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@faun shared a link, 3 months, 1 week ago
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Rethinking Efficiency for Cloud-Native AI Workloads

AI isn’t just burning compute—it's torching old-school FinOps. Reserved Instances? Idle detection? Cute, but not built for GPU bottlenecks and model-heavy pipelines. What’s actually happening:Infra teams are ditching cost-first playbooks for something smarter—business-aligned orchestrationthat chas.. read more  

Rethinking Efficiency for Cloud-Native AI Workloads
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@faun shared a link, 3 months, 1 week ago
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Why I Ditched Docker for Podman (And You Should Too)

Older container technologies like Docker have been prone to security vulnerabilities, such as CVE-2019-5736 and CVE-2022-0847, which allowed for potential host system compromise. Podman changes the game by eliminating the need for a persistent background service like the Docker daemon, enhancing sec.. read more  

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@faun shared a link, 3 months, 1 week ago
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Dynamic Kubernetes request right sizing with Kubecost

Kubecost’s Amazon EKS add-on now handlesautomated container request right-sizing. That means teams can tweak CPU and memory requests based on actual usage—once or on a recurring schedule. Optimization profiles are customizable, and resizing can be baked into cluster setup using Helm. Yes, that mean.. read more  

Dynamic Kubernetes request right sizing with Kubecost
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@laura_garcia shared a post, 3 months, 2 weeks ago
Software Developer, RELIANOID

🌐 NIS2 is reshaping cybersecurity compliance across Europe.

At RELIANOID, we are fully aligned and compliant with NIS2 requirements, helping organizations strengthen their security posture. 👉 Explore more: https://www.relianoid.com/security-compliances/relianoid-nis2-compliance/ #NIS2#CyberSecurity#Compliance#Regulation#EUCompliance#InfoSec#DataProtection#Go..

nis2 compliance RELIANOID
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@ketbostoganashvili shared a post, 3 months, 2 weeks ago
Technical Content Writer

Send emails with Vercel and Mailtrap

Next.js Vercel Mailtrap.io

Learn how to integrate Mailtrap with your Vercel-hosted applications to send transactional emails with reliable delivery and comprehensive analytics.

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@ketbostoganashvili shared a post, 3 months, 2 weeks ago
Technical Content Writer

Send emails with Bolt.new and Mailtrap

Bolt Mailtrap.io

Learn how to integrate Mailtrap with your Bolt.new application to send transactional emails and manage contacts without writing complex code.

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@anjali shared a link, 3 months, 2 weeks ago
Customer Marketing Manager, Last9

APM for Kubernetes: Monitor Distributed Applications at Scale

Understand Kubernetes APM by linking request flows with pod, node, and cluster data to get complete visibility at scale.

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@laura_garcia shared a post, 3 months, 2 weeks ago
Software Developer, RELIANOID

🌊 Load Balancing Smart Wave with RELIANOID — Built for Marine Telemetry

The Smart Wave platform is key for real-time telemetry from offshore buoys, vessels, and coastal stations. But how do you ensure it performs reliably — even over satellite links? We've published a new technical guide showing how to load balance Smart Wave using RELIANOID: ✅ MQTT & TCP ingestion for ..

Knowledge base_how to load balance SMART WAVE_blue economy
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@faun shared a link, 3 months, 2 weeks ago
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What makes Claude Code so damn good (and how to recreate that magic in your agent)!?

Claude Code skips the multi-agent circus. One main loop. At most, one fork in the road. Everything runs through a flat message history, tracked by a tidy little to-do list. Over half its LLM calls? Outsourced to lighter, cheaper models likeclaude-3-5-haiku. Smart split: heavyweight reasoning when y.. read more  

What makes Claude Code so damn good (and how to recreate that magic in your agent)!?
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@faun shared a link, 3 months, 2 weeks ago
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My Own DNS Server At Home

RunningBIND on Fedora with Podmanputs you in the driver’s seat—local DNS, full zone control, and no third-party middlemen. It handles staticforward/reverse zonesacross multiple IPv4 subnets, skips the mess of dynamic updates, and plugs into your router as a recursiveforwarding resolver. Call it a se.. read more  

My Own DNS Server At Home
Gemini 3 is Google’s third-generation large language model family, designed to power advanced reasoning, multimodal understanding, and long-running agent workflows across consumer and enterprise products. It represents a major step forward in factual reliability, long-context comprehension, and tool-driven autonomy.

At its core, Gemini 3 emphasizes low hallucination rates, deep synthesis across large information spaces, and multi-step reasoning. Models in the Gemini 3 family are trained with scaled reinforcement learning for search and planning, enabling them to autonomously formulate queries, evaluate results, identify gaps, and iterate toward higher-quality outputs.

Gemini 3 powers advanced agents such as Gemini Deep Research, where it excels at producing well-structured, citation-rich reports by combining web data, uploaded documents, and proprietary sources. The model supports very large context windows, multimodal inputs (text, images, documents), and structured outputs like JSON, making it suitable for research, finance, science, and enterprise knowledge work.

Gemini 3 is available through Google’s AI platforms and APIs, including the Interactions API, and is being integrated across products such as Google Search, NotebookLM, Google Finance, and the Gemini app. It is positioned as Google’s most factual and research-capable model generation to date.