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Story Xygeni Team Trending
@mashka shared a post, 5 days, 15 hours ago
Paid Acquisition and Growth Marketing, xygeni

New Threats in Open Source: Worms, AI-Driven Malware, and Trust Abuse

Open source security just hit a new level: self-spreading worms, AI-run attacks, and registry abuse at a massive scale. Shai-Hulud, GlassWorm, and AI-orchestrated intrusions show how fast threats now move, and how easily one stolen token can infect entire ecosystems. The supply chain has changed. Our defenses must too.

New-Threats-in-Open-Source-Worms-AI-Driven-Malware-and-Trust-Abuse-1
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@priya_prabu shared a post, 5 days, 16 hours ago
Senior Product Marketer

Key Oracle performance metrics

Oracle performance issues rarely come from a single metric. This guide breaks down the most important Oracle performance indicators across instance health, memory, storage, waits, SQL, and availability, and shows how to use them together to detect bottlenecks early and prevent downtime.

Story FAUN.dev() Team
@eon01 shared a post, 5 days, 16 hours ago
Founder, FAUN.dev

Microk8s vs K3s

Kubernetes k3s MicroK8s Rancher k3d

To truly master Kubernetes, you need a safe sandbox, and running a lightweight distribution is the perfect solution for your local development workflow. These smaller K8s flavors provide a full-featured, yet constrained, environment that is easy on system resources. Both MicroK8s (maintained by Canonical) and k3s (from Rancher) are popular, production-ready options that deliver the core K8s experience with minimal operational burden, low storage needs, and simple networking setups.

These two platforms are fantastic for learning, experimentation, rapid testing, and skill development. If you don't know which one to choose, this post will give you the quick overview you need to decide.

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@kaptain added a new tool k3d , 5 days, 18 hours ago.
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@varbear shared a link, 1 week ago
FAUN.dev()

Phishing for AWS Credentials via the New 'aws login' Flow

AWS rolled out a newaws loginCLI command using OAuth 2.0 with PKCE. It grabs short-lived credentials, finally pushing out those dusty long-lived access keys. But here’s the hitch:The remote login flow opens up a phishing gap. Since the CLI session and browser session aren’t bound, attackers could sp.. read more  

Phishing for AWS Credentials via the New 'aws login' Flow
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@varbear shared a link, 1 week ago
FAUN.dev()

SQLite JSON Superpower: Virtual Columns + Indexing - DB Pro Blog

SQLite’sJSON virtual generated columnspunch way above their weight. They let you index JSON fields on the fly, no migrations, no whining. Computed like real columns, queryable like real columns, indexable like real columns. But from JSON. Want flexibility without surrendering speed? This flips the s.. read more  

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@varbear shared a link, 1 week ago
FAUN.dev()

Guarding My Git Forge Against AI Scrapers

To stop a wave of scraping on their self-hosted Forgejo, the author stacked defenses like a firewall architect on caffeine. First camemanual IP rate-limiting. ThenNGINX caching and traffic shaping. Finally:Iocaine 3. That last one didn’t just block bots, it lured them into a maze of junk pages. The .. read more  

Guarding My Git Forge Against AI Scrapers
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@varbear shared a link, 1 week ago
FAUN.dev()

How We Saved 70% of CPU and 60% of Memory in Refinery’s Go Code, No Rust Required.

Refinery 3.0 cuts CPU by 70% and slashes RAM by 60%. The trick: selective field extraction from serialized spans. No full deserialization. Fewer heap allocations. Way less waste. It also recycles buffers, handles metrics smarter, and is gearing up to parallelize its core decision loop... read more  

How We Saved 70% of CPU and 60% of Memory in Refinery’s Go Code, No Rust Required.
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@varbear shared a link, 1 week ago
FAUN.dev()

How We Migrated DB 1 to DB 2 , 1 Billion Records Without Downtime

A team movedover 1 billion production records- no downtime, no drama. The stack: dual writes, Kafka retries, and idempotent inserts to keep it clean. They ranshadow readsto sniff for errors, chunked the transfers with checksums, and held off indexing to keep inserts fast. Caches got warmed early to .. read more  

How We Migrated DB 1 to DB 2 , 1 Billion Records Without Downtime
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@varbear shared a link, 1 week ago
FAUN.dev()

14x Faster Faceted Search in PostgreSQL with ParadeDB

ParadeDB brings Elasticsearch-stylefacetingtoPostgreSQL, ranked search results and filter counts, all in one shot. No extra passes. It pulls this off with a customwindow function, planner hooks, andTantivy's columnar index under the hood. That's how they’re squeezing out10×+ speedupson hefty dataset.. read more  

14x Faster Faceted Search in PostgreSQL with ParadeDB
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.