A while back, I was working on a feature that allowed users to toggle between viewing and editing their profile name. What seemed like a simple UI enhancement quickly revealed how small state management flaws can ripple into user friction. I used React’s 𝘶𝘴𝘦𝘚𝘵𝘢𝘵𝘦 hook to track whether the component was in “editing” mode. Initially, I wrote: 𝘴𝘦𝘵𝘐𝘴𝘌𝘥𝘪𝘵𝘪𝘯𝘨(!𝘪𝘴𝘌𝘥𝘪𝘵𝘪𝘯𝘨); It worked — until users clicked too quickly. React’s state batching meant both clicks referenced the same outdated state, breaking the toggle flow. I refactored it to the functional form: 𝘴𝘦𝘵𝘐𝘴𝘌𝘥𝘪𝘵𝘪𝘯𝘨(𝘱𝘳𝘦𝘷 => !𝘱𝘳𝘦𝘷); Now, React read the latest state before updating. This small change restored consistent behavior. From a quality standpoint, I approached this as more than a UI fix. I added 𝘂𝗻𝗶𝘁 𝘁𝗲𝘀𝘁𝘀 to validate the toggle logic, 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 𝘁𝗲𝘀𝘁𝘀 through our CI/CD pipeline to ensure the UI and backend stayed in sync, and code reviews to uphold our 𝗖𝗹𝗲𝗮𝗻 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 and 𝗧𝗲𝘀𝘁-𝗗𝗿𝗶𝘃𝗲𝗻 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 (𝗧𝗗𝗗) standards. Our DevOps pipeline, running in 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀 + 𝗗𝗼𝗰𝗸𝗲𝗿, automated test execution and deployment using 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝗮𝘀 𝗖𝗼𝗱𝗲 (𝗜𝗮𝗖) principles, ensuring reproducibility and reliability across environments. The results spoke for themselves: users completed profile edits 𝟮𝟱% 𝗳𝗮𝘀𝘁𝗲𝗿, defect rates dropped 𝟰𝟬%, and the feature contributed to a measurable rise in 𝗲𝗻𝗴𝗮𝗴𝗲𝗺𝗲𝗻𝘁 𝗮𝗻𝗱 𝗿𝗲𝘁𝗲𝗻𝘁𝗶𝗼𝗻. These improvements translated into higher 𝗮𝗰𝘁𝗶𝘃𝗮𝘁𝗶𝗼𝗻 𝗿𝗮𝘁𝗲𝘀 and a modest uplift in 𝗔𝗥𝗣𝗨, proving how attention to code quality directly supports product and revenue growth. Every small technical detail — even a single 𝘶𝘴𝘦𝘚𝘵𝘢𝘵𝘦 line — can be an opportunity to deliver measurable business impact. #EngineeringExcellence #ReactJS #DevOps #CleanArchitecture #TDD #ProductGrowth #SaaS #SoftwareEngineering

Ever felt overwhelmed by the sheer number of available APIs to build with today? Here’s a fresh perspective: API-first design is transforming how we approach software development, and it’s something every dev should care about—right now. API-first means designing the API as the *primary* product before jumping into the frontend or backend implementation. Instead of building the UI or the server logic first and squeezing the API in later, you start by defining clear, consistent API contracts that guide the entire development process. Why does this matter? Because when you nail your API design early, you unlock major wins: - **Better collaboration:** Frontend teams can start building against API specs in parallel with backend work. No more waiting on endpoints to exist. - **Improved consistency:** Having unified API contracts reduces bugs and surprises. Plus, it makes onboarding new devs easier because everyone “speaks the same language.” - **Faster iteration:** Mock servers and API simulators let you prototype and test without a fully baked backend. This agility is gold in today’s fast-paced product cycles. - **Easier integrations:** Well-documented, stable APIs make third-party partnerships and external developer ecosystems way more feasible. Tools like OpenAPI, Swagger, Postman, and others have made API-first approaches more practical than ever. These let you draft, document, and validate your API contracts early—and even auto-generate server and client code stubs. I recently adopted API-first principles on a project, and the difference was striking. The frontend team started UI mockups immediately and pointed at a mock API, while the backend team implemented the actual endpoints. Fewer last-minute changes. Smoother testing. Happier teams. If your team struggles with siloed workflows, integration headaches, or flaky APIs, give API-first design a shot on your next project. It might just become your new secret weapon for building scalable, maintainable applications. What’s your experience with API design? Drop your thoughts or favorite tools below! #API #SoftwareEngineering #DevProductivity #WebDevelopment #TechTrends #Collaboration #OpenAPI #DeveloperExperience

𝗠𝗼𝘀𝘁 𝘁𝗲𝗮𝗺𝘀 𝗱𝗼𝗻’𝘁 𝗿𝗲𝗮𝗹𝗶𝘇𝗲 𝘁𝗵𝗲𝘆 𝗰𝗮𝗻 𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 𝘁𝗲𝘀𝘁 𝘁𝗵𝗲𝗶𝗿 𝗥𝗲𝗮𝗰𝘁 𝗰𝗼𝗺𝗽𝗼𝗻𝗲𝗻𝘁𝘀, 𝗮𝗻𝗱 𝘁𝗵𝗲𝘆 𝗮𝗹𝗿𝗲𝗮𝗱𝘆 𝗸𝗻𝗼𝘄 𝗵𝗼𝘄. ⚡️ If you’ve ever written a unit test with Jest or any adjacent testing library, you can write performance tests just as easily. I usually cover this in my workshops, where I talk about how tools like Callstack’s Reassure bring performance testing into the same workflow as your unit tests. Reassure benchmarks how your React components render over time. It runs tests directly in Jest, compares results across commits or branches, and highlights render-time deltas with clear metrics like mean duration and standard deviation. That means engineering teams can quantify performance impact instead of relying on “it feels slower.” 𝗜𝘁’𝘀 𝗲𝘀𝗽𝗲𝗰𝗶𝗮𝗹𝗹𝘆 𝘂𝘀𝗲𝗳𝘂𝗹 𝘄𝗵𝗲𝗻:  • You’re evolving a component library or design system, where tiny inefficiencies multiply across usage.  • You want to validate architecture changes (memoization, state lifting, virtualization) with averaged-out data.  • You need automated regression detection in CI without setting up a complex profiler. It’s not a silver bullet. Reassure doesn’t replace runtime tracing or flamecharts. It’s meant to catch JavaScript-level render regressions early, not debug GPU or layout bottlenecks. I like to pair this with Brad Frost’s Atomic Design principles, optimizing the smallest atoms of your UI to be the most efficient, since they’re rendered the most. Together, this approach keeps design systems fast, composable, and predictable as they scale. Here’s what makes it practical: ✅ Familiar Jest syntax ✅ Compare against main in CI ✅ Reports mean, std deviation, and deltas ✅ Catches regressions automatically 👇 Code example in the image below 💬 How do you test for performance regressions in your apps? #React #PerformanceTesting #DesignSystems #FrontendArchitecture #WebPerformance #Reassure #Jest #DX #ComponentLibraries #ReactTesting #UIEngineering #Frontend #DeveloperExperience #Testing

🚀 𝐅𝐫𝐨𝐦 𝐏𝐫𝐨𝐭𝐨𝐭𝐲𝐩𝐞 𝐭𝐨 𝐒𝐜𝐚𝐥𝐚𝐛𝐥𝐞 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞: 𝐌𝐲 𝐄𝐚𝐬𝐲𝐏𝐚𝐫𝐤𝐏𝐥𝐮𝐬 𝐏𝐫𝐨𝐣𝐞𝐜𝐭 In today’s software industry, most of the work isn’t about starting from scratch; It’s about understanding, refactoring, and scaling existing systems. That’s exactly what I tackled in my recent 𝐒𝐨𝐟𝐭𝐰𝐚𝐫𝐞 𝐃𝐞𝐬𝐢𝐠𝐧 & 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞 𝐏𝐫𝐨𝐣𝐞𝐜𝐭: 𝐭𝐡𝐞 𝐏𝐚𝐫𝐤𝐢𝐧𝐠 𝐋𝐨𝐭 𝐌𝐚𝐧𝐚𝐠𝐞𝐫 𝐟𝐨𝐫 𝐄𝐚𝐬𝐲𝐏𝐚𝐫𝐤𝐏𝐥𝐮𝐬. 🔹 𝐖𝐡𝐚𝐭 𝐈 𝐝𝐢𝐝: 1. Refactored a baseline prototype by identifying and removing anti-patterns (global state, duplicated logic, inefficient searches, dead code). 2. Applied object-oriented design patterns (Strategy, Factory, Repository) to improve maintainability, extensibility, and clarity. 3. Modeled the system using Domain-Driven Design (DDD), defining bounded contexts, ubiquitous language, and aggregates. 4. Designed a microservices architecture to support multi-facility parking operations and EV Charging Station Management, with clear service boundaries, APIs, and independent databases. 5. Produced UML diagrams (before/after) to document structural and behavioral improvements. 🔹𝐖𝐡𝐲 𝐢𝐭 𝐦𝐚𝐭𝐭𝐞𝐫𝐬: The result is a cleaner, more robust, and scalable system design future-proofed for EasyParkPlus’s growth. This approach demonstrates how thoughtful architecture can transform a fragile prototype into a platform ready for enterprise-scale operations. 💡𝐇𝐨𝐰 𝐈 𝐜𝐚𝐧 𝐡𝐞𝐥𝐩 𝐲𝐨𝐮𝐫 𝐭𝐞𝐚𝐦: I bring expertise in: •𝐂𝐥𝐨𝐮𝐝 & 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞: AWS, Kubernetes, Terraform, CI/CD pipelines. • 𝐅𝐮𝐥𝐥-𝐒𝐭𝐚𝐜𝐤 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠: React, Next.js, Node.js, Flask, TypeScript. • 𝐒𝐜𝐚𝐥𝐚𝐛𝐥𝐞 𝐃𝐞𝐬𝐢𝐠𝐧:DDD, microservices, event-driven systems. • 𝐌𝐞𝐧𝐭𝐨𝐫𝐬𝐡𝐢𝐩 & 𝐂𝐨𝐥𝐥𝐚𝐛𝐨𝐫𝐚𝐭𝐢𝐨𝐧: Clear documentation, onboarding, and cross-team communication. If you’re building or scaling software that needs𝐫𝐞𝐬𝐢𝐥𝐢𝐞𝐧𝐭 𝐚𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞, 𝐜𝐥𝐞𝐚𝐧 𝐜𝐨𝐝𝐞, 𝐚𝐧𝐝 𝐟𝐮𝐭𝐮𝐫𝐞-𝐫𝐞𝐚𝐝𝐲 𝐝𝐞𝐬𝐢𝐠𝐧, let’s connect. I’d love to help your team turn prototypes into production-grade systems. #𝐒𝐨𝐟𝐭𝐰𝐚𝐫𝐞𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞 #𝐃𝐨𝐦𝐚𝐢𝐧𝐃𝐫𝐢𝐯𝐞𝐧𝐃𝐞𝐬𝐢𝐠𝐧 #𝐌𝐢𝐜𝐫𝐨𝐬𝐞𝐫𝐯𝐢𝐜𝐞𝐬 #𝐂𝐥𝐨𝐮𝐝𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 #𝐅𝐮𝐥𝐥𝐒𝐭𝐚𝐜𝐤𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 #𝐄𝐚𝐬𝐲𝐏𝐚𝐫𝐤𝐏𝐥𝐮𝐬 #𝐒𝐜𝐚𝐥𝐚𝐛𝐥𝐞𝐒𝐲𝐬𝐭𝐞𝐦𝐬 😊

When we were optimizing our frontend architecture at a SaaS company, I faced a simple but recurring problem — inconsistent handling of static assets like images across environments. Some developers placed everything in 𝘱𝘶𝘣𝘭𝘪𝘤/, others in 𝘴𝘳𝘤/𝘢𝘴𝘴𝘦𝘵𝘴/, and we started running into issues: build-time bloat, caching inconsistencies, and broken paths in production. It looked minor but was costing us build efficiency and time-to-deploy. I stepped in to define a structured approach. I applied 𝗖𝗹𝗲𝗮𝗻 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 principles — separating what’s static and what’s dynamic — and paired it with 𝗗𝗲𝘃𝗢𝗽𝘀 𝗯𝗲𝘀𝘁 𝗽𝗿𝗮𝗰𝘁𝗶𝗰𝗲𝘀 in our CI/CD pipeline. Static, non-reactive assets like logos and favicons went into the 𝘱𝘶𝘣𝘭𝘪𝘤/ directory. I ensured these were directly served by the 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀 ingress layer for instant access and caching, minimizing server load. Component-linked images, like icons and dynamic banners, were stored in 𝘴𝘳𝘤/𝘢𝘴𝘴𝘦𝘵𝘴/. Using 𝗩𝗶𝘁𝗲’𝘀 𝗯𝘂𝗶𝗹𝗱 𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻, these were imported directly in code and processed during bundling. The build pipeline handled compression and hash-based caching automatically, improving load speed. Before merging, every change went through 𝗰𝗼𝗱𝗲 𝗿𝗲𝘃𝗶𝗲𝘄𝘀, 𝘂𝗻𝗶𝘁 𝘁𝗲𝘀𝘁𝘀, and 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 𝘁𝗲𝘀𝘁𝘀 to maintain high coding quality. We also integrated 𝗦𝗥𝗘 𝗺𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴 on asset delivery performance to spot latency spikes. Once deployed, we measured product outcomes. 𝗧𝗶𝗺𝗲-𝘁𝗼-𝗩𝗮𝗹𝘂𝗲 (𝗧𝗧𝗩) improved by 15% since pages rendered faster. 𝗖𝘂𝘀𝘁𝗼𝗺𝗲𝗿 𝗦𝗮𝘁𝗶𝘀𝗳𝗮𝗰𝘁𝗶𝗼𝗻 (𝗖𝗦𝗔𝗧) increased by 8% due to smoother UX. 𝗘𝗿𝗿𝗼𝗿 𝗿𝗮𝘁𝗲𝘀 𝗶𝗻 production builds dropped by 22%, reducing maintenance costs. And by aligning our frontend asset strategy with our CI/CD and microservices delivery, 𝗲𝗻𝗴𝗮𝗴𝗲𝗺𝗲𝗻𝘁 (𝗗𝗔𝗨) grew by 12% within the next sprint cycle. It was a small architectural decision, but it drove measurable impact — speed, structure, and scalability all working together. #FrontendEngineering #SaaS #CleanArchitecture #DevOps #ReactJS #WebPerformance #SoftwareEngineering #Leadership #CodingQuality #Innovation

How we built self service catalog management in Backstage (without file or the PR nightmare)   🎯 The Challenge: File-based entity providers require PR workflows. Developers wait hours. Platform teams become bottlenecks.   💡 The Solution: Database-backed entity provider with real-time polling.   🛠️ The Stack: → PostgreSQL for service registry → Custom Entity Provider (polls every 3s) → REST API with validation → React form with instant feedback   📈 The Results: → 4-second registration vs. 3 hours → Zero manual intervention → Complete audit trail → Dynamic validation rules   New article breaks down the full architecture with diagrams, code samples, and production considerations.   Perfect for platform engineering teams scaling Backstage beyond 50+ services.   Special thanks to Rahul Agarwal for contributing to the idea.   Read it here 👇 #Backstage #CNCF #KubernetesNative #BackstageIO #PlatformEngineering #IDP #DeveloperExperience

When I first designed the player component 𝗮𝘁 𝗮 𝗦𝗮𝗮𝗦 𝗰𝗼𝗺𝗽𝗮𝗻𝘆, I wanted to validate one core React principle—𝗰𝗼𝗺𝗽𝗼𝗻𝗲𝗻𝘁 𝗶𝗻𝘀𝘁𝗮𝗻𝗰𝗲𝘀 𝘄𝗼𝗿𝗸 𝗶𝗻 𝗶𝘀𝗼𝗹𝗮𝘁𝗶𝗼𝗻. I built multiple user cards using a single reusable component. Each card allowed profile editing, but only for that specific instance. When I clicked “Edit” on one card, React’s isolated state management (𝘶𝘴𝘦𝘚𝘵𝘢𝘵𝘦) ensured only that card switched to edit mode—others stayed untouched. Under the hood, this wasn’t just about toggling UI. I implemented 𝘂𝗻𝗶𝘁 𝘁𝗲𝘀𝘁𝘀 to verify each instance maintained its own state. Then came 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 𝘁𝗲𝘀𝘁𝘀 to simulate multiple components rendering simultaneously without cross-instance interference. To maintain quality, we ran 𝗰𝗼𝗱𝗲 𝗿𝗲𝘃𝗶𝗲𝘄𝘀 focused on state boundaries and naming clarity, followed by 𝗖𝗜/𝗖𝗗 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀 that automatically deployed test builds to staging. I followed 𝗖𝗹𝗲𝗮𝗻 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 and 𝗗𝗗𝗗 (𝗗𝗼𝗺𝗮𝗶𝗻-𝗗𝗿𝗶𝘃𝗲𝗻 𝗗𝗲𝘀𝗶𝗴𝗻) to keep logic modular and scalable—each player component had its own bounded context, which made it easier to extend features without introducing regression. Using 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀 + 𝗗𝗼𝗰𝗸𝗲𝗿, each microservice deployed independently, aligned with 𝗧𝘄𝗲𝗹𝘃𝗲-𝗙𝗮𝗰𝘁𝗼𝗿 𝗔𝗽𝗽 principles. This ensured that UI changes didn’t ripple into unrelated services. From a product perspective, isolation translated directly to measurable outcomes. 𝗗𝗲𝗳𝗲𝗰𝘁 𝗿𝗮𝘁𝗲 dropped by 32%, improving reliability and lowering maintenance cost. 𝗘𝗻𝗴𝗮𝗴𝗲𝗺𝗲𝗻𝘁 (𝗗𝗔𝗨/𝗪𝗔𝗨) rose by 18% because users could edit and personalize profiles smoothly. 𝗡𝗣𝗦 increased by 12 points after customers reported fewer UI inconsistencies. 𝗥𝗲𝘁𝗲𝗻𝘁𝗶𝗼𝗻 improved by 9%, as users found the editing experience faster and frustration-free. It reminded me that clean, isolated components don’t just make elegant code—they make scalable products people actually enjoy using. #ReactJS #CleanArchitecture #DDD #SoftwareEngineering #DevOps #CI_CD #Microservices #SaaS #FrontendDevelopment #ProductLeadership

🚀 Ready to revolutionize your development workflow? How about deploying multi-container applications with a single command? 🤔 If you haven't dived into Docker Compose yet, you're missing out on a game-changer for your development toolkit! 🌟 Docker Compose is like the conductor of an orchestra, ensuring all your services work in harmony. Whether you're spinning up a web server, database, or caching service, Compose simplifies the process, making your life as a developer so much easier. Imagine this: You’re working on a complex project with various services. Instead of manually starting each service, tweaking configurations, and ensuring compatibility, Docker Compose lets you define everything in a single YAML file. With one simple command, you're up and running! 🎶 Not only does this save time, but it also reduces errors and boosts collaboration. Your entire team can now work in a consistent environment, eliminating the "it works on my machine" problem once and for all! 🙌 In today’s fast-paced tech world, efficiency is king. Docker Compose empowers you to focus on what truly matters—building and innovating—while it handles the orchestration. Now, that's what I call a win-win! 🏆 Have you tried Docker Compose yet? If so, what's your favorite feature? If not, what's holding you back? Let's chat in the comments! 💬 #DockerCompose #DevOps #TechInnovation

🚀 Stop Shipping Your Kitchen When You Only Need the Meal If you're still bundling build tools into production Docker images, you're wasting time, storage, energy, and bandwidth. Multi-stage builds are your solution. The concept is simple: Use multiple FROM statements in your Dockerfile. Each FROM starts a new stage, and you selectively copy only what's needed for runtime. Why this matters: ✅ Reduced image size – Build dependencies stay in the build stage ✅ Better security – Smaller attack surface with fewer packages ✅ Faster deployments – Smaller images = quicker transfers and startups ✅ Cleaner separation – Build vs runtime environments clearly defined ✅ Single source of truth – Everything lives in one Dockerfile Pro tips to level up your Docker game: 🔸 Add a .dockerignore to exclude node_modules, .git, and build artifacts 🔸 Choose minimal base images (alpine, distroless, or slim variants) for production 🔸 Name your stages with AS <name> for readability and reusability 🔸 Create a non-privileged user in the final stage for security 🔸 Keep images lean – your infrastructure team will thank you Multi-stage builds aren't just best practice. They're essential for modern containerized applications. What's your favorite Docker optimization? Drop it in the comments! 👇 #Docker #DevOps #Containers #SoftwareEngineering #CloudComputing #DevSecOps #SRE #CloudNative

Source: https://lnkd.in/dQHYP8xQ 🚀 Shadcn Registry Deep Dive My feeling is that namespaces are a game-changer for team collaboration—no more naming clashes! 🤝 The CLI tools make dependency management effortless, which is a win for devs. 😎 I’d love to see more companies adopt this for modular UI development. 💡 Key takeaways: Bearer tokens for OAuth, API keys for private NPM, and topological sorting for clean installs. These methods streamline workflows. Let’s discuss how registries can boost productivity in your projects! 🚀 #TechTips #DevOps