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Developers don’t care about Kubernetes clusters

Most cloud-native tools obsess over clusters. Not developers. That means poor support for things like promoting code between environments or deploying by feature - not just by repo. The author pushes for a better way: platforms that hide the Kubernetes mess and tame CI/CD. Think feature-driven deplo.. read more  

Developers don’t care about Kubernetes clusters
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@kaptain shared a link, 2 weeks, 6 days ago
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udwall: A Tool for Making UFW and Docker Play Nice With Each Other

Hexmos droppedudwall, a declarative firewall manager that finally makesUFWandDockerplay nice. Docker’s notorious for bulldozing past UFW rules via iptables. udwall patches that hole. It syncs rules across both, auto-reconciles changes, backs up configs, and plugs cleanly intoAnsible. No more duct-ta.. read more  

udwall: A Tool for Making UFW and Docker Play Nice With Each Other
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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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@kaptain shared a link, 2 weeks, 6 days ago
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The Grafana trust problem

Grafana’s been busy clearing the shelves.Grafana Agent,Agent Flow, andOnCall? All deprecated. The replacement:Grafana Alloy- a one-stop observability agent that handles logs, metrics, traces, and OTEL without flinching. Meanwhile,Mimir 3.0ships with a Kafka-powered ingestion pipeline. More scalabili.. read more  

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@kaptain shared a link, 2 weeks, 6 days ago
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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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@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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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