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Kubernetes Configuration Good Practices

Stripped down and sharp, the blog lays out Kubernetes config best practices: keep YAML manifests in version control, use Deployments (not raw Pods), and label like you mean it - semantically, not just alphabet soup. It digs into sneaky pain points too, like how YAML mangles booleans (yes≠true), and .. read more  

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@kaptain shared a link, 2 weeks, 6 days ago
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You Want Microservices—But Do You Need Them?

Amazon Prime Video ditched its pricey microservices maze and rebuilt as asingle-process monolith, cutting ops costs by 90%. No big press release. Just results. Same move from Twilio Segment. And Shopify. Both pulled their tangled systems back intomodular monoliths- cleaner, faster, easier to test, a.. read more  

You Want Microservices—But Do You Need Them?
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@kaptain shared a link, 2 weeks, 6 days ago
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Turning Kubernetes Last Access to Kubernetes Least Access Using KIEMPossible

KIEMPossible is a new open-source tool for Kubernetes entitlement cleanup. It maps out who has access to what - roles, entities, permissions - and shows how those are actually used across your clusters. Think of it as a permission microscope for AKS, EKS, GKE, and even the DIY K8s crowd. It breaks d.. read more  

Turning Kubernetes Last Access to Kubernetes Least Access Using KIEMPossible
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@kala shared a link, 2 weeks, 6 days ago
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How I Built a 100% Offline “Second Brain” for Engineering Docs using Docker & Llama 3 (No OpenAI)

Senior Automation Engineer built an offline RAG system for technical documents using Ollama, Llama 3, and ChromaDB in a Dockerized microservices architecture. The system enables efficient retrieval and generation of information from PDFs with a streamlined UI. The deployment package, including compl.. read more  

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@kala shared a link, 2 weeks, 6 days ago
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How to Evaluate LLMs Without Opening Your Wallet

A new mock-based framework lets QA and automation folks stress-test LLM outputs - no API calls, no surprise charges. It runs entirely local, usingpytest fixtures, structured test flows, and JSON schema checks to keep things tight. Test logic stays modular. Cross-validation’s baked in. And if you nee.. read more  

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@kala shared a link, 2 weeks, 6 days ago
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I tested ChatGPT’s backend API using RENTGEN, and found more issues than expected

A closer look at OpenAI’s API uncovers some shaky ground: misconfiguredCORS headers, missingX-Frame-Options, noinput validation, and borkedHTTP status handling. Large uploads? Boom..crash!CORS preflightrequests? Straight-up denied. So much for smooth browser support... read more  

I tested ChatGPT’s backend API using RENTGEN, and found more issues than expected
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@kala shared a link, 2 weeks, 6 days ago
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Datacenters in space are a terrible, horrible, no good idea.

A former NASA engineer - now a Google Cloud AI infra alum - rips apart the idea of building GPU datacenters in orbit. His verdict: space is a terrible server rack. Power delivery? A nightmare. Heat dissipation? Worse in a vacuum. Radiation? Frying time. Even a 200kW solar rig (think ISS-sized) could.. read more  

Datacenters in space are a terrible, horrible, no good idea.
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@kala shared a link, 2 weeks, 6 days ago
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Writing a good CLAUDE.md

Anthropic’s Claude Code now deprioritizes parts of the root context file it sees as irrelevant. It still reads the file every session, but won’t waste cycles on side quests. The message to devs: stop stuffing it with catch-all instructions. Instead, use modular context that unfolds as needed - think.. read more  

Writing a good CLAUDE.md
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@kala shared a link, 2 weeks, 6 days ago
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Cato CTRL™ Threat Research: HashJack - Novel Indirect Prompt Injection Against AI Browser Assistants

A new attack method -HashJack- shows how AI browsers can be tricked with nothing more than a URL fragment. It works like this: drop malicious instructions after the#in a link, and AI copilots likeComet,Copilot for Edge, andGemini for Chromemight swallow them whole. No need to hack the site. The LLM .. read more  

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1,500+ PRs Later: Spotify’s Journey with Our Background Coding Agent

Spotify just gave its internal Fleet Management tooling a serious brain upgrade. They've wired inAI coding agentsthat now handle source-to-source transformations across repos - automatically. So far? Over 1,500 AI-generated PRs pushed. Not just lint fixes - these include heavy-duty migrations. They'.. read more  

1,500+ PRs Later: Spotify’s Journey with Our Background Coding Agent
Magika is an open-source file type identification engine developed by Google that uses machine learning instead of traditional signature-based heuristics. Unlike classic tools such as file, which rely on magic bytes and handcrafted rules, Magika analyzes file content holistically using a trained model to infer the true file type.

It is designed to be both highly accurate and extremely fast, capable of classifying files in milliseconds. Magika excels at detecting edge cases where file extensions are incorrect, intentionally spoofed, or absent altogether. This makes it particularly valuable for security scanning, malware analysis, digital forensics, and large-scale content ingestion pipelines.

Magika supports hundreds of file formats, including programming languages, configuration files, documents, archives, executables, media formats, and data files. It is available as a Python library, a CLI, and integrates cleanly into automated workflows. The project is maintained by Google and released under an open-source license, making it suitable for both enterprise and research use.

Magika is commonly used in scenarios such as:

- Secure file uploads and content validation
- Malware detection and sandboxing pipelines
- Code repository scanning
- Data lake ingestion and classification
- Digital forensics and incident response