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@faun shared a link, 8 months, 3 weeks ago
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kube-bench Tutorial: Features, Use Cases, How It Works

kube-benchjust leveled up. Aqua Security’s CIS compliance scanner now snaps into CI/CD, runs pre-deploy checks, and helps dig through forensics after incidents. It plays nice with managed K8s—EKS, AKS, GKE—and handles custom YAML test suites if you’re going off the beaten path. Reports land in stru.. read more  

kube-bench Tutorial: Features, Use Cases, How It Works
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CNCF Incubates OpenYurt for Kubernetes at the Edge

OpenYurt just leveled up—now officially an incubating project under the CNCF. It pushes Kubernetes out past the data center, into the messy edges of the network, without breaking upstream compatibility. No forks, no duct tape. The maintainer roster’s growing too. Folks fromVMware,Microsoft, andInte.. read more  

CNCF Incubates OpenYurt for Kubernetes at the Edge
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v1.34: Of Wind & Will (O' WaW)

Kubernetes v1.34 drops with58 updates, and23 just hit stable. Highlights: Dynamic Resource Allocation (DRA), per-Pod resource limits, and secure image pulls using Pod-specific ServiceAccount tokens. Scalability gets a lift from streaming list responses. Security tightens with finer anonymous auth r.. read more  

v1.34: Of Wind & Will (O' WaW)
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Kubernetes v1.34 brings networking refinements for cloud-native infrastructure

Kubernetes 1.34 comes packed withnetworking upgradesbuilt for scale. Less overhead. Fewer headaches. Easier to run big clusters without sweating packet flows. This triannual release keeps pushing the envelope for both cloud-native setups and the on-prem diehards... read more  

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Evolving Kubernetes for generative AI inference

Google Cloud, ByteDance, and Red Hat are wiring AI smarts straight intoKubernetes. Think: faster inference benchmarks, smarter LLM-aware routing, and on-the-fly resource juggling—all built to handle GenAI heat. Their new push,llm-d, bakesvLLMdeep into Kubernetes. That unlocks disaggregated serving .. read more  

Evolving Kubernetes for generative AI inference
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The architecture of AI is different from all of the computing that came before it

AI is breaking open source out of its old habits. Compute-heavy models now demand GPU-first stacks, leaner infrastructure, and fresh rules for how we build and scale. Jonathan Bryce points out: scalability and reliability still matter—but AI’s deployment needs throw the old architecture playbook ou.. read more  

The architecture of AI is different from all of the computing that came before it
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From Novice to Pro: Mastering Lightweight Linux for Your Kubernetes Project

Alpine, Flatcar, Fedora CoreOS, Talos, and Ubuntu Core are carving out strong niches as Kubernetes-first base OSes. Each leans into immutability, container-native design, and just enough system overhead to get out of the way. That lean profile isn’t just a flex—it means lower resource drag and a de.. read more  

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@laura_garcia shared a post, 8 months, 3 weeks ago
Software Developer, RELIANOID

💡 What is a VIP Load Balancer?

AVIP (Virtual IP)load balancer distributes traffic across multiple servers using a single IP. It ensures: ✅ Scalability ✅ High availability ✅ Session persistence ✅ Smart traffic routing 🚀RELIANOIDtakes VIP load balancing to the next level with: 🔒 SSL offloading 📊 Dynamic health monitoring ⚖️ Advance..

Knowledge base VIP LOAD BALANCER
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@anjali shared a link, 8 months, 3 weeks ago
Customer Marketing Manager, Last9

A Practical Guide to Python Application Performance Monitoring(APM)

Monitor, debug, and optimize Python apps in production with APM—track transactions, DB queries, errors, and external calls.

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@idjuric660 shared a post, 8 months, 3 weeks ago
Technical Content Writer, Mailtrap

How to Send Emails from Supabase using SMTP or Email API

Whether you’re confirming user signups, sending notifications, or automating workflows, Supabase makes it easy to integrate and send emails with SMTP or third-party APIs. And in this guide, I’ll walk you through every step of the process, including: - Sending emails using Supabase Auth[click here to..

GPT (Generative Pre-trained Transformer) is a deep learning model developed by OpenAI that has been pre-trained on massive amounts of text data using unsupervised learning techniques. GPT is designed to generate human-like text in response to prompts, and it is capable of performing a variety of natural language processing tasks, including language translation, summarization, and question-answering. The model is based on the transformer architecture, which allows it to handle long-range dependencies and generate coherent, fluent text. GPT has been used in a wide range of applications, including chatbots, language translation, and content generation.

GPT is a family of language models that have been trained on large amounts of text data using a technique called unsupervised learning. The model is pre-trained on a diverse range of text sources, including books, articles, and web pages, which allows it to capture a broad range of language patterns and styles. Once trained, GPT can be fine-tuned on specific tasks, such as language translation or question-answering, by providing it with task-specific data.

One of the key features of GPT is its ability to generate coherent and fluent text that is indistinguishable from human-generated text. This is achieved by training the model to predict the next word in a sentence given the previous words. GPT also uses a technique called attention, which allows it to focus on relevant parts of the input text when generating a response.

GPT has become increasingly popular in recent years, particularly in the field of natural language processing. The model has been used in a wide range of applications, including chatbots, content generation, and language translation. GPT has also been used to create AI-generated stories, poetry, and even music.