kubectl Hacks That Changed How I Work With Kubernetes Selma Guedidi Apr 29 #kubernetes #containers #devops #automation 1 reaction Add Comment 12 min read
Kubernetes Multi-Tenancy: Namespace Isolation, RBAC, and Network Policies Explained Most teams running shared Kubernetes clusters believe they have isolation. They have namespaces. They have different teams deploying to different namespaces. It feels like separation. It is not. Kubernetes was designed as a single-tenant system. Multi-tenancy is not a built-in feature. It is a property you constr
This week, I was updating the image of a FastAPI app in our Kubernetes cluster, but I took the whole app down because the process failed due to an incompatible dependency with our server. The updated pod was unable to start, but we didn't have health checks in place, so the deployment continued to update the other replicas, taking down all app instances. In this tutorial, I will explain how to add
The Kubernetes community's announcement of Ingress NGINX's retirement in March 2026 has created an urgent need for migration planning across thousands of production clusters. With no security patches, bug fixes, or updates coming after the final v1.15.1 release, organizations must act now to avoid running unmaintained software with escalating security risks. This isn't just about swapping one ingr
Kubernetes and AI have become unlikely bedfellows—and the numbers prove it. New data from CNCF and SlashData reveals that two-thirds of organizations running generative AI models have standardized on Kubernetes for orchestration. But here's the thing: it's not because Kubernetes magically solves AI problems. It's because the engineering fundamentals that make Kubernetes valuable—standardization, r
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