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@kala shared a link, 4 days, 17 hours ago

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AWS Frontier Agents: Kiro, DevOps Agent, and Security Agent

“Frontier Agents” drop straight into incident workflows. They kick off investigations on their own, whether triggered by alarms or a human hand, pulling together logs, metrics, and deployment context fast. Findings show up where they’re needed: Slack threads, tickets, operator dashboards. No shell c.. read more

AWS Frontier Agents: Kiro, DevOps Agent, and Security Agent

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@kala shared a link, 4 days, 17 hours ago

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Is that allowed? Authentication and authorization in Model Context Protocol

TheModel Context Protocol (MCP) 2025-11-25spec tightens up remote agent auth. It leans intoOAuth 2.1 Authorization Code grants, PKCE required, step-up auth backed. No token passthrough allowed. What’s new: experimental extensions forclient credentialsandclient ID metadata. These smooth out agent reg.. read more

Is that allowed? Authentication and authorization in Model Context Protocol

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@kala shared a link, 4 days, 17 hours ago

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Securing Agents in Production (Agentic Runtime, #1)

Palantir's AIP Agentic Runtime isn't just another agent platform, it's a control plane with teeth. Think tight policy enforcement, ephemeral autoscaling with Kubernetes (Rubix), and memory stitched in from the jump viaOntology. Tool usage? Traced and locked down with provenance-based security. Every.. read more

Securing Agents in Production (Agentic Runtime, #1)

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@kala shared a link, 4 days, 17 hours ago

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Keeping 20,000 GPUs healthy

Modal unpacked how it keeps a 20,000+ GPU fleet sane across AWS, GCP, Azure, and OCI. Think autoscaling, yes, but with some serious moves behind the curtain. They're running instance benchmarking, enforcing machine image consistency, running boot-time checks, and tracking GPU health both passively a.. read more

Keeping 20,000 GPUs healthy

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@devopslinks shared a link, 4 days, 17 hours ago

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Nanoservices: Why Serverless Got Architecture Right

A fresh take onAWS Lambdaand serverless: thinknanoservices- tiny, isolated functions instead of chunky microservices. No shared state or shared runtime but clean separation, lean logic, and fewer ways to screw up scaling. Where microservices can spiral into spaghetti, nanoservices stay crisp. Each f.. read more

Nanoservices: Why Serverless Got Architecture Right

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@devopslinks shared a link, 4 days, 17 hours ago

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Moltbot Personal Assistant Goes Viral, And So Do Your Secrets

Moltbot, the self-hosted AI agent with native hooks for Slack, Telegram, and WhatsApp, exploded from 50-ish to over 3,000 GitHub forks a day after going viral on Jan 24, 2026. It's built around a file-backed workspace and automates everything from code deploys to cloud orchestration. Cool? Definitel.. read more

Moltbot Personal Assistant Goes Viral, And So Do Your Secrets

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@devopslinks shared a link, 4 days, 17 hours ago

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Supply-chain risk of agentic AI - infecting infrastructures via skill worms

AI assistants with shell, network, or filesystem "skills" don't just help, they expose. These hooks can run commands before any human checks the model’s output. That means a bigger attack surface. More room for lateral movement. Easier persistence. In setups where tools like Claude Code run often, i.. read more

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@devopslinks shared a link, 4 days, 17 hours ago

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I Cannot SSH Into My Server Anymore (And That’s Fine)

A dev ditched their $100/month VPS for a clean, automated CoreOS setup. No SSH. No clicking around. JustIgnition,Podman Quadlets, andTerraformdoing the heavy lifting. It boots from YAML, spins up containers with systemd, and keeps itself fresh withPodman auto-updates, zero-touch, straight from the r.. read more

I Cannot SSH Into My Server Anymore (And That’s Fine)

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@devopslinks shared a link, 4 days, 17 hours ago

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CodeBreach: Supply Chain Vuln & AWS CodeBuild Misconfig

Wiz Research dropped details onCodeBreach, a serious flaw that cracked open AWS SDK GitHub repos, yes, including the popular JavaScript one. The root problem? Leakyregex filtersin CodeBuild pipelines. They missed anchors, so attackers slipped in rogue pull requests, dodged build rules, and stole hig.. read more

CodeBreach: Supply Chain Vuln & AWS CodeBuild Misconfig

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@nelly96 gave 🐾 to Verification vs Validation Explained for Beginners in QA , 5 days, 2 hours ago.

Flask is an open-source web framework written in Python and created by Armin Ronacher in 2010. It is known as a microframework, not because it is weak or incomplete, but because it provides only the essential building blocks for developing web applications. Its core focuses on handling HTTP requests, defining routes, and rendering templates, while leaving decisions about databases, authentication, form handling, and other components to the developer. This minimalistic design makes Flask lightweight, flexible, and easy to learn, but also powerful enough to support complex systems when extended with the right tools.

At the heart of Flask are two libraries: Werkzeug, which is a WSGI utility library that handles the low-level details of communication between web servers and applications, and Jinja2, a templating engine that allows developers to write dynamic HTML pages with embedded Python logic. By combining these two, Flask provides a clean and pythonic way to create web applications without imposing strict architectural patterns.

One of the defining characteristics of Flask is its explicitness. Unlike larger frameworks such as Django, Flask does not try to hide complexity behind layers of abstraction or dictate how a project should be structured. Instead, it gives developers complete control over how they organize their code and which tools they integrate. This explicit nature makes applications easier to reason about and gives teams the freedom to design solutions that match their exact needs. At the same time, Flask benefits from a vast ecosystem of extensions contributed by the community. These extensions cover areas such as database integration through SQLAlchemy, user session and authentication management, form validation with CSRF protection, and database migration handling. This modular approach means a developer can start with a very simple application and gradually add only the pieces they require, avoiding the overhead of unused components.

Flask is also widely appreciated for its simplicity and approachability. Many developers write their first web application in Flask because the learning curve is gentle, the documentation is clear, and the framework itself avoids unnecessary complexity. It is particularly well suited for building prototypes, REST APIs, microservices, or small to medium-sized web applications. At the same time, production-grade deployments are supported by running Flask applications on WSGI servers such as Gunicorn or uWSGI, since the development server included with Flask is intended only for testing and debugging.

The strengths of Flask lie in its minimalism, flexibility, and extensibility. It gives developers the freedom to assemble their application architecture, choose their own libraries, and maintain tight control over how things work under the hood. This is attractive to experienced engineers who dislike being boxed in by heavy frameworks. However, the same freedom can become a limitation. Flask does not include features like an ORM, admin interface, or built-in authentication system, which means teams working on very large applications must take on more responsibility for enforcing patterns and maintaining consistency. In situations where a project requires an opinionated, all-in-one solution, Django or another full-stack framework may be a better fit.

In practice, Flask has grown far beyond its initial positioning as a lightweight tool. It has been used by startups for rapid prototypes and by large companies for production systems. Its design philosophy—keep the core simple, make extensions easy, and let developers decide—continues to attract both beginners and professionals. This balance between simplicity and power has made Flask one of the most enduring and widely used Python web frameworks.