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@faun shared a link, 1 year, 2 months ago
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Every pod eviction in Kubernetes, explained

Kubernetes governs pod lifecycles with various eviction techniques that can influence availability and sometimes disregard PodDisruptionBudgets. To address nodes under duress, Kubelet takes action. At the same time, eviction APIs, taints, and kube-schedulers oust pods according to priority. Configur.. read more  

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@faun shared a link, 1 year, 2 months ago
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Ingress-nginx CVE-2025-1974: What You Need to Know

Ingress-nginx patches critical vulnerabilities in CVE-2025-1974, compelling users to upgrade for secure cluster management. Versionsv1.12.1 and v1.11.5eliminate these flaws. If an immediate upgrade isn't feasible, users should consider disabling the Validating Admission Controller... read more  

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@anjali shared a link, 1 year, 2 months ago
Customer Marketing Manager, Last9

Python Loguru: The Logging Cheat Code You Need in Your Life

If logging in Python feels like a chore, Loguru is the cheat code you need—zero boilerplate, rich features, and pure simplicity!

logging
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@anjali shared a link, 1 year, 2 months ago
Customer Marketing Manager, Last9

New Relic vs Datadog: The Complete Comparison

New Relic or Datadog? Compare features, pricing, and performance to find the right observability tool for your needs.

datadog
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@laura_garcia shared a post, 1 year, 2 months ago
Software Developer, RELIANOID

Live Technical Support

Are you ready to see real support in action? Check out our latest video featuring one of our expert support technicians working live with a client to migrate from v6.2 to v8. In this session, we not only recreated the cluster but also ensured that every service is operating flawlessly. It’s a clear ..

network virtual interfaces
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@anjali shared a link, 1 year, 2 months ago
Customer Marketing Manager, Last9

MySQL Logs: Your Guide for Database Performance

Struggling with slow queries? MySQL logs hold the answers! Learn how to read them, fix issues, and boost your database performance.

redis
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@laura_garcia shared a post, 1 year, 2 months ago
Software Developer, RELIANOID

Application Layer Gateway Properties

When dealing with modern network security and performance challenges, Application Layer Gateways (ALGs) play a crucial role in ensuring seamless communication, security, and optimization at the application layer. But what makes an ALG so important? ✅ Protocol Awareness: ALGs understand and modify sp..

Application Layer Gateway properties
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@anjali shared a link, 1 year, 2 months ago
Customer Marketing Manager, Last9

Ubuntu Crash Logs: Find, Fix, and Prevent System Failures

Learn how to find and use Ubuntu crash logs to troubleshoot issues, prevent future failures, and keep your system running smoothly.

logs
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@anjali shared a link, 1 year, 2 months ago
Customer Marketing Manager, Last9

RabbitMQ Logs: Monitoring, Troubleshooting & Configuration

If RabbitMQ queues are backing up or messages aren’t being consumed, logs can help you figure out what’s wrong. Here’s how to monitor and fix issues.

rabbit
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@laura_garcia shared a post, 1 year, 2 months ago
Software Developer, RELIANOID

🔹 How Load Balancing in IIS Server Works 🔹

Efficient load balancing is crucial for maintaining high availability and optimal performance in IIS Server environments. By distributing client requests across multiple servers, load balancing prevents overload, ensures reliability, and enhances scalability. Key aspects of IIS load balancing includ..

Load Balancing in IIS Server
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.