer should know: 🔹 Programming Languages JavaScript, Python, Java, PHP 🔹 Frameworks Node.js, Django, Laravel, Spring Boot 🔹 Databases PostgreSQL, MySQL, Oracle, MongoDB 🔹 APIs REST, GraphQL, RPC, SOAP 🔹 Data Formats JSON (modern APIs), XML (legacy systems) 🔹 Tools Git & GitHub, Docker, Postman, VS Code 🔹 Security & Authentication JWT, OAuth2, Session Auth, Input Validation, Hashing 🔹 Performance & Scaling Redis, Memcached, Background Jobs, Rate Limiting 🔹 Architecture MVC, Clean Architecture, Microservices, Serverless If you’re preparing for backend interviews or aiming to become a senior backend engineer, this is your core checklist. Save this 📌 — backend fundamentals never go out of style. 📚 Recommended Backend Development Courses 🔗 IBM Full-Stack Cloud Developer Professional Certificate https://lnkd.in/dnEjYxhD 🔗 Software Design & Architecture https://lnkd.in/dsBbkH-w 🔗 System Design Fundamentals https://lnkd.in/dtbuHXyD 🔗 AI-Powered System Design https://lnkd.in/d_szZHSf Strong backend engineers build systems that scale — not just code that works.

🚀 Building Software That Actually Scales (Not Just Works) Over the years in software development, I’ve learned one important truth: Writing code is easy. Writing maintainable, scalable, and production-ready software is the real skill. Here’s what I focus on in every project I build: 🔹 Clean Architecture – separation of concerns, not spaghetti logic 🔹 Performance-first APIs – optimized queries, async execution, caching 🔹 Security by design – JWT, RBAC, device/session management 🔹 Real-world scalability – background jobs, queues, rate limits 🔹 Readable code – because future you is also a developer I mostly work with: Python (Django / FastAPI) Golang for high-performance services SQLAlchemy / PostgreSQL / MySQL Redis, Celery, WebSockets Algo-trading & real-time systems I enjoy solving problems where logic, performance, and reliability matter more than just “getting it to work”. If you’re building: ✅ Scalable backend systems ✅ Trading / real-time applications ✅ High-traffic APIs ✅ Clean, future-proof architectures Let’s connect and exchange ideas 🤝 Good software is built by thinking engineers, not just fast coders. #SoftwareDevelopment #BackendEngineering #PythonDeveloper #Golang #FastAPI #Django #SystemDesign #CleanCode #APIDevelopment #TechCareers

Big Tech and Go: main language or “special forces”? Yesterday I listed companies where Go is used in production - today the main question is: who actually uses Go as a main language (and who keeps it as a tool for specific jobs)? 𝗚𝗼𝗼𝗴𝗹𝗲 Plot twist: Go was created at Google, but it’s still not the main (only) language there. Google uses C++, Java, Python and Go. Go is important, but it lives alongside the big legacy stacks (and a lot of very serious C++). 𝗨𝗯𝗲𝗿 Go is one of the main backend languages (together with Java and Python). Great fit for microservices and real-time systems. 𝗡𝗲𝘁𝗳𝗹𝗶𝘅 Java is the main stack. Go appears where startup time, efficiency and network performance matter (infra, tooling, gateways). 𝗗𝗿𝗼𝗽𝗯𝗼𝘅 Python is the “home” language, but Go is used actively for performance-critical backend and distributed systems. 𝗧𝘄𝗶𝘁𝘁𝗲𝗿 (𝗫) Historically Scala and Java. Go is used for backend services and infrastructure tooling (especially where concurrency helps). 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 Main languages are C#, C++ and TypeScript. Go is used inside Azure and infrastructure/DevOps areas. 𝗔𝗺𝗮𝘇𝗼𝗻 (𝗔𝗪𝗦) Main languages are often Java, C++ and Python, but Go is important too (a lot of internal services and CLI/infrastructure tooling). 𝗬𝗮𝗻𝗱𝗲𝘅 Go is one of the main backend languages alongside C++ and Python. 𝗢𝘇𝗼𝗻 Go is one of the core backend languages (orders, payments, logistics). 𝗩𝗞 Go is one of the main backend languages alongside PHP (surprise!) and C++. 𝗪𝗶𝗹𝗱𝗯𝗲𝗿𝗿𝗶𝗲𝘀 Go is one of the main backend languages for high-load systems. 𝗧𝗶𝗻𝗸𝗼𝗳𝗳 Go is one of the key backend languages for APIs and financial services. Also: Docker and Kubernetes are written in Go - which is a pretty strong “resume line” for any language 😄 The general pattern looks the same almost everywhere: Go is used for microservices Go is used for infrastructure & DevOps tooling Go is used for high-load backend Go is used for real-time / network services 𝗖𝗼𝗻𝗰𝗹𝘂𝘀𝗶𝗼𝗻: Go is rarely the only language in Big Tech, but it’s often the key language when performance, predictability and deployability matter. #Day64 #golang #FromPHPtoGo

Over the past few weeks, I built my first complete backend system using Java + Spring Boot. It’s a blog platform backend with authentication, feed, likes, comments, profile updates, and image handling — deployed and running. Live Frontend: https://lnkd.in/gM2ZbtMA GitHub (Frontend): https://lnkd.in/gugq9MSS GitHub (Backend): https://lnkd.in/gDjDbvT3 What I focused on: • Stateless JWT authentication using Supabase • MongoDB denormalization for faster reads • Atomic $inc updates to prevent race conditions • Async background updates for profile image propagation • Retry mechanism for failure resilience • Cursor-based pagination • API latency measurement (P50 / P95 / P99) • Structured logging with trace IDs • Micrometer + Actuator for observability One interesting part was handling denormalized data correctly. When a user updates their profile picture, all their blogs and comments need to reflect that change. Instead of blocking the request, I handled it asynchronously with retries and eventual consistency — keeping reads fast while maintaining correctness. I also made sure likes and comment counters use atomic MongoDB operations to avoid race conditions under concurrent requests. This project helped me understand: How Spring Security filter chains work How JWT validation actually flows per request Why P95 latency matters more than average How infrastructure (free-tier deployments) impacts perceived performance How real backend systems think about tradeoffs It’s still a monolith, but structured cleanly with separation of concerns and performance awareness from the beginning. Not perfect — but intentionally designed. Open to feedback from backend engineers and anyone working with distributed systems. #Java #SpringBoot #BackendDevelopment #MongoDB #SystemDesign #Microservices #RESTAPI #SoftwareEngineering #JWT #Cloud #Micrometer #LearningInPublic