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@varbear shared a link, 3 weeks, 4 days ago
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Web development is fun again

A seasoned dev takes a hard look at today’s messy full-stack reality: scattered tools, niche deep-dives, and burnout baked into the job. ButAI coding assistantsflipped the script. They help offload overhead, mimic pro-level workflows, and sanity-check the code. Now this dev moves across frontend and.. read more  

Web development is fun again
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@varbear shared a link, 3 weeks, 4 days ago
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The Mac Malware of 2025 👾

The 2025 macOS malware scene leveled up hard. Thinkmodular infostealers, built for stealth, slipping in with staged loaders, encrypted configs, and slick social engineering - fake updates, bogus job interviews, even sketchy terminal promos like “ClickFix.” Attackers leaned onAppleScript,JXA, andGo-b.. read more  

The Mac Malware of 2025 👾
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@kaptain shared a link, 3 weeks, 4 days ago
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v1.35: Introducing Workload Aware Scheduling

Kubernetes v1.35 is shifting gears. The newWorkload APIand earlygang schedulingsupport bring group-first thinking, schedule Pods as a unit, or not at all. They’ve thrown inopportunistic batchingtoo. It’s in Beta. It speeds up clusters juggling loads of identical Pods by skipping repeat feasibility c.. read more  

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@kaptain shared a link, 3 weeks, 4 days ago
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From Cluster UI to Operational Plane: Lessons from the Kubernetes Dashboard Deprecation

The official Kubernetes Dashboard has been deprecated. This reflects the shift in Kubernetes operations towards multi-cluster environments, GitOps workflows, and strict access controls. Modern Kubernetes environments require application-aware, RBAC-first operational tools that work across clusters a.. read more  

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@kaptain shared a link, 3 weeks, 4 days ago
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Kubernetes by Example

K8s by Exampleis likeGo by Example, but for YAML and Kubernetes. It’s packed with annotated manifests that show real deployment, scaling, and self-healing patterns, stuff you'd actually use in prod... read more  

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@kaptain shared a link, 3 weeks, 4 days ago
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Kubernetes Was Overkill. We Moved to Docker Compose and Saved 60 Hours.

A small team rolled back their Kubernetes move after six months in the weeds. The setup tanked productivity, bloated infra costs, and turned simple deploys into a slog. They ditched it, brought back Docker Compose, and chopped deploy time from 45 minutes to 4. That one change freed up 60+ engineerin.. read more  

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@kaptain shared a link, 3 weeks, 4 days ago
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Bryan Cantrill: How Kubernetes Broke the AWS Cloud Monopoly

Bryan Cantrill says Kubernetes didn’t just organize containers, it cracked open the cloud market. By letting teams provision infrastructure without locking into provider APIs, it broke AWS’s first-mover grip. That shift putcloud neutralityon the table, and suddenly multi-cloud wasn’t just a buzzword.. read more  

Bryan Cantrill: How Kubernetes Broke the AWS Cloud Monopoly
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@kala shared a link, 3 weeks, 4 days ago
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8 plots that explain the state of open models

Starting 2026, Chinese companies are dominating the open AI model scene, with Qwen leading in adoption metrics. Despite the rise of new entrants like Z.ai, MiniMax, Kimi Moonshot, and others, Qwen's position seems secure. DeepSeek's large models are showing potential to compete with Qwen, but the Ch.. read more  

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@kala shared a link, 3 weeks, 4 days ago
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Build an AI-powered website assistant with Amazon Bedrock

AWS spun up a serverless RAG-based support assistant usingAmazon BedrockandBedrock Knowledge Bases. It pulls in docs via a web crawler and S3, then stuffs embeddings intoAmazon OpenSearch Serverless. Access is role-aware, locked down withCognito. Everything spins up clean withAWS CDK... read more  

Build an AI-powered website assistant with Amazon Bedrock
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@kala shared a link, 3 weeks, 4 days ago
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Towards Generalizable and Efficient Large-Scale Generative Recommenders

Authors discuss their approach to scaling generative recommendation models from O(1M) to O(1B) parameters for Netflix tasks, improving training stability, computational efficiency, and evaluation methodology. They address challenges in alignment, cold-start adaptation, and deployment, proposing syst.. read more  

Syself Autopilot takes care of the entire lifecycle of clusters, from provisioning to scaling, updates and other day-2 tasks. Free up your teams to work on what really matters . Use Kubernetes, don't manage.

For companies in need of tailored services, we have a dedicated team of experts in delivering cloud-native software and enterprise-grade infrastructure configuration.

Why Choose Syself:
• We've built and maintained the most popular Cluster API Provider, that manages thousands of servers in production at Hetzner
• We actively participate in the Kubernetes community, contributing to other provider integrations and the Cluster API project, ensuring alignment with community standards
• We have a team of experts distributed in 4 continents, aways ready to assist you with urgent issues or tailored advice
• We've won a public tender from the German government to build a Kubernetes-as-a-service framework for managing cluster lifecycle, aiding the government and agencies to use Cluster API

About Syself Autopilot:
• Pre-built, immutable base for 100% reproducible clusters
• Declarative, idempotente cluster definition as Kubernetes resources
• Fully compatible with GitOps and other Kubernetes-native tools
• GDPR compliant
• One click or automated upgrades of clusters, including OS, Kubernetes control and data planes and add-ons
• Self-healing: automated issue detection and fixes, without human intervention
• Users own the entire infrastructure, including control planes