Modern yazılım geliştirme ekosisteminde altyapının kod olarak yönetilmesi hız ve ölçeklenebilirlik açısından devrim yaratırken GitOps yaklaşımı bu süreci merkezi bir doğruluk kaynağına bağlamaktadır. Ancak tüm yapılandırma detaylarının tek bir platformda toplanması kritik siber güvenlik risklerini de beraberinde getirmektedir. Nesil Teknoloji olarak TSE A Sınıfı sızma testi yetkimizle endüstriyel
Why This Topic Matters OTP (One-Time Password) verification is a critical security feature in modern mobile applications. Whether you're building a fintech app, healthcare platform, or any service requiring user authentication, implementing OTP verification efficiently can be the difference between a smooth user experience and frustrated users abandoning your app. The react-native-otp-auto-verif
Introduction Building a mobile application that handles sensitive financial data — crypto transactions, KYC verification, gift cards — means security is not an afterthought. It is a core deliverable. During the development of a cross-platform fintech application, one of the non-negotiables on the security checklist was runtime application self-protection (RASP). After evaluating our options, we
React Native's New Architecture — JSI, Fabric, and TurboModules — has been "coming soon" for long enough that some teams wrote it off as vaporware. It shipped. It is now default in new React Native projects. And it meaningfully changes how the framework works at the performance-critical boundaries between JavaScript and native code. This post is not a getting-started guide. It is an honest account
It's a one-line item on the roadmap. "Send a push notification when X happens." Estimate is two days, three if the backend doesn't have FCM credentials yet. There's a library for it. The library is the visible part. The other 90% is platform lifecycle, registration state machines, race conditions with navigation, payload archaeology, and a half-dozen iOS and Android quirks. Nobody writes them down
Hello Developers! 👋 Most developers today pick a side: Let’s talk about combining C++ and JavaScript—the ultimate hybrid stack for high-performance applications. 👇 1. The Core Engine (C++) ⚙️ 2. The Browser Bridge (WebAssembly) 🌉 3. The Cinematic Experience (Vanilla JS + UI/UX) ✨ The Takeaway 🎯 Keep optimizing, keep building! 💻✨ ~ Ujjwal Sharma | @stackbyujjwal About the Author 👨💻 Ujjwal
I built a Vamana-based vector search engine in C++ called sembed-engine. Recently I made a pull request that sped up queries by 16x and builds by 9x. The algorithm stayed exactly the same. The recall stayed at 1.0. The number of visited nodes did not change. The speedup came from data layout. The original code stored vectors as separate objects pointed to by shared_ptr: struct Record { int64_t
The first time I implemented Vamana from the DiskANN paper, my approximate nearest neighbor index was slower than brute force. On tiny test fixtures, brute force took 0.27 ms per query. My Vamana implementation took 22.98 ms. That sounds absurd. ANN exists to skip work. The problem was not the algorithm. It was how I mapped the paper's abstractions to actual data structures. The DiskANN pseudocode