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@anjali shared a link, 1 year, 3 months ago
Customer Marketing Manager, Last9

Windows Event Logs: Monitoring, Alerts, and Compliance

Learn how to monitor Windows Event Logs, set up alerts, and ensure compliance with proper log retention and archiving strategies.

windows
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@anjali shared a link, 1 year, 3 months ago
Customer Marketing Manager, Last9

Why Server Health Monitoring Matters (And How to Do It Right)

Monitoring server health helps prevent downtime, spot issues early, and keep systems running smoothly. Here’s how to do it the right way.

ngnix monitoring
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@anjali shared a link, 1 year, 3 months ago
Customer Marketing Manager, Last9

OpenTelemetry Visualization Setup: A Developer's Guide

Learn how to set up OpenTelemetry visualization, choose the right tools, and configure dashboards for actionable insights.

open
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@squadcast shared a post, 1 year, 3 months ago

Datadog vs Prometheus: Two Major Monitoring Tools Compared

Datadog and Prometheus are leading monitoring tools with different strengths. Datadog offers a comprehensive SaaS solution with built-in integrations and intuitive dashboards, ideal for teams seeking minimal setup. Prometheus provides a powerful open-source alternative with excellent Kubernetes integration and scalability for cloud-native environments, though requiring more technical expertise. Choose Datadog for ease-of-use and all-in-one monitoring, or Prometheus for cost-effectiveness and customizability in cloud-native infrastructure.

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@anjali shared a link, 1 year, 3 months ago
Customer Marketing Manager, Last9

8 Best Grafana Alternatives: Open-Source & Commercial

Explore the top 8 Grafana alternatives, including open-source and commercial tools, to find the best monitoring solution for your needs.

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@laura_garcia shared a post, 1 year, 3 months ago
Software Developer, RELIANOID

A big Thank you!

🌟 A Big Thank You! 🌟 We’re incredibly grateful for the positive feedback on our Support Service! Providing fast, reliable, and expert assistance is a top priority for us, and it’s always rewarding to hear that we’re making a difference. A huge thank you to our team for their dedication and to our cu..

egemen felicitacion editada RELIANOID
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@anjali shared a link, 1 year, 3 months ago
Customer Marketing Manager, Last9

Apache Monitoring: Setup Guide, Tools, and Best Practices

Learn how to monitor Apache effectively with this guide on setup, essential tools, and best practices for performance optimization.

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@laura_garcia shared a post, 1 year, 3 months ago
Software Developer, RELIANOID

RELIANOID at FinovateEurope!

🚀 RELIANOID is attending FinovateEurope 2025! 🌍 📍 London, UK 📅 February 25-26, 2025 FinovateEurope is Europe's leading fintech conference, and we’re excited to be part of it! With 30+ live demos showcasing cutting-edge fintech solutions, you'll discover the technologies shaping 2025 and beyond. 🌟..

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@squadcast shared a post, 1 year, 3 months ago

Prometheus vs Datadog: A Complete Comparison Guide for 2025

Datadog Prometheus

Prometheus is a free, open-source monitoring solution ideal for technical teams who prefer complete control and Kubernetes environments. It uses a pull-based model and requires more technical expertise to maintain. Datadog is a comprehensive, subscription-based platform offering 600+ integrations, advanced analytics, and minimal maintenance overhead, making it better suited for enterprise environments and multi-cloud deployments. Choose Prometheus for cost-effectiveness and customization, or Datadog for ease of use and advanced features.

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@squadcast shared a post, 1 year, 3 months ago

How to Reduce MTTR: A Comprehensive Guide to Faster Incident Resolution

To reduce MTTR (Mean Time to Resolve/Restore), organizations should implement intelligent incident detection using AI/ML, integrate alerting and diagnostic systems, automate responses through IaC and chaos engineering, enhance real-time communication, maintain updated runbooks, and focus on continuous team training. These strategies, combined with robust system architecture and clear procedures, help teams resolve incidents faster and maintain higher service reliability.

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.