Updates and recent posts about GPT..

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

Best 20 Linux Commands for Daily Use in Production Servers

A fresh roundup drops20 go-to Linux commandsfor production sysadmins, dialing in on modern defaults likehtop > top,ss > netstat, andip > ifconfig. The shift? Faster tools that actually get updates. Built with systemd in mind, too. Expect the usual suspects—journalctl,rsync,crontab—all still pulling..

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

SLI Evolution Stages

A new SLI evolution model lays out a maturity roadmap—from rebranded latency/error metrics to ones that actually track business impact. It replaces shallow signals and pulls in the stuff that matters: how service failures hit user goals, tasks, and bottom lines...

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

%CPU Utilization Is A Lie

Stress tests on the Ryzen 9 5900X uncovered a big gap between **reported CPU utilization** and what the chip actually pushes. Around 50% on paper? Could mean close to full throttle in reality—thanks to sneaky behaviors from **SMT resource sharing** and **Turbo frequency scaling**. **Takeaway:** Raw..

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

Introducing Budget Controls for AWS: Automatically Manage Your Cloud Costs

**Budget Controls for AWS** just got better. The open-source tool now reins in more than just EC2. It wrangles **RDS Aurora**, **SageMaker**, and **OpenSearch** too. Under the hood, it taps **AWS Budgets**, **AWS Config**, and **custom tags** to watch spend like a hawk. Hit a budget threshold? It c..

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

Fast, Secure Kubernetes with AKS Automatic

Azure dropped **AKS Automatic**, a new managed Kubernetes tier that tries to do it all—so you don’t have to. It comes with baked-in best practices: autoscaling via HPA, VPA, KEDA, and Karpenter. Automated patching. Node repair. Monitoring. All wired up by default. You still get full access to the ..

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

Kubernetes Security: Best Practices to Protect Your Cluster

A new JetBrains IDE plugin throws Kubernetes security best practices straight into your deployment manifests—right where they belong. Think: checks for `runAsRoot`, privileged mode, `hostPath`, host ports, and sketchy sysctls. No hand-waving. It enforces stuff like: - Default `runAsNonRoot` - Drop ..

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

v1.34: Pods Report DRA Resource Health

Kubernetes v1.34 lands with an alpha upgrade to **[KEP-4680](https://github.com/kubernetes/enhancements/tree/master/keps/sig-node/4680-add-resource-health-to-pod-status)**, pushing **Dynamic Resource Allocation (DRA)** into smarter territory: health-aware Pods. DRA drivers can now stream device heal..

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

v1.34: Recovery From Volume Expansion Failure (GA)

Kubernetes v1.34 bumps **automated recovery from botched PVC expansions** to GA. Users can now fix bad volume size requests—no admin, no drama. It cleans up unused quota, slows down retry spam, and surfaces progress with new PVC status fields...

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

v1.34: DRA Consumable Capacity

Kubernetes 1.34 rolls in **consumable capacity** for Dynamic Resource Allocation (DRA). That means device plugins can now carve up resources—GPU memory, NIC bandwidth, etc.—into precise slices for Pods, ResourceClaims, and namespaces. The scheduler tracks it all, so nothing spills over...

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

v1.34: Decoupled Taint Manager Is Now Stable

Kubernetes 1.34 graduates the taint eviction controller to GA. Now, the node lifecycle controller only applies taints, while a dedicated taint eviction controller manages pod eviction. First split in 1.29, now stable in 1.34...

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.