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@kaptain shared a link, 2 weeks, 6 days ago
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v1.36: In-Place Vertical Scaling for Pod-Level Resources Graduates to Beta

Kubernetes v1.36 moves In-Place Pod-Level Resources Vertical Scaling to Beta and flips the feature gate on by default. Operators can patch a Pod's aggregate resource to resize running Pods. Often no container restart is needed. Kubelet breaks the Pod-level change into per-container resize events. It.. read more  

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@kaptain shared a link, 2 weeks, 6 days ago
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From Ingress NGINX to Higress: migrating 60+ resources in 30 minutes with AI

With the March 2026 retirement ofIngress NGINX, teams face an urgent compliance mandate. They must replace unpatched controllers. EnterHigress. Built onEnvoyandIstio. It unifies LLM protocols, enforces token rate limits, caches prompts, hostsMCP, and usesxDSfor zero-downtime. AnAI agentpaired withhi.. read more  

From Ingress NGINX to Higress: migrating 60+ resources in 30 minutes with AI
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@kaptain shared a link, 2 weeks, 6 days ago
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v1.36: Staleness Mitigation and Observability for Controllers

Kubernetes v1.36 shipsclient-goatomicFIFOprocessing and cache-introspection APIs. Controllers detect stale informer state and skip acting on it. kube-controller-managerenables the capability by default for four high-contention pod controllers. It addsalpha metricsfor skipped syncs and informer resou.. read more  

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@kaptain shared a link, 2 weeks, 6 days ago
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Auto-Diagnosing Kubernetes Alerts with HolmesGPT and CNCF Tools

STCLab built an AI investigation pipeline withHolmesGPT, a 200-linePythonplaybook, andOpenTelemetry. It streamedMimir,Loki, andTempointo Slack threads. Metadata-driven markdownrunbookslimited tools per namespace, cut wasted tool calls from 16 to 2, and let the same model resolve alerts faster... read more  

Auto-Diagnosing Kubernetes Alerts with HolmesGPT and CNCF Tools
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@kala shared a link, 2 weeks, 6 days ago
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Introducing the Agent Readiness score. Check to see if your site is agent-ready

Cloudflare launchedIsItAgentReady. It scans200kdomains, scoresagent readiness, publishes weekly adoption charts, and exposes results via anAPI. It checksrobots.txt,llms.txt, content negotiation viaAccept: text/markdown,API Catalog,.well-known/mcp.json, OAuth discovery, andx402payments. Cloudflare ov.. read more  

Introducing the Agent Readiness score. Check to see if your site is agent-ready
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@kala shared a link, 2 weeks, 6 days ago
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Multi-Agent System Reliability

LLMs are unreliable out of the box, but multi-agent systems can improve by dividing work among specialized agents. Building robust systems involves leveraging human system patterns like hierarchy, consensus, adversarial debate, and knock-out in a multi-agent architecture to ensure correctness and re.. read more  

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@kala shared a link, 2 weeks, 6 days ago
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Monitoring LLM behavior: Drift, retries, and refusal patterns

Traditional software is predictable due to determinism, while generative AI is unpredictable. Engineers need a new infrastructure layer, the AI Evaluation Stack, to ship enterprise-ready AI products. The stack includes deterministic assertions and model-based assertions to ensure structural integrit.. read more  

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@kala shared a link, 2 weeks, 6 days ago
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An open-weights Chinese model just beat Claude, GPT-5.5, and Gemini in a programming challenge

The AI Coding Contest Day 12 matched ten models on a sliding‑letter puzzle. Open‑weightsKimi K2.6took first: 22 match points (7‑1‑0).MiMo V2‑Proscored second by blasting claims for intact ≥7‑letter seeds (43 points).GPT‑5.5andClaude Opus 4.7landed third and fifth. Grids ran10×10→30×30. Heavy scrambl.. read more  

An open-weights Chinese model just beat Claude, GPT-5.5, and Gemini in a programming challenge
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@kala shared a link, 2 weeks, 6 days ago
FAUN.dev()

The AI engineering stack we built internally - on the platform we ship

Cloudflare wired AI into the engineering stack. LLM traffic funnels through aproxy WorkerandAI Gateway. It shippedWorkers AIand theAgents SDK. Daily users hit 3,683 (93% R&D). MR throughput climbed to ~10,952/week.Workers AIhandled 51B input tokens and cut a security agent's inference spend by 77%... read more  

The AI engineering stack we built internally - on the platform we ship
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@devopslinks shared a link, 2 weeks, 6 days ago
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How incidents can teach us about what’s already working well

A famous optical illusion developed by Edward H. Adelson shows that two squares, despite appearing different in shade, are actually the same gray. This illusion demonstrates how the brain processes light, shadow, and objects when interpreting visual signals from the optic nerve. Studying such illusi.. read more  

How incidents can teach us about what’s already working well
FAUN.dev() is a developer-first platform built with a simple goal: help engineers stay sharp without wasting their time. It curates practical newsletters, thoughtful technical blogs, and useful developer tools that focus on signal over noise.

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If it’s on FAUN.dev(), it’s worth your attention.

Beyond curation, we run a course marketplace (WIP) designed to keep developers current. These courses go deep into the subjects that shape real-world work—things like Kubernetes internals, modern DevOps workflows, cloud-native architecture, and using AI tools to build faster and smarter. It’s practical learning, taught by people who’ve done the work. Developers from companies like GitHub, Netflix, and Shopify already rely on FAUN.dev() to stay on top of their game. They trust us because we keep it real: no hype, no filler, just what you need to grow and do your best work. For sponsors and partners, FAUN.dev() offers access to a focused, engaged audience of technical professionals. This isn’t just another broad developer community—it’s a place where smart engineers go to get smarter. If you have something meaningful to offer them, you’ll be in good company. In short, FAUN.dev() is more than a content hub. It’s a place to grow, to learn, and to connect with what really matters in software today.