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@kaptain shared a link, 1 month ago
FAUN.dev()

A Deep Dive into Kubernetes Headless Service

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  

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@jamesmiller shared a post, 1 month ago

Automating Penetration Testing in CI/CD: A Practical Guide for Developers

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Automating pentesting in CI/CD helps developers catch vulnerabilities early, reduce MTTR, and keep releases secure without slowing the pipeline. This guide breaks down why automation matters, the tools developers rely on, common mistakes to avoid, and practical steps to build a reliable pentesting workflow inside modern CI/CD pipelines.

Automating Penetration Testing in CI/CD
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@elenamia shared a post, 1 month ago
Technical Consultant, Damco Solutions

Google Cloud Services: A Comprehensive Overview for Modern Businesses

Read this blog to learn about Google Cloud Platform services and its key features, pricing, and use cases across industries.

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@kala shared a link, 1 month ago
FAUN.dev()

How to Create an Effective Prompt for Nano Banana Pro

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  

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@kala shared a link, 1 month ago
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So you wanna build a local RAG?

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  

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@kala shared a link, 1 month ago
FAUN.dev()

Learning Collatz - The Mother of all Rabbit Holes

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  

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@kala shared a link, 1 month ago
FAUN.dev()

200k Tokens Is Plenty

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  

200k Tokens Is Plenty
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@kala shared a link, 1 month ago
FAUN.dev()

Google tests new Gemini 3 models on LM Arena

Google’s been quietly field-testing two shadow models,Fierce FalconandGhost Falcon, on LM Arena. Early signs? They're probably warm-ups for the next Gemini 3 Flash or Pro drop. Classic Google move: float a checkpoint, stir up curiosity, then go GA... read more  

Google tests new Gemini 3 models on LM Arena
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@kala shared a link, 1 month ago
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Prompts for Open Problems

The author, Ben Recht, proposes five research directions inspired by his graduate machine learning class, arguing for different research rather than just more. These prompts include adopting a design-based view for decision theory, explaining the robust scaling trends in competitive testing, and mov.. read more  

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@kala shared a link, 1 month ago
FAUN.dev()

A trillion dollars is a terrible thing to waste

OpenAI co-founder Ilya Sutskever just said the quiet part out loud: scaling laws are breaking down. Bigger models aren’t getting better at thinking, they’re getting worse at generalizing and reasoning. Now he’s eyeingneurosymbolic AIandinnate inductive constraints. Yep, the “just make it huge” era m.. read more  

A trillion dollars is a terrible thing to waste
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.