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

NEW RELEASE: RELIANOID 8.4 Enterprise Edition is here!

- We’re excited to announce the launch of RELIANOID 8.4, bringing greater performance, security, and automation to your Application Delivery Infrastructure. - What’s new in 8.4: - High-Performance Proxy – Now with HTTP/2 support and Hot Restart for seamless, zero-downtime updates. - Multi-Factor Aut..

RELIANOID Enterprise Edition 8.4.0
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@anjali shared a link, 2 months ago
Customer Marketing Manager, Last9

OpenTelemetry Spans Explained: Deconstructing Distributed Tracing

Understand how OpenTelemetry Spans capture, connect, and explain every operation in your distributed system for deeper visibility.

otel
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@laura_garcia shared a post, 2 months ago
Software Developer, RELIANOID

🔁 In case you missed it:Incident Response in 2025: Lessons Learned

🔁 In case you missed it: Our August blog post — “Incident Response in 2025: Lessons Learned” — looks back at a summer marked by major cyber incidents, from supply chain disruptions to large-scale data breaches. Discover how AI-driven detection, faster response strategies, and new resilience tools ar..

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

Top 9 APM Tools for Node.js Performance Monitoring

Compare top APM tools for Node.js — from open-source options to enterprise-grade platforms — and choose the best fit for your stack.

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

Top 11 Ruby APM Tools for 2025: A Performance-Driven Selection

Explore the top Ruby APM tools for 2025 — from open-source to enterprise — to monitor, trace, and optimize your app’s performance.

nodejs_apm
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@laura_garcia shared a post, 2 months ago
Software Developer, RELIANOID

🔐 Defense-in-depth is no longer a theory—it's a necessity in industrial networks.

In our latest article, we explore how industrial sectors are implementing network segmentation and microsegmentation to protect critical systems. From vertical and horizontal segmentation models to modern OT firewalls and IoT gateways, we break down the architectures and tools driving zero-trust in ..

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

🌍 RELIANOID at DevOpsDays Almaty 2025 | 24 October | Almaty, Kazakhstan

DevOpsDays — a global series of technical conferences uniting software development and IT operations professionals — is coming to Almaty on 24 October 2025! 🎉 This event will gather local and international experts, engineers, and businesses to share insights, drive collaboration, and grow the DevOp..

devopsdays almaty event
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@laura_garcia shared a post, 2 months, 1 week ago
Software Developer, RELIANOID

🚨 Cyberattack on Qantas exposed growing threats to aviation

A few months ago, up to 6 million customers were affected through a third-party data breach — reportedly linked to Scattered Spider, a group notorious for social engineering and supply chain attacks. 🔍 The takeaway? The weakest link often lies outside the organization. ✈️ At RELIANOID, we helped air..

Magika is an open-source file type identification engine developed by Google that uses machine learning instead of traditional signature-based heuristics. Unlike classic tools such as file, which rely on magic bytes and handcrafted rules, Magika analyzes file content holistically using a trained model to infer the true file type.

It is designed to be both highly accurate and extremely fast, capable of classifying files in milliseconds. Magika excels at detecting edge cases where file extensions are incorrect, intentionally spoofed, or absent altogether. This makes it particularly valuable for security scanning, malware analysis, digital forensics, and large-scale content ingestion pipelines.

Magika supports hundreds of file formats, including programming languages, configuration files, documents, archives, executables, media formats, and data files. It is available as a Python library, a CLI, and integrates cleanly into automated workflows. The project is maintained by Google and released under an open-source license, making it suitable for both enterprise and research use.

Magika is commonly used in scenarios such as:

- Secure file uploads and content validation
- Malware detection and sandboxing pipelines
- Code repository scanning
- Data lake ingestion and classification
- Digital forensics and incident response