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@kaptain shared a link, 3 weeks, 4 days ago
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Helm 4 Overview

Helm 4 ditches the old plugin model for a sharper, plugin-first architecture powered by WebAssembly. That means isolation/control, and deeper customization - if you're ready to adapt! Post-renderers are now plugins. That breaks compatibility with earlier exec-based setups, so expect some rewiring. .. read more  

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@kaptain shared a link, 3 weeks, 4 days ago
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The State of OCI Artifacts for AI/ML

OCI artifacts quietly leveled up. Over the last 18 months, they’ve gone from a niche hack to production muscle for AI/ML workloads on Kubernetes. The signs? Clear enough:KitOpsandModelPacklanded in the CNCF Sandbox. Kubernetes 1.31 got native support forImage Volume Source. Docker pushedModel Runner.. read more  

The State of OCI Artifacts for AI/ML
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@kaptain shared a link, 3 weeks, 4 days ago
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Unlocking next-generation AI performance with Dynamic Resource Allocation on Amazon EKS and Amazon EC2 P6e-GB200

Amazon just droppedEC2 P6e-GB200 UltraServers, packingNVIDIA GB200 Grace Blackwellchips. Built for running trillion-parameter AI models onAmazon EKSwithout losing sleep over scaling. Under the hood:NVLink 5.0,IMEX, andEFAv4stitch up to 72 Blackwell GPUs into one memory-coherent cluster per UltraServ.. read more  

Unlocking next-generation AI performance with Dynamic Resource Allocation on Amazon EKS and Amazon EC2 P6e-GB200
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@kala shared a link, 3 weeks, 4 days ago
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Build AI Agents Worth Keeping: The Canvas Framework

MIT and McKinsey found a gap the size of the Grand Canyon: 80% of companies claim they’re using generative AI, but fewer than 1 in 10 use cases actually ship. Blame it on scattered data, fuzzy goals, and governance that's still MIA. A new stack is stepping in:product → agent → data → model. It flips.. read more  

Build AI Agents Worth Keeping: The Canvas Framework
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@kala shared a link, 3 weeks, 4 days ago
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Detect inappropriate images in S3 with AWS Rekognition + Terraform

A serverless AWS pipeline runs image moderation on autopilot - withS3,Lambda,Rekognition,SNS, andEventBridgeall wired up throughTerraform. When a photo gets flagged, it’s tagged, maybe quarantined, and triggers an email alert. Daily scan? Handled... read more  

Detect inappropriate images in S3 with AWS Rekognition + Terraform
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@kala shared a link, 3 weeks, 4 days ago
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Grokipedia

Grokipedia just dropped - a Wikipedia remix built from LLM output, pitched as an escape from "woke" bias. The pitch? Bold. The execution? Rough. Entries run long. Facts bend. Citations wander. And the tone? Cold, context-free, and unmistakably machine-made. The usual LLM suspects are here: hallucina.. read more  

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@kala shared a link, 3 weeks, 4 days ago
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Why GPUs accelerate AI learning: The power of parallel math

Modern AI eats GPUs for breakfast - training, inference, all of it. Matrix ops? Parallel everything. Models like LLaMA don’t blink without a gang of H100s working overtime... read more  

Why GPUs accelerate AI learning: The power of parallel math
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@kala shared a link, 3 weeks, 4 days ago
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Agentic AI and Security

Agentic LLM apps come with a glaring security flaw: they can't tell the difference between data and code. That blind spot opens the door to prompt injection and similar attacks. The fix? Treat them like they're radioactive. Run sensitive tasks in containers. Break up agent workflows so they never ju.. read more  

Agentic AI and Security
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@kala shared a link, 3 weeks, 4 days ago
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New trend: Programming by kicking off parallel AI agents

Senior engineers are starting to spin upparallel AI coding agents- think Claude Code, Cursor, and the like - to run tasks side by side. One agent sketches boilerplate. Another tackles tests. A third refactors old junk. All at once. Is it "multitasking on steroids"? Not just this as it messes with ho.. read more  

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@devopslinks shared a link, 3 weeks, 4 days ago
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More Than DNS: The 14 hour AWS us-east-1 outage

AWS’s us-east-1 faceplanted for 14 hours after arace conditioninDynamoDBkicked off a DNS meltdown, taking down 140 services. EC2 buckled under acongestive collapse, overwhelmed by a backup in DropletWorkflow Manager queues. Meanwhile, NLB health checks kept firing blanks - tricked by stale network s.. read more  

More Than DNS: The 14 hour AWS us-east-1 outage
Kueue is a Kubernetes-native job queueing and workload management system designed for large-scale, mixed compute environments such as AI/ML training, batch workloads, and HPC workflows. Instead of scheduling individual Pods, Kueue operates at the job level, deciding when a job should run based on resource quotas, fair-sharing policies, cluster availability, and workload priorities.

Kueue integrates tightly with Kubernetes, working alongside the default scheduler rather than replacing it. It provides features such as all-or-nothing (gang) admission, workload preemption, quota-based sharing across teams or tenants, and support for advanced frameworks like JobSet and Ray. Its goal is to help Kubernetes clusters run efficiently under heavy load while ensuring that critical, latency-sensitive, or large training jobs receive the resources they need without starving lower-priority workloads.