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@laura_garcia shared a post, 4 days, 9 hours ago

Software Developer, RELIANOID

💡 Third-Party Vendors: The Hidden Cybersecurity Risk

In today’s hyper-connected world, digital supply chains are only as secure as their weakest link. One single vendor can open the door to ransomware, outages, or worse. At RELIANOID, we take this risk seriously. 🔒 That’s why we apply: ✅ Continuous vendor risk assessments ✅ Real-time monitoring of thi..

cropped-Blog-THIRD-PARTY-VENDOR-RISKS-RELIANOID

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@varbear shared a link, 4 days, 10 hours ago

FAUN.dev()

Unconventional PostgreSQL Optimizations

PostgreSQL 18 now supportsvirtual generated columns, indexable expressions without burning storage. Perfect for standardizing queries in analytics-heavy pipelines. Pair that withplanner constraint exclusion(constraint_exclusion=on), and Postgres can dodge irrelevant table scans based on constraints... read more

Unconventional PostgreSQL Optimizations

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@varbear shared a link, 4 days, 10 hours ago

FAUN.dev()

Software engineering when machine writes the code

In 1968, computer scientists identified the "software crisis" - the existing methods of programming were struggling to handle the power of computers. Today, AI coding assistants are accelerating productivity, but concerns arise about understanding the code they generate, the implications for debuggi.. read more

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@varbear shared a link, 4 days, 10 hours ago

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The challenges of soft delete

"Soft delete" sounds gentle. It isn't. Slapping adeleted_atcolumn on every table pollutes queries, drags down migrations, and leaves tombstones all over production. This post digs into saner options:PostgreSQL triggers,event archiving in the app layer, andCDC via WAL. Each separates the dead stuff f.. read more

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@varbear shared a link, 4 days, 10 hours ago

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How I Taught GitHub Copilot Code Review to Think Like a Maintainer

Vibe coding has made contributing to open source easier, but the high number of contributions to the AI agent framework goose has posed a challenge. An AI Code Review agent like Copilot can help review PRs, but tuning its feedback is crucial for reducing noise and increasing value. By providing clea.. read more

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@kaptain shared a link, 4 days, 12 hours ago

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Experimenting with Gateway API using kind

A new guide shows how to runGateway APIlocally withkindandcloud-provider-kind. It spins up a one-node Kubernetes cluster in Docker - complete with LoadBalancer Services and a Gateway API controller. Cloud vibes, zero cloud bill. Fire it up to deploy demo apps, test routing, or poke around with CRD e.. read more

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@kaptain shared a link, 4 days, 12 hours ago

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Cluster API v1.12: Introducing In-place Updates and Chained Upgrades

Cluster API v1.12.0 addsin-place updatesandchained upgrades, so machines can swap parts without going down, and clusters can jump versions without drama. KubeadmControlPlaneandMachineDeploymentsnow choose between full rollouts or surgical patching, depending on what changed. The goal: keep clusters .. read more

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@kaptain shared a link, 4 days, 12 hours ago

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Ingress NGINX: Statement from the Steering and Security Response Committees

Kubernetes is cutting offIngress NGINXin March 2026. No more updates. No bug fixes. No security patches. Done. Roughly half of cloud-native setups still rely on it, but it's been understaffed for years. If you're one of them, it's time to move. There’s no plug-and-play replacement, but the ecosystem.. read more

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@kaptain shared a link, 4 days, 12 hours ago

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Run a Private Personal AI with Clawdbot + DMR

Clawdbot just plugged intoDocker Model Runner (DMR). That means you can now run your own OpenAI-compatible assistant, locally, on your hardware. No cloud. No per-token fees. No data leaking into the void!.. read more

Run a Private Personal AI with Clawdbot + DMR

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@kaptain shared a link, 4 days, 12 hours ago

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New Conversion from cgroup v1 CPU Shares to v2 CPU Weight

A new quadratic formula now mapscgroup v1 CPU sharestocgroup v2 CPU weight. Why? Because the old linear approach messed with CPU fairness; especially at low share values. This fix nails prioritization where it counts. It lands at theOCI runtime layer, live inrunc v1.3.2andcrun v1.23, so containers f.. read more

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.