Operations | Monitoring | ITSM | DevOps | Cloud

Introducing Kentik AI Advisor. AI with a comprehensive understanding of your network that thinks critically and advises how to design, operate, and protect infrastructure at scale. With the rise of hybrid cloud networks and the growing demands of AI infrastructure, network teams are under pressure to balance cost, performance, and security, often with limited resources that delay critical strategic initiatives.

Bringing together a host of traditional and modern powerful test data management capabilities, Redgate Test Data Manager allows users to.

In this episode of Masters of Data, we dive into how AI learns, examining both how we teach it and what it derives from human performance, as well as why context plays a crucial role in AI interactions. We break down five key components of AI training and talk about why we should view AI as a tool under human control rather than an autonomous entity. We explore the challenge of maintaining context in AI—much like our own memory struggles—and discuss methods, such as retrieval-augmented generation, that can help AI retain context more effectively.

With Datadog GPU Monitoring, engineering and ML teams can monitor GPU fleet health across cloud, on-prem, and GPU-as-a-Service platforms like Coreweave and Lambda Labs. Real-time insights into allocation, utilization, and failure patterns make it easy to spot bottlenecks, eliminate idle GPU spend, and resolve provisioning gaps. By tying usage metrics directly to cost and surfacing hardware and networking issues impacting performance, Datadog helps teams make fast, cost-efficient decisions to keep AI workloads running reliably at scale.

Microsoft has identified a zero-day vulnerability in the Windows kernel, rated 7.0 on the CVSS scale. Organizations often misprioritize vulnerabilities, focusing on high-severity scores instead of those actively exploited. Many lower-severity vulnerabilities are chained by attackers. A risk-based approach to vulnerability management is crucial. Current Windows OS versions are affected, and organizations should consider Extended Security Updates to mitigate risks as more zero days are anticipated.

This video provides a step-by-step walkthrough for configuring monitoring for.NET applications running on Linux using SolarWinds Observability. The demonstration covers the full setup process—from adding a new service to verifying the APM library connection. Topics covered in this video include: This guide is intended for developers, system administrators, and DevOps engineers who need to quickly and reliably instrument.NET applications on Linux for performance monitoring and observability.

Looking for a faster way to discover every device on your network? This video walks through how SolarWinds Observability automatically scans and classifies network gear—including routers, switches, access points, firewalls, and SD-WAN devices—in seconds. You’ll learn how to: This is the easiest way to get full network visibility without scripts, config files, or manual inventory work.

Chaos Engineering isn’t about breaking things. It’s about being thoughtful about failure to learn something. Gremlin founder and CEO Kolton Andrus lays it out in this clip from when he sat down with Stephen Townshend on the Slight Reliability podcast!

Your laptop is powerful enough to run your own LLM. Here's why that matters While centralized AI tools help teams, they miss something critical: your personal knowledge. Meeting notes, tips, tricks, and context only you have. Kyle Fransham shows how running a local LLM changes the game. Index your own "master document of knowledge" and query it right in your dev environment. No cloud needed. The tools are accessible. The setup is simple. And the impact? Game-changing for how you work.

Good observability starts with good data. In this clip, we hear how Cribl gives teams real control over their data pipelines so they can collect, enrich, and route telemetry from any source to the right destination. It is not just about more dashboards or another platform. It is about building an observability ecosystem that connects IT, security, and the business through cleaner data and smarter AIOps. Tool rationalization and AI driven pipelines are not future goals. They are happening right now.