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DevOps: Automating Release Tags

GitHub Actionsjust got a shot of adrenaline. The workflow now slaps tags on releases with spicysemantic versioning. It skims through PR details for those major head-turners and voila—auto-generated changelogs that save time and sanity... read more  

DevOps: Automating Release Tags
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Shopify Tech Stack

Shopify's stack might look like a minimalist's dream—Ruby on RailsandReact. But don’t be fooled; it flexes serious muscle, wrangling173 billion requests in just one day. They've superchargedRubywith the mighty duo ofYJITandSorbet, flungReact Nativeacross key apps, and turned toKafkawhen sending66 mi.. read more  

Shopify Tech Stack
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FinOps Foundation Launches New FinOps for AI Certification

$644 billionis set to flood generative AI by 2025. Yet figuring out the worth and taming costs is still cloudy—and not the fun, "find a silver lining" kind. Enter theFinOps Foundationwith their new rolling certification. For $500, they aim to transform AI spending into data-driven decisions and reso.. read more  

FinOps Foundation Launches New FinOps for AI Certification
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AWS Launches EKS Dashboard to Tackle Multi-Cloud Kubernetes Complexity

AWS has unleashed theAmazon EKS Dashboard—the ultimate tool for seeing your Kubernetes clusters in vivid color. It dishes up cost forecasts and keeps an eye on compliance, which is more than you can say for Google Cloud'sKHI, obsessed as it is with log inspection alone. AWS serves up the full pictur.. read more  

AWS Launches EKS Dashboard to Tackle Multi-Cloud Kubernetes Complexity
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How to create Cilium Cluster Mesh between K3s and Azure Kubernetes Service

Ciliummasterfully knits clusters, weaving on-prem K3s with privateAKSusing Azure Virtual WAN. Efficient load-balancing? Piece of cake... read more  

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FinOps in Action: Efficient AWS EKS Deployment with Terraform

Amazon EKStames Kubernetes chaos on AWS and dishes up power moves when you throwTerraforminto the ring. Terraform automates and locks down cluster management, letting you strut into cost-saving territory like a pro. Deploying EKS clusters through Terraform? That's your golden ticket toSpot Instances.. read more  

FinOps in Action: Efficient AWS EKS Deployment with Terraform
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@faun shared a link, 11 months, 2 weeks ago
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Run Kubernetes Clusters for Less with Amazon EC2 Spot and Karpenter

Karpenterbrings some much-needed swagger toAWS EKSclusters with its clever auto-scaling tricks. It grabsEC2 Spot Instancesand slashes costs by a dazzling90%for stateless, flexible workloads. Imagine dynamic nodes practically springing to life, optimized compute horsepower unleashed, and interruption.. read more  

Run Kubernetes Clusters for Less with Amazon EC2 Spot and Karpenter
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@faun shared a link, 11 months, 2 weeks ago
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A Year of Envoy Gateway GA: Building, Growing, and Innovating Together

Envoy Gatewayjust wrapped its rookie year, and it’s been anything but boring. Four major releases. Game-changing features. A community of builders that means business. Version 1.4? It roped in65 contributorsfrom54 companies, revamping the way cloud-native traffic flows. Meanwhile,Envoy Proxykeeps gr.. read more  

A Year of Envoy Gateway GA: Building, Growing, and Innovating Together
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Publishing AI models to Hub

Docker Model Runnerstruts out with new tricks:tag, push, and packagecommands. Want to pass around AI models like they're hot potatoes? Now you can. They're OCI artifacts now, slotting smoothly into your workflow like it was always meant to be... read more  

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From Kafka to Ray: Deploying AI and Stateful Workloads on AKS with Confidence

Azure's new AKS guides slice through the fog around deployingKafka,Apache Airflow, andRay. Spotlights shine onJVM tuningmagic for Kafka and a peek atKubeRaywrangling distributed Ray... read more  

Gemini 3 is Google’s third-generation large language model family, designed to power advanced reasoning, multimodal understanding, and long-running agent workflows across consumer and enterprise products. It represents a major step forward in factual reliability, long-context comprehension, and tool-driven autonomy.

At its core, Gemini 3 emphasizes low hallucination rates, deep synthesis across large information spaces, and multi-step reasoning. Models in the Gemini 3 family are trained with scaled reinforcement learning for search and planning, enabling them to autonomously formulate queries, evaluate results, identify gaps, and iterate toward higher-quality outputs.

Gemini 3 powers advanced agents such as Gemini Deep Research, where it excels at producing well-structured, citation-rich reports by combining web data, uploaded documents, and proprietary sources. The model supports very large context windows, multimodal inputs (text, images, documents), and structured outputs like JSON, making it suitable for research, finance, science, and enterprise knowledge work.

Gemini 3 is available through Google’s AI platforms and APIs, including the Interactions API, and is being integrated across products such as Google Search, NotebookLM, Google Finance, and the Gemini app. It is positioned as Google’s most factual and research-capable model generation to date.