Updates and recent posts about Gemini 3..

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@faun shared a link, 1 year, 2 months ago

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Running Docker Containers on Kubernetes Without a Container Runtime Using WasmEdge

WasmEdgedoesn't just compete with old-school OCI runtimes—it obliterates them with lightning-fast startups. It takes a chainsaw to resource waste and security headaches, thanks to its ironclad sandboxing. Its cross-platform magic dances acrossx86, ARM, and RISC-Vwith zero configuration drama. A drea.. read more

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@faun shared a link, 1 year, 2 months ago

FAUN.dev()

Platformless: How Choreo Built a Secure Kubernetes Platform with GitOps

Choreo by WSO2dreams big, plotting to eclipse Kubernetes. It's not just any platform; it's anenterprise-grade Internal Developer Platformwrapped in an elegant UI. Think of it as a tech ballerina effortlessly twirling around more than 20 CNCF tools. The goal? Make code deployment child's play while b.. read more

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@viktoriiagolovtseva shared a post, 1 year, 2 months ago

How to Calculate Productivity in Jira: A Comprehensive Guide

Struggling to measure your team’s performance in Jira? Discover how to turn raw data into actionable productivity insights!

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@anjali shared a link, 1 year, 2 months ago

Customer Marketing Manager, Last9

The Role of Log Shippers in Your Stack

Log shippers quietly move logs to where they’re needed—making debugging, monitoring, and observability possible without the chaos.

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@anjali shared a link, 1 year, 2 months ago

Customer Marketing Manager, Last9

The Ultimate Guide to Ubuntu Performance Monitoring

A practical guide to monitoring performance on Ubuntu—tools, tips, and commands to keep your system running efficiently.

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@anjali shared a link, 1 year, 2 months ago

Customer Marketing Manager, Last9

API Latency: Definition, Measurement, and Optimization Techniques

Learn what API latency really means, how to measure it the right way, and practical ways to make your APIs respond faster.

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@laura_garcia shared a post, 1 year, 2 months ago

Software Developer, RELIANOID

🌐 Understanding the Five Eyes Coalition and Embracing Secure Innovation 🔒

The Five Eyes (FVEY) Coalition, an alliance of the US, UK, Canada, Australia, and New Zealand, has been a cornerstone of global intelligence sharing since WWII. Over the decades, its mission has evolved to address modern challenges like cybersecurity, critical infrastructure protection, and counteri..

The Five Eyes Coalition_ Origins, Evolution, and Principles of Secure Innovation Solutions

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@laura_garcia shared a post, 1 year, 2 months ago

Software Developer, RELIANOID

🚀 We’re heading to QCon London 2025! 🚀

From April 7th to 10th, RELIANOID will be joining some of the brightest minds in software development at QCon London, where pioneers and senior engineers share the latest trends, best practices, and real-world case studies. 🔹 What to Expect at QCon London? ✅ Emerging trends in software architecture,..

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@anjali shared a link, 1 year, 2 months ago

Customer Marketing Manager, Last9

How to Configure ContainerPort in Kubernetes (The Easy Way)

Learn how ContainerPort works in Kubernetes, why it matters, and how to configure it correctly for simplified container networking.

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@anjali shared a link, 1 year, 2 months ago

Customer Marketing Manager, Last9

Log4j vs Log4j2: Which Logging Framework Should You Choose

Choosing between Log4j and Log4j2? Log4j2 offers better performance, security, and flexibility. Here's why it might be the right choice for you.

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.