Operations | Monitoring | ITSM | DevOps | Cloud

This was what Sarah was looking to solve. ⁠Managing software licenses isn’t just tracking installs—it’s about uncovering hidden usage and reclaiming wasted spend. When Sarah faced $12M in software costs, scattered licenses, and zero visibility, she needed a better way. With Nexthink, she gained real-time insights, smart user nudges, and automated reclamation. ⁠The result?

Taylor proved it—turning license headaches, VPN chaos, SCCM continuity and patch pain into a smooth, confident performance.⁠⁠Here's how Taylor did it.⁠ In the end, IT isn’t just about fixing—it’s about flowing, scaling, and making work effortless.⁠Request a demo today.

We’re pleased to announce the availability of Elastic Cloud Serverless on Google Cloud in three new regions: This doubles the number of available regions on Google Cloud and dramatically increases serverless deployment options in the US. Elastic Cloud Serverless provides the fastest way to start and scale observability, security, and search solutions without managing infrastructure.

Modern development tools, CI/CD infrastructure, and AI have accelerated the pace at which companies release software. This speed supports innovation, but it also increases complexity and the chance of something breaking in ways that aren’t immediately obvious. Teams now deal with more operational data, complex failure patterns, and systems where a small configuration change can ripple across dozens of microservices.

SquaredUp Dashboard Server (DS) and SquaredUp Cloud both deliver cutting-edge data visualization for IT and engineering teams. The two products can be used independently, or together for complete operational visibility. This article explores how SquaredUp DS and Cloud differ, when to use each, and how they work together.

Synthetic monitoring is, at its core, about visibility. It’s the practice of probing your systems from the outside to see what a user would see. But there’s a hidden parameter that determines whether those probes actually deliver value: frequency. How often you run checks is more than a technical configuration—it’s a strategic choice that ripples through detection speed, operational noise, and even your team’s credibility.

Recently, I was testing Coroot’s AI Root Cause Analysis on failure scenarios from the OpenTelemetry demo. One of them, loadgeneratorFloodHomepage, simulates a flood of excessive requests. As expected, it caused a latency degradation across the stack. Coroot’s RCA highlighted how the latency cascaded through all dependent services. At the same time, we noticed a moderate increase in CPU usage for the frontend service and the node itself.

You've got Prometheus running in one cluster — maybe a dev environment, a single EKS cluster, or a proof-of-concept setup. The configuration is straightforward: node_exporter on a few EC2 instances, some service discovery for pods, and a single Prometheus server scraping everything. Storage is local, retention is 15 days, and you can keep all the default recording rules without worrying about costs.

Carrier pigeons once flapped through war zones with vital messages. Today? Sensor fusion delivers battlefield intel faster than thought. The fight isn’t just about who has the data, it’s about who moves on it first. Speed wins wars now! Read how it’s changing the game, how deployable command and control (C2) nodes can help, and why network slicing is a key ingredient in building a resilient, high-speed transport network: Carrier Pigeons to Sensor Fusion: Speed Matters in Information.

Dan Mindru is a Frontend Developer and Designer who is also the co-host of the Morning Maker Show. Dan is currently developing a number of applications including PageUI, Clobbr, and CronTool. I find it remarkable that we’re getting so many AI startups every day. As software engineers, most of us like to know what our software is actually doing. We plan, review, and perform automatic tests to verify it’s working as expected. Then we do a round of manual testing for good measure. Not with AI.