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@faun shared a link, 1 year, 2 months ago
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The Next Evolution of DigitalOcean Kubernetes: Introducing Features that Unlock Superior Scalability for Growing Businesses

DigitalOceanjust cranked up the cluster game to a cool1,000nodes, injectedeBPF-based routingfor a performance boost, and rolled outManaged Ciliumto keep things rock steady. Scale orchestration? Now it's on rocket fuel... read more  

The Next Evolution of DigitalOcean Kubernetes: Introducing Features that Unlock Superior Scalability for Growing Businesses
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@faun shared a link, 1 year, 2 months ago
FAUN.dev()

Introducing kube-scheduler-simulator

kube-scheduler-simulatorlets you peek into the mind of Kubernetes’ scheduler. You can poke and prod at scheduling decisions without risking a real cluster meltdown. Add custom plugins like a pro, no sweat. Forget blindsiding surprises. The simulator mirrors production with eerie accuracy—sync resour.. read more  

Introducing kube-scheduler-simulator
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@faun shared a link, 1 year, 2 months ago
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CKA Prep: CKA Exam Overview and Preparation Strategy

CKA exam:Juggle up to 6 Kubernetes clusters like a pro. Command rolling updates, Ingress, and persistent storage with flair. Imperative commands? Your secret weapon to snatch victory... read more  

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@faun shared a link, 1 year, 2 months ago
FAUN.dev()

Google Cloud unveils AI-focused updates to Kubernetes Engine

Meet theCluster Director for GKE. This beast masters GPU/TPU clusters seamlessly, herding them with Kubernetes APIs like a rodeo star. Meanwhile, theGKE Inference Gatewayramps up AI model performance. It's like magic but real: Serving costs tumble by up to30%. Tail latency? Chopped by up to60%... read more  

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@faun shared a link, 1 year, 2 months ago
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Optimize Gemma 3 Inference: vLLM on GKE 🏎️💨

GKE Autopilot's GPUmeans business—AI inference tasks don’t stand a chance. Just two arguments and, bam, you’ve unleashed NVIDIA's beastly Gemma 3 27B model, which chugs a massive46.4GB VRAM. ⚡️ Meanwhile, vLLM squeezes the models with bf16 precision, though optimization requires wrestling with algor.. read more  

Optimize Gemma 3 Inference: vLLM on GKE 🏎️💨
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@faun shared a link, 1 year, 2 months ago
FAUN.dev()

Kubernetes 1.33 – What you need to know

Kubernetes 1.33 shakes things up with game-changing updates.LIST streaming encodingtrims down API Server memory like a chef with a sharp knife. Deliberate deletion orders lock down security tighter than a drum. And get this:in-place updatesfor Pod resources ditch those annoying restarts! Finally, us.. read more  

Kubernetes 1.33 – What you need to know
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@anjali shared a link, 1 year, 2 months ago
Customer Marketing Manager, Last9

Observability vs APM: What’s the Real Difference?

Observability goes beyond APM—it's not just about metrics, it's about understanding why things break, not just that they did.

o11Y VS APM
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@anjali shared a link, 1 year, 2 months ago
Customer Marketing Manager, Last9

Logging vs Monitoring: What’s the Real Difference?

Logging and monitoring work together, but they’re not the same. Here’s how they help you understand, fix, and improve your systems.

logging
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@anjali shared a link, 1 year, 2 months ago
Customer Marketing Manager, Last9

Debug Logging: A Comprehensive Guide for Developers

A clear guide to debug logging—what it is, how to use it well, and why it matters when you're trying to understand what your code is doing.

Debug Logging_ A Comprehensive Guide for Developers
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@shurup shared a post, 1 year, 2 months ago
@palark

Nelm, a new alternative to Helm, is GA

werf

werf, a CNCF Sandbox project, announced Nelm as a new tool for deploying Helm charts.

Nelm project
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.