ContentPosts from @rajatcoding..
Link
@faun shared a link, 8 months, 3 weeks ago
FAUN.dev()

Linux Detection Engineering - A Sequel on Persistence Mechanisms

PANIX turns the tangled web of Linux persistence and Process Capabilities on its head. It makes them as easy to test as flipping a light switch—and sharpens your detection game along the way... read more  

Linux Detection Engineering - A Sequel on Persistence Mechanisms
Link
@faun shared a link, 8 months, 3 weeks ago
FAUN.dev()

AWS Well-Architected Framework: Performance Efficiency Pillar

The AWS Well-Architected Framework's Performance Pillar champions nimble, cloud-native and serverless-first approaches. These tactics help systems pivot like a ballerina, dodge vendor lock-in, and slash costs. WithWardley Mapping, gain clarity. Prioritize flexibility. Ditch the shackles of hard-code.. read more  

AWS Well-Architected Framework: Performance Efficiency Pillar
Link
@faun shared a link, 8 months, 3 weeks ago
FAUN.dev()

Measure risk probability in IAM

AWS actions don't always pick up list capabilities from resource types automatically. You'll often find yourself manually specifying list actions, which throws a wrench into Attribute-Based Access Control (ABAC) plans. AWS docs on dependency themes like PassRole? Incomplete at best. Cue the unexpect.. read more  

Measure risk probability in IAM
Story
@laura_garcia shared a post, 8 months, 3 weeks ago
Software Developer, RELIANOID

📍 VI Cybersecurity & Data Innovation Summit

🛡️ Madrid: The Hub of Cybersecurity Innovation in 2025 🗓️ April 29th | Madrid, Spain Over 300 cybersecurity professionals will gather to explore the future of digital protection — and RELIANOID will be there! What to expect: 🔹 Inspiring keynotes & expert panels on cybersecurity trends. 🔹 Live demos ..

VI CYBERSECURITY & DATA INNOVATION SUMMIT 2025 RELIANOID
Link
@anjali shared a link, 8 months, 3 weeks ago
Customer Marketing Manager, Last9

Distributed Network Monitoring: Guide to Getting Started & Troubleshooting

A practical guide to getting started with distributed network monitoring and solving common issues across modern, complex systems.

monitoring
Story
@laura_garcia shared a post, 8 months, 3 weeks ago
Software Developer, RELIANOID

🌍💡 World Creativity and Innovation Day — April 21 💡🌍

At RELIANOID, creativity isn’t just a value — it’s the foundation of everything we do. In a world where technology evolves at lightning speed, standing still is not an option. That’s why our team constantly challenges the status quo, reimagining howApplication Delivery, Security, and High-Performanc..

World-Creativity-and-Innovation-Day RELIANOID
Link
@anjali shared a link, 8 months, 3 weeks ago
Customer Marketing Manager, Last9

A Comprehensive Guide to Monitoring Disk I/O on Linux

Learn how to monitor and optimize disk I/O performance on Linux with this comprehensive guide to better manage system resources.

logging
Link
@faun shared a link, 8 months, 3 weeks ago
FAUN.dev()

Kagent: Bringing Agentic AI to Cloud Native

Kagentrides on the back ofMicrosoft’s AutoGenlike a pro. This nifty tool empowers DevOps ninjas to unleash AI agents inKubernetes. Picture it automating all the drudgework: configuration hassles, network security fiddling—you name it. By syncing up with power players likePrometheusandArgo, it transf.. read more  

Kagent: Bringing Agentic AI to Cloud Native
Link
@faun shared a link, 8 months, 3 weeks ago
FAUN.dev()

Creating a ClickHouse Cluster on Raspberry Pis

Craft a miniature powerhouse with threeRaspberry Pi 5s, each kitted out with NVMe drives. It's your ticket to an eye-opening, hands-on Kubernetes adventure. Start by installingK3s—the featherweight Kubernetes hero. Then, unleash theAltinity Operatorto deftly manage yourClickHousecluster. Say goodbye.. read more  

Creating a ClickHouse Cluster on Raspberry Pis
Link
@faun shared a link, 8 months, 3 weeks ago
FAUN.dev()

Understanding new GKE inference capabilities

Google Cloud Nextswings open the curtains on GKE’s latest tricks for inference. Imagine serving costs dropping by 30%, tail latency by 60%, and a whopping 40% leap in throughput. Talk about upgrades with attitude!.. read more  

Understanding new GKE inference capabilities