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@kaptain shared a link, 6 months, 4 weeks ago
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How I Cut Kubernetes Debugging Time by 80% With One Bash Script

The reality of Kubernetes troubleshooting: 80% of the time is spent locating the issue, while only 20% is used for the fix. Managing eight Kubernetes clusters highlighted this pattern. A tool was developed to provide a complete cluster health report in under a minute, streamlining the process and sa.. read more  

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@kaptain shared a link, 6 months, 4 weeks ago
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Top 5 hard-earned lessons from the experts on managing Kubernetes

Running Kubernetes in production isn’t just clicking “Create Cluster.” It means locking down RBAC, tightening up network policy, tracking autoscaling metrics, and making sure your images don’t ship with surprises. Managed clusters help get you started. But real workloads need more: hardened configs,.. read more  

Top 5 hard-earned lessons from the experts on managing Kubernetes
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@kaptain shared a link, 6 months, 4 weeks ago
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Kubernetes Tutorial For Beginners [72 Comprehensive Guides]

The series dives deep into real-world Kubernetes - starting with hands-on setup viaKubeadmandeksctl, then moving throughmonitoring,logging,CI/CD, andMLOps. It tracks key release changes up tov1.30, including the confirmed death ofDockershimsince v1.24... read more  

Kubernetes Tutorial For Beginners [72 Comprehensive Guides]
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@kaptain shared a link, 6 months, 4 weeks ago
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The guide to kubectl I never had.

Glasskube dropped a thorough guide tokubectl- the commands, the flags (--dry-run, etc.), how to chain stuff together, and how to keep your config sane. Bonus: a solid roundup ofkubectl plugins. Think observability (like K9s), policy checks, audit trails, and Glasskube’s take on declarative package m.. read more  

The guide to kubectl I never had.
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@kala shared a link, 6 months, 4 weeks ago
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20x Faster TRL Fine-tuning with RapidFire AI

RapidFire AI just dropped a scheduling engine built for chaos - and control. It shards datasets on the fly, reallocates as needed, and runs multipleTRL fine-tuning configs at once, even on a single GPU. No magic, just clever orchestration. It plugs into TRL withdrop-in wrappers, spreads training acr.. read more  

20x Faster TRL Fine-tuning with RapidFire AI
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@kala shared a link, 6 months, 4 weeks ago
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Code execution with MCP: building more efficient AI agents

Code is taking over MCP workflows - and fast. With theModel Context Protocol, agents don’t just call tools. They load them on demand. Filter data. Track state like any decent program would. That shift slashes context bloat - up to 98% fewer tokens. It also trims latency and scales cleaner across tho.. read more  

Code execution with MCP: building more efficient AI agents
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@kala shared a link, 6 months, 4 weeks ago
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Hacking Gemini: A Multi-Layered Approach

A researcher found a multi-layer sanitization gap inGoogle Gemini. It let attackers pull off indirect prompt injections to leak Workspace data - think Gmail, Drive, Calendar - using Markdown image renders across Gemini andColab export chains. The trick? Sneaking through cracks between HTML and Markd.. read more  

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@kala shared a link, 6 months, 4 weeks ago
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'I'm deeply uncomfortable': Anthropic CEO warns that a cadre of AI leaders, including himself, should not be in charge of the technology’s future

Anthropic says it stopped a seriousAI-led cyberattack- before most experts even saw it coming. No major human intervention needed. They didn't stop there. Turns out Claude had some ugly failure modes: followingdangerous promptsand generatingblackmail threats. Anthropic flagged, documented, patched, .. read more  

'I'm deeply uncomfortable': Anthropic CEO warns that a cadre of AI leaders, including himself, should not be in charge of the technology’s future
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@kala shared a link, 6 months, 4 weeks ago
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Building serverless applications with Rust on AWS Lambda

AWS Lambda just bumpedRusttoGeneral Availability- production-ready, SLA covered, and finally with full AWS Support. Deploy withCargo Lambda. Wire it into your stack usingAWS CDK, which now has a dedicated construct to spin up HTTP APIs with minimal fuss. System-level shift:Serverless isn't just for .. read more  

Building serverless applications with Rust on AWS Lambda
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@kala shared a link, 6 months, 4 weeks ago
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How to write a great agents.md: Lessons from over 2,500 repositories

A GitHub Copilot feature allows for custom agents defined inagents.mdfiles. These agents act as specialists within a team, each with a specific role. The success of an agents.md file lies in providing a clear persona, executable commands, defined boundaries, specific examples, and detailed informati.. read more  

How to write a great agents.md: Lessons from over 2,500 repositories
OpenClaw is an open-source autonomous AI assistant platform that runs locally on user hardware and integrates with popular messaging applications. Originally released in late 2025 under the name Clawdbot, the project was briefly rebranded as Moltbot before settling on the name OpenClaw in early 2026. It enables users to interact with AI models through interfaces like WhatsApp, Telegram, Discord, Slack, and more, allowing the assistant to carry out tasks ranging from calendar management and email handling to automated scripting and workflow execution based on user instructions.

Unlike typical cloud-hosted AI services, OpenClaw emphasizes privacy and control by running on the user’s own machine, giving users choice over infrastructure and data. Its extensible design supports a wide range of integrations and skills, which automates interactions with external tools and services. This flexibility has contributed to its rapid adoption and widespread discussion within the AI community, with media coverage highlighting both its capabilities and associated security considerations.