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v1.34: User preferences (kuberc) are available for testing in kubectl 1.34

Kubernetes v1.34 pusheskubectlinto the future with a betauser preferencessystem. Drop a.kubercfile in place, and you can bake in default flags, toggle features likeinteractive deleteorServer-Side Apply, and wire up custom aliases—including pre- and post-args... read more  

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Battle for Resources or the SSA Path to Kubernetes Diplomacy

A full-stack engineer and systems architect with hands-on time incloudandIoT, building real-world tools for theoil and gas sector. Think connected rigs, smart pipelines, and infrastructure that doesn’t flinch at scale. Market signal:Industrial tech’s going deep. Cloud and IoT aren’t side projects a.. read more  

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Kubernetes in an AI-Native World: Can It Stay Relevant?

At KubeCon + CloudNativeCon Hyderabad 2025, CNCF leads made it clear:cloud-native infraisn’t just supporting AI—it’s becoming its backbone. The conversation’s moved on from“Can Kubernetes run AI?”to“How does it evolve for AI-first everything?”.. read more  

Kubernetes in an AI-Native World: Can It Stay Relevant?
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An introduction to platform engineering

Platform engineering is stepping in where DevOps didn’t quite land. Think fewer duct-taped pipelines, more thoughtful systems. The fix? Internal Developer Platforms (IDPs), usually riding on Kubernetes, built to tame the sprawl. Gartner says 80% of big engineering orgs will run platform teams by 20.. read more  

An introduction to platform engineering
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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
Levelop is an interview preparation platform designed specifically for working software engineers (typically with 2–6 years of experience) who want to land jobs at top-tier tech companies.

Instead of just handing you endless lists of problems or passive videos to watch, Levelop uses an active, AI-guided approach to help you build the right mental models for tough technical interviews.

Here is how it works:

Two Specialized AI Mentors: * Orion (Coding AI): Instead of just telling you that your code is wrong, Orion steps in when your code fails, maps out where your knowledge gap is, and guides you to fix it yourself.

Aurora (System Design AI): Rather than making you watch a 40-minute video, Aurora has a live conversation with you to explain foundational system design concepts before you even start drawing on the canvas.

Sprint-Based Practice: You practice in structured loops called "sprints," which combine both Data Structures & Algorithms (DSA) and system design problems.

Actionable Feedback Loop: At the end of every sprint, you receive a detailed report. It scores your technical skills, gives you a behavioral profile, and ranks the exact weaknesses you need to focus on during your next sprint.

In short, it is a smart, interactive practice arena that focuses on actively fixing your specific weaknesses rather than just tracking how many hours you spend studying.