Operations | Monitoring | ITSM | DevOps | Cloud

In bridging traditional enterprise environments with modern GPU resources, we're helping organizations build AI infrastructure that's truly ready for production workloads. Co-authored by Duncan Ng, Vice President Solutions Engineering, Vultr As enterprises move from AI experimentation to production deployment, most are realizing a fundamental truth: Successful AI adoption requires more than just access to GPU computing power.

Here at Honeycomb, we emphasize that organizations are sociotechnical systems. At a high level, that means that “wet-brained” people and the stuff they do is irreducible to “dry-brained” computations. That cashes out as the inability to ultimately remove or replace people in organizations with computers, in spite of what artificial general intelligence (AGI) ideologues would have you believe.

Cybersecurity in the Industrial Internet of Things (IIoT) is often overlooked despite powering critical infrastructure such as energy grids, telecom networks, factories, robotics, and aerospace, all of which are prime targets for cyberattacks and data breaches. A single breach can disrupt essential services or expose sensitive data. So, how do we stay ahead of bad actors and proactively defend these systems?

Cloud networking costs can escalate due to inefficient routing and limited visibility. Kentik’s cloud visibility and analytics solution helps engineers optimize transit, reduce costs, and improve performance by analyzing AWS Transit Gateways and exploring alternatives like direct peering, storage endpoints, and AWS CloudWAN.

With the new Pandora ITSM version 105, you now have features designed to improve your workflow and optimize ticket and project management.

Debugging distributed systems can often feel like searching for a needle in a haystack. When issues arise, engineers need faster ways to pinpoint critical spans within their traces. With our latest Deeper Trace Analytics update, SigNoz now enables powerful filtering for root and entry spans—making it significantly easier to analyze and debug distributed traces.

Engineering’s gotten really complicated. The rush to “innovate or die” created more code, more tools, and more teams—without a single, unifying way to keep it all healthy and moving. The result? Orphaned services, slow releases, and endless overhead... just to name a few.

Uptime monitoring checks whether a website, server, or online service is available. It runs automated tests at set intervals, verifying responses and sending alerts if a failure occurs. Businesses rely on uptime monitoring to detect issues early, prevent revenue loss, and maintain customer trust. A website outage can harm reputation, impact SEO rankings, and disrupt operations.