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@varbear shared a link, 2 weeks, 6 days ago

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Building a Blockchain in Go: From 'Hello, Block' to 10,000 TPS

A new Go tutorial shows how to build a lean, fast blockchain - clocking ~10,000 TPS - without the usual bloat. It covers the full stack:P2P networking,custom consensus, and properstate management. No unbounded mempools. No missing snapshots. Just a chain that actually runs, benchmarked on real machi.. read more

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@varbear shared a link, 2 weeks, 6 days ago

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Inside the GitHub Infrastructure Powering North Korea’s Contagious Interview npm Attacks

The Socket Threat Research Team has been following North Korea’s Contagious Interview operation as it targets blockchain and Web3 developers through fake job interviews. The campaign has added at least197 malicious npm packagesand over31,000 downloadssince last report, showcasing the adaptability of.. read more

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@varbear shared a link, 2 weeks, 6 days ago

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Building Mac Farm: Running 2000+ iOS Pipelines Daily

At Trendyol, they runover 2,000 iOSpipelines daily across130 Mac machines, executing50,000+ unit testsand10,000+ UI testsfor their iOS apps. The team initiated a mobile CI transformation to address the challenges of scale and performance as their team grew and AI usage increased. They built a macOS .. read more

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@varbear shared a link, 2 weeks, 6 days ago

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How to Get Developers in Your Team to Contribute to Your Test Automation

A fresh blog post dives into how to get devs pulling their weight ontest automation- not as extra credit, but as part of shipping code. The playbook: tie automation work straight to thedefinition of done, clear up who owns what, and stop pretending delivery pressure is a mystery. The big idea? Most .. read more

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@varbear shared a link, 2 weeks, 6 days ago

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Before You Push: Implementing Quality Gates in Your Software Project

This post discusses best practices for automated testing in software engineering, including unit tests and integration tests for databases, APIs, and emulators. It also covers end-to-end tests using tools like Cypress, Appium, Postman, and more. Additionally, it highlights the importance of environm.. read more

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@varbear shared a link, 2 weeks, 6 days ago

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Partitions, Sharding, and Split-for-Heat in DynamoDB

DynamoDB starts to grumble when a single partition gets hit with more than 1,000WCU. To dodge throttling, writes need to fan out across shards. Recommended move: start with10 logical shards. WatchCloudWatch metrics. DialNup or down. Letburstandadaptive capacitybuy you breathing room - untilSplit-for.. read more

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@kaptain shared a link, 2 weeks, 6 days ago

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In-place Pod resizing in Kubernetes: How it works and how to use it

Kubernetes 1.33 and 1.34 takein-place Pod resource updatesfrom beta to battle-ready. You can now tweak CPU and memory on the fly - no Pod restarts needed. It's on by default. What’s new: memory downsizing with guardrails, kubelet metrics that actually tell you what’s going on, and smarter retries th.. read more

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@kaptain shared a link, 2 weeks, 6 days ago

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KubeCon North America 2025 Recap: Federation and

HAProxy just droppedUniversal Mesh, a fresh spin on service mesh design. Forget the per-service sidecars - this model plants high-speed gateways at the network edges instead. Result? Lighter by 30–50% on resources, easier to upgrade, and way less hassle routing traffic across Kubernetes, VMs, and cl.. read more

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@kaptain shared a link, 2 weeks, 6 days ago

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Ingress NGINX Is Retiring. Here’s Your Path Forward with HAProxy

TheIngress NGINX projectis riding off into the sunset by March 2026. Time to pick a new horse. One strong contender: theHAProxy Kubernetes Ingress Controller. It matches feature-for-feature, comes with deeper observability, and reloads configs without taking your cluster offline. HAProxy’s not stopp.. read more

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@kaptain shared a link, 2 weeks, 6 days ago

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Developers don’t care about Kubernetes clusters

Most cloud-native tools obsess over clusters. Not developers. That means poor support for things like promoting code between environments or deploying by feature - not just by repo. The author pushes for a better way: platforms that hide the Kubernetes mess and tame CI/CD. Think feature-driven deplo.. 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.

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