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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.. read more  

Best 20 Linux Commands for Daily Use in Production Servers
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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... read more  

SLI Evolution Stages
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%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.. read more  

%CPU Utilization Is A Lie
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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.. read more  

Introducing Budget Controls for AWS: Automatically Manage Your Cloud Costs
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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 .. read more  

Fast, Secure Kubernetes with AKS Automatic
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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.. read more  

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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 .. read more  

Kubernetes Security: Best Practices to Protect Your Cluster
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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... read more  

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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... read more  

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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... read more  

INTELLECT-3 is a frontier-class 100B+ Mixture-of-Experts language model developed by Prime Intellect and trained end-to-end using their large-scale asynchronous RL framework, PRIME-RL. Built on the GLM-4.5-Air base model, INTELLECT-3 combines supervised fine-tuning with long-horizon reinforcement learning across hundreds of verifier-backed environments spanning math, code, science, logic, and agentic tasks.

The model was trained on a high-performance cluster of 512 NVIDIA H200 GPUs across 64 nodes, supported by Prime Intellect’s Sandboxes execution engine, deterministic compute orchestration, and Lustre-backed distributed storage. The result is a model that surpasses many larger systems in reasoning benchmarks while remaining fully open-source.

Prime Intellect released not only the model weights but also the full training recipe: PRIME-RL, Verifiers, the Environments Hub, datasets, and evaluation suites. INTELLECT-3 is positioned as a foundation for organizations seeking to post-train or customize their own frontier-grade models without relying on proprietary AI labs.