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Updates and recent posts about Gemini 3..

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@shurup shared a post, 11 months ago

@palark

Looking for a Kaniko alternative to build containers? Give werf a try

#contain... #Contain... #Cloud N... #werf #kuberne...

Since Kaniko is no longer maintained, you might be looking for another tool to build your containers in a Kubernetes-based environment. werf is a CNCF Sandbox project that might be helpful in your case.

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@alberthiltonn shared a post, 11 months ago

A Quick Guide on How to Build an AI MVP Application

#Build a... #AI MVP ...

Build an AI MVP by defining the problem, researching the market, assembling a team, choosing the right technology, preparing data, prototyping, testing, and refining based on feedback.

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@makhtar shared a post, 11 months ago

Marketing Consultant, Read Dive

Magento Web Design: The Ultimate Guide for Ecommerce Success

Magento is one of the most powerful e-commerce platforms in the world. It offers flexibility, control, and tools for building great online stores. But success with Magento starts with smart and simple web design.

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@makhtar shared a post, 11 months ago

Marketing Consultant, Read Dive

CloudFront Pricing Explained: A Complete Beginner’s Guide for 2025

Amazon CloudFront is a content delivery network (CDN). It helps websites load faster by using global edge locations.

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@laura_garcia shared a post, 11 months ago

Software Developer, RELIANOID

🚀 Boost Network Performance with ECMP

Equal-Cost Multi-Path (ECMP) allows multiple paths with the same cost to be used simultaneously — optimizing traffic, increasing redundancy, and improving throughput. 🔹 Key Benefits • Load balancing across equal-cost routes • Seamless failover and redundancy • Better bandwidth usage and lower laten..

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@mostafahussein shared a link, 11 months ago

Kafka Encryption for Cardholder Data: Solving PCI Challenges with Kroxylicious

#kafka #pci #DevSecO... #cyberse... #kroxyli...

Encrypt Kafka messages at rest without changing app code — using Kroxylicious and OpenBao to meet PCI encryption requirements.

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@faun shared a link, 11 months, 1 week ago

FAUN.dev()

Weaponizing Dependabot: Pwn Request at its finest

GitHub bots like Dependabot might merge malicious code due to "Confused Deputy" attacks, escalating to command injection via crafted branch names. New TTPs reveal clever ways attackers exploit these issues... read more

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@faun shared a link, 11 months, 1 week ago

FAUN.dev()

GitOps in 2025: From Old-School Updates to the Modern Way

GitOpshas taken the throne, withGitas the undisputed oracle for configurations. Welcome to a world whereArgo CDandFluxstrut their stuff. By 2025, this lively dance ofpull-basedmagic reshapes the landscape. GitOps isn't just a tool anymore—it's a full-blown, no-holds-barred platform transformation... read more

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@faun shared a link, 11 months, 1 week ago

FAUN.dev()

Clarifying Roles in Data and Engineering: Why Specialization Matters

Data Analystssift through the past usingSQLandBI tools. Their goal? Unearthing insights. Meanwhile,Data Scientistsharness the power ofPythonandRto gaze into the future—predicting trends like data-driven oracles. On another front,Data Engineerscraft pipelines. ThinkApache Spark—the stage manager for .. read more

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@faun shared a link, 11 months, 1 week ago

FAUN.dev()

Terraform security: 5 foundational practices

Lock downTerraformlike Fort Knox. Verify your module origins. Guard sensitive state data like a nosy neighbor's business. And, please, no hardcoded credentials—rookie mistake. For ironclad security, pin those module versions, tap into private registries, and wield the power of dynamic provider crede.. read more

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.