Updates and recent posts about Gemini 3..

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@radhika_rv16 shared a link, 1 week ago

SRE, Writer

Platform Engineering: From Bash Scripts to AI-Powered Platforms — and What Comes Next

I once got a Slack message at 11pm: "hey, prod seems slow?" No runbook. No alert. Just me, SSH'd into a box, squinting at top output. That was platform engineering. Here's how far we've come — and where AI is taking us next.

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@eon01 published a course, 1 week ago

Founder, FAUN.dev

GitOps the Hard Way, with Argo CD

#Helm #gitops #Argo CD #gitlab #kuberne...

Build Real GitOps Pipelines From Empty Clusters to Automated Deploys

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@laura_garcia shared a post, 1 week, 1 day ago

Software Developer, RELIANOID

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@work4bots started using tool Spring , 1 week, 3 days ago.

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@work4bots started using tool Helm , 1 week, 3 days ago.

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@work4bots started using tool Azure Kubernetes Service (AKS) , 1 week, 3 days ago.

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@work4bots started using tool Azure , 1 week, 3 days ago.

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@work4bots added a new tool Bicep , 1 week, 3 days ago.

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@eon01 shared a post, 1 week, 3 days ago

Founder, FAUN.dev

AWX in Action is out, and there's a course

#red hat... #ansible #Tower #AWX

"AWX in Action: Ansible Orchestration at Scale" is now available in print and ebook. It covers running AWX on Kubernetes for real, not a sandbox demo that falls over the moment you add a second execution node.

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.