Terraform Production Readiness Cheatsheet
Terraform working isnât enough. Learn what it takes to make it production-ready â from backend design to security and automated pipelines.
Updates and recent posts about GPT.. Story
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@cloudsignals shared a post, 1Â month, 3Â weeks ago
Director - Cloud Engineering, osttra
DevSecOps: Rapid & Secure Delivery
If security is your last step, youâre already too late. This guide shows how to build a DevSecOps pipeline where security is continuous, automated, and invisible to delivery speed.
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GitHub backs down, kills Copilot PR âtipsâ after backlash
GitHub revoked Copilot's ability to inject tips into other users' pull requests after reports that Copilot Review inserted aRaycastlink. They disabled agent tips in PR comments, blamed a programming-logic bug, and said they won't turn tips into ads... read more Â
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SQLite Features You Didnât Know It Had: JSON, text search, CTE, STRICT, generated columns, WAL
SQLite packsJSONextraction, expression indexes,FTS5full-text search,CTEs, window functions, andWALinto a single file. It enforcesstrict tables, supportsgenerated columns, and indexes JSON expressions for fast semi-structured queries... read more Â
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Email address obfuscation: What works in 2026?
The article catalogs obfuscation methods:HTML entities,SVG in an object,display:none, JavaScript decoders, custom encodings, andAESâ256. It coversmailtoobfuscation, redirects (302/301,.htaccess), interaction-gated reveals, accessibility caveats, and ahoneypot-based spam-statistics system... read more Â
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I told Claude Code to build me an executive assistant. This is what my work as CTO looks like now
CTO at ZAR shares his experience managing 10 engineers, shipping code, and operating at the C-level with an AI assistant named Claude Code. The system allows him to maintain context across multiple workstreams, automate tasks, and scale his productivity. In just three weeks, he has documented 82 mee.. read more Â
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Python 3.3: The Version That Quietly Rewired Everything
Python 3.3 introduced three key features that have had a lasting impact on Python development. Firstly, yield from simplified the composition of generators by allowing easy delegation between them. Secondly, venv standardized virtual environments in Python, improving isolation and reproducibility of.. read more Â
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@kaptain shared a link, 1Â month, 3Â weeks ago
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Duolingo's Kubernetes Leap
Duolingo made a bold leap migrating 500+ services to Kubernetes, embracing Argo CD for blue-green deployments and leveraging GitOps for flexibility and control. This shift to a cellular architecture enabled them to isolate environments and manage developer trust while navigating AWS rate limits. Exc.. read more Â
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K3s on On-Prem Infrastructures the GitOps Way: Writing a Custom k0rdent Template from Scratch
Kubernetes, now 12 years old, has evolved into the universal operating system for modern infrastructure, running on various platforms like Proxmox. Using k0rdent, Proxmox, and K3s, users can provision and manage Kubernetes clusters on-premise in a declarative, repeatable, and clean manner. This appr.. read more Â
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@kaptain shared a link, 1Â month, 3Â weeks ago
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Kubernetes Monitoring Helm chart v4: Biggest update ever!
The Kubernetes Monitoring Helm chart version 4.0 is designed to solve real pain points that users have hit as their monitoring setups have grown. Destinations are now defined as a map instead of a list, making it easier to manage configurations for multiple clusters. Collectors are defined by the us.. read more Â
GPT is a family of language models that have been trained on large amounts of text data using a technique called unsupervised learning. The model is pre-trained on a diverse range of text sources, including books, articles, and web pages, which allows it to capture a broad range of language patterns and styles. Once trained, GPT can be fine-tuned on specific tasks, such as language translation or question-answering, by providing it with task-specific data.
One of the key features of GPT is its ability to generate coherent and fluent text that is indistinguishable from human-generated text. This is achieved by training the model to predict the next word in a sentence given the previous words. GPT also uses a technique called attention, which allows it to focus on relevant parts of the input text when generating a response.
GPT has become increasingly popular in recent years, particularly in the field of natural language processing. The model has been used in a wide range of applications, including chatbots, content generation, and language translation. GPT has also been used to create AI-generated stories, poetry, and even music.
