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@varbear shared a link, 3 weeks, 4 days ago
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The Code Review That Cost $2 Million, CodeGood

New data shows only15% of code review comments catch real bugs. The rest? Nitpicks on style, naming, or formatting - stuff linters and AI were made to handle. Human reviews burn through$3.6M a yearin larger orgs and still miss the tough stuff: threading issues, system integration bugs, rare edge cas.. read more  

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@kaptain shared a link, 3 weeks, 4 days ago
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BadPods Series: Everything Allowed on AWS EKS

A security researcher ran a full-blown container escape on EKS usingBadPods- a tool that spins up dangerously overprivileged pods. The pod broke out of its container, poked around the host node, moved laterally, and swiped AWS IAM creds. All of it slipped past EKS’s defaultPod Security Admission (PS.. read more  

BadPods Series: Everything Allowed on AWS EKS
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@kaptain shared a link, 3 weeks, 4 days ago
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Streamline your containerized CI/CD with GitLab Runners and Amazon EKS Auto Mode

GitLab Runners now work withAmazon EKS Auto Mode. That means hands-off infra, smarter scaling, and built-in AWS security. Runners spin up onEC2 Spot Instances, so teams can cut CI/CD compute costs by as much as90%- without hacking together flaky pipelines... read more  

Streamline your containerized CI/CD with GitLab Runners and Amazon EKS Auto Mode
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@kaptain shared a link, 3 weeks, 4 days ago
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Implementing assurance pipeline for Amazon EKS Platform

AWS released a full-stack CI/CD validation pipeline forAmazon EKS. It pulls in six layers of testing,Terraform,Helm,Locustload testing, and evenAWS Fault Injectionfor pushing resilience to the edge. The goal: bake policy checks, functional tests, and brutal load tests right into pre-deployment. Fewe.. read more  

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@kaptain shared a link, 3 weeks, 4 days ago
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From Deterministic to Agentic: Creating Durable AI Workflows with Dapr

Dapr droppedDurable Agents- a mashup of classic workflows and LLM-driven agents that can actually get things done and survive rough edges. They track reasoning steps, tool calls, and chat states like a champ. If things crash, no problem: Dapr Workflows and Diagrid Catalyst bring it all back... read more  

From Deterministic to Agentic: Creating Durable AI Workflows with Dapr
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@kaptain shared a link, 3 weeks, 4 days ago
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Kubernetes GPU Management Just Got a Major Upgrade

Kubernetes 1.34 droppedDynamic Resource Allocation (DRA)- think persistent volumes, but for GPUs and custom hardware. Vendors can now plug in drivers and schedulers for their devices, and workloads can pick exactly what they need. Coming in 1.35: a newworkload abstractionthat speaks the language of .. read more  

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@kaptain shared a link, 3 weeks, 4 days ago
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v1.35: New level of efficiency with in-place Pod restart

Kubernetes 1.35, as you may know, introducedin-place Pod restarts(alpha). It's a real reset: all containers, init and sidecars included - without killing the Pod or kicking off a reschedule. Think restart without the cloud drama. Big win for workloads with heavy inter-container dependencies or massi.. read more  

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@kaptain shared a link, 3 weeks, 4 days ago
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1.35: Enhanced Debugging with Versioned z-pages APIs

Kubernetes 1.35 makes a quiet-but-crucial upgrade: z-pages debugging endpoints now returnstructured, machine-readable JSON. That means tools- not just tired humans - can parse control plane state directly. The responses areversioned, backward-compatible, and tucked behind feature flags for now... read more  

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@kaptain shared a link, 3 weeks, 4 days ago
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v1.35: Watch Based Route Reconciliation in the Cloud Controller Manager

Kubernetes v1.35 sneaks in an alphafeature gatethat flips the CCM route controller from "check every X minutes" to "watch and react." It now usesinformersto trigger syncs when nodes change - plus a light periodic check every 12–24 hours... read more  

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@kala shared a link, 3 weeks, 4 days ago
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The 2026 Data Engineering Roadmap: Building Data Systems for the Agentic AI Era

Data engineering’s getting flipped.AI agentsandLLMsaren’t just tagging along anymore - they’re the main users now. That means engineers need to buildcontext-aware, machine-readable data systemsthat don’t just store info but actually make sense of it. Think:vector databases,knowledge graphs,semantic .. read more  

The 2026 Data Engineering Roadmap: Building Data Systems for the Agentic AI Era
Winston AI is an advanced, all-in-one content verification platform designed to deliver the most accurate AI content detection available today. Recognized as the best AI detector by educators, students, publishers, journalists, researchers, and businesses worldwide, Winston AI helps users confidently verify whether content is written by a human, generated by AI, or a combination of both.

Built for academic, professional, and enterprise use, Winston AI addresses the growing need for transparency and authenticity in an AI-driven world. Whether reviewing essays, research papers, articles, marketing content, or digital publications, Winston AI provides fast, reliable, and explainable results that users can trust.

At the core of Winston AI is a powerful AI content checker capable of identifying text generated by ChatGPT, Claude, Google Gemini, and all known AI models. Winston AI continuously updates its detection systems to keep pace with the rapidly evolving AI landscape, ensuring consistent accuracy even as new models and writing techniques emerge.

Winston AI analyzes content at a deep linguistic level, evaluating structure, predictability, and stylistic patterns to distinguish AI-generated text from human writing. This advanced approach reduces false positives and delivers clear probability scores, helping users make informed decisions without uncertainty.

Winston AI goes beyond basic AI detection by offering a comprehensive suite of tools designed to support content authenticity, credibility, and integrity across multiple formats.

AI Detector
Accurately identifies AI-generated, human-written, and mixed text with detailed confidence scores and sentence-level insights.

Plagiarism Checker
Detects copied or unoriginal content across academic and professional sources, supporting originality and ethical content creation.

Fact Checker Tool
Helps verify claims and statements within content, reducing misinformation and improving accuracy for research, journalism, and publishing.

AI Image & Deepfake Detector
Analyzes images to determine whether they were generated or manipulated by AI, helping users identify synthetic visuals and deepfake content.

Writing Feedback
Provides actionable feedback on clarity, structure, and quality, supporting students, educators, and professionals in improving written work.

HUMN-1 Website Certification
Allows websites to display a trust signal certifying human-verified content, reinforcing transparency and credibility with audiences and search engines.

Together, these tools make Winston AI a complete solution for verifying authenticity, accuracy, originality, and credibility across text, images, and websites.