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@devopslinks shared a link, 1 month, 3 weeks ago
FAUN.dev()

Year in Review: Lessons From 12 Projects Patreon Shipped in 2025

Patreon engineers made massive bets in 2025, shipping code across all areas of the system and enabling impactful features like Autopilot's growth tools suite. Expanding Autopilot's scope, reach, and effectiveness was a challenge, especially guaranteeing recipient redemption after email delivery in a.. read more  

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@devopslinks shared a link, 1 month, 3 weeks ago
FAUN.dev()

Making a micro Linux distro

A dev dives into building a barebones Linux distro for RISC-V using QEMU. Starts at the metal: compiles the kernel, wires up a no-frills init process, packs it all into an initramfs. Then levels up, drops inu-rootto swap out raw shell scripts for Go-powered userland tools. Adds network. Now it’s a f.. read more  

Making a micro Linux distro
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@devopslinks shared a link, 1 month, 3 weeks ago
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Monitoring & Observability: Using Logs, Metrics, Traces, and Alerts to Understand System Failures

Railway just leveled up its observability game. Now logs, metrics, and alerts all live in one tidy dashboard - clean and connected. Structured logs flow straight from stdout/stderr. Metrics pulse in real time. Alerts plug into monitors or deployment webhooks so teams catch firesbeforethey rage... read more  

Monitoring & Observability: Using Logs, Metrics, Traces, and Alerts to Understand System Failures
News FAUN.dev() Team
@devopslinks shared an update, 1 month, 3 weeks ago
FAUN.dev()

Canonical Introduces Minimal Ubuntu Pro: Smaller Images and Secure Cloud Workloads at Scale

Ubuntu GNU/Linux

Canonical has launched Minimal Ubuntu Pro, enhancing cloud security with lightweight images and robust features. Available on AWS, Azure, and Google Cloud, it offers minimized attack surfaces and long-term support.

Canonical Introduces Minimal Ubuntu Pro: Smaller Images and Secure Cloud Workloads at Scale
News FAUN.dev() Team
@varbear shared an update, 1 month, 3 weeks ago
FAUN.dev()

AI's Dependence on Python Deepens as Anthropic Funds Core Ecosystem Work

Python

Anthropic invests $1.5 million in the Python Software Foundation to boost Python ecosystem security. The funding targets improvements in CPython and PyPI, including new tools for package review and malware datasets. It also supports the PSF's core activities and community initiatives.

AI's Dependence on Python Deepens as Anthropic Funds Core Ecosystem Work
News FAUN.dev() Team
@kala shared an update, 1 month, 3 weeks ago
FAUN.dev()

Anthropic’s New "Economic Primitives" Reveal Who Uses Claude, for What, and How Well It Works

Anthropic's new Economic Index report introduces five "economic primitives" to measure *how* Claude is used: task complexity, user and AI skill level, use case (work, coursework, personal), autonomy, and task success - built from privacy-preserving classification of anonymized Claude.ai and first-party API transcripts from **November 2025**.

Anthropic’s New "Economic Primitives" Reveal Who Uses Claude, for What, and How Well It Works
News FAUN.dev() Team
@varbear shared an update, 1 month, 3 weeks ago
FAUN.dev()

Tailwind CSS Lays Off 75% of Its Engineering Team as AI Cuts Documentation Traffic by 40%

tailwindcss Vercel

Tailwind CSS laid off roughly **75% of its engineering team** after a **~40% drop in documentation traffic** and an estimated **~80% decline in revenue**, even as usage of the framework continues to grow. According to its creator, AI-driven access to documentation has broken the link between adoption and sustainability.

News FAUN.dev() Team
@devopslinks shared an update, 1 month, 3 weeks ago
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Pulumi Expands IaC Platform to Support Terraform, OpenTofu, and Native HCL

Pulumi Terraform

Pulumi added support for managing Terraform and OpenTofu state in Pulumi Cloud and introduced native HCL support in its infrastructure as code engine. These changes allow teams to use Terraform, OpenTofu, Pulumi languages, and HCL side by side, with shared state visibility, governance features, and AI-assisted operations available across tools.

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@laura_garcia shared a post, 2 months ago
Software Developer, RELIANOID

🔐 RELIANOID Load Balancer – Security Contributions

At RELIANOID, we actively and selflessly contribute to improving global cybersecurity, staying true to our open-source spirit. 🤝 We maintain close collaborations with security platforms, forums, and threat-intelligence communities, sharing our expertise to help strengthen protection across the Inter..

abuseipdb contributor relianoid
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@laura_garcia shared a post, 2 months ago
Software Developer, RELIANOID

📍 RELIANOID at Bett UK 2026

We’re excited to take part in Bett UK 2026, the world’s leading EdTech event, bringing together educators, innovators, and decision-makers shaping the future of education. 🗓 January 21–23, 2026 📍 London, United Kingdom Join us to discover how RELIANOID enables secure, scalable, and highly available ..

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GPT-5.4 is OpenAI’s latest frontier AI model designed to perform complex professional and technical work more reliably. It combines advances in reasoning, coding, tool use, and long-context understanding into a single system capable of handling multi-step workflows across software environments. The model builds on earlier GPT-5 releases while integrating the strong coding capabilities previously introduced with GPT-5.3-Codex.

One of the defining features of GPT-5.4 is its ability to operate as part of agent-style workflows. The model can interact with tools, APIs, and external systems to complete tasks that extend beyond simple text generation. It also introduces native computer-use capabilities, allowing AI agents to operate applications using keyboard and mouse commands, screenshots, and browser automation frameworks such as Playwright.

GPT-5.4 supports context windows of up to one million tokens, enabling it to process and reason over very large documents, long conversations, or complex project contexts. This makes it suitable for tasks such as analyzing codebases, generating technical documentation, working with large spreadsheets, or coordinating long-running workflows. The model also introduces a feature called tool search, which allows it to dynamically retrieve tool definitions only when needed. This reduces token usage and makes it more efficient to work with large ecosystems of tools, including environments with dozens of APIs or MCP servers.

In addition to improved reasoning and automation capabilities, GPT-5.4 focuses on real-world productivity tasks. It performs better at generating and editing spreadsheets, presentations, and documents, and it is designed to maintain stronger context across longer reasoning processes. The model also improves factual accuracy and reduces hallucinations compared with previous versions.

GPT-5.4 is available across OpenAI’s ecosystem, including ChatGPT, the OpenAI API, and Codex. A higher-performance variant, GPT-5.4 Pro, is also available for users and developers who require maximum performance for complex tasks such as advanced research, large-scale automation, and demanding engineering workflows. Together, these capabilities position GPT-5.4 as a model aimed not just at conversation, but at executing real work across software systems.