A fresh Kubernetes troubleshooting guide lays out real-world tactics for tracking down 12 common cluster headaches. Think:kubectlsleuthing, poking through system logs, scraping observability metrics, and jumping intodebug containers. The guide breaks down howAIOpsis stepping in, digesting event data.. read more  

Headless Serviceis a powerfulKubernetesfeature enabling direct pod-to-pod communication forstateful applicationsand preciseservice discoverywithout traditional load balancing.No automatic load balancing, pod IP changes, andspecial use casesmake it ideal for specific scenarios, not general workloads... read more  

Kubernetes 1.35 is done with legacy baggage. cgroups v1? Deprecated. Image pull credentials? Now re-verified by default—no more freeloading. kubectl SPDY API upgrades? Locked down. You’ll needcreatepermissions just to speak the protocol. Expect breakage if your workflows leaned on old assumptions. U.. read more  

vCluster, a CNCF sandbox project, spins up real-deal Kubernetes control planes inside pods. Each lives in its own namespace but behaves like a full cluster, admin access, CRDs, Helm, the works. It reuses the host’s worker nodes using a syncer that routes vCluster workloads onto the real thing... read more  

The author details how to effectively prompt Google’s Nano Banana Pro, a visual reasoning model, emphasizing that success relies on structured design documents rather than vague requests. The method prioritizes four key steps: defining the Work Surface (e.g., dashboard or comic), specifying the prec.. read more  

Skald spun up a full local RAG stack, withpgvector,Sentence Transformers,Docling, andllama.cpp, in under 10 minutes. The thing hums on English point queries. Benchmarks show open-source models and rerankers can go toe-to-toe with SaaS tools in most tasks. They stumble, though, on multilingual prompt.. read more  

Researchers trained small transformer models to predict the "long Collatz step," an arithmetic rule for the infamous unsolved Collatz conjecture, achieving surprisingly high accuracy up to 99.8%. The models did not learn the universal algorithm, but instead showed quantized learning, mastering speci.. read more  

Amp’s team isn’t chasing token limits. Even with ~200k available via Opus 4.5, they stick toshort, modular threads, around 80k tokens each. Why? Smaller threads are cheaper, more stable, and just work better. Instead of stuffing everything into a single mega-context, they slice big tasks into focuse.. read more