Operations | Monitoring | ITSM | DevOps | Cloud

Every time you join a video meeting, move data between cloud environments or use an AI-powered application, your traffic travels across a complex network of interconnected infrastructure. At the heart of this global ecosystem sits the internet backbone – and the highest-performing networks within it are known as Tier 1 IP backbones.

A network monitoring platform can handle more than 1,000 devices, but the device total is only the starting point. A workable design must keep polling cycles on time, preserve visibility during failures, control notification volume, support the devices you own, and recover cleanly when the monitoring system itself has a problem. Crossing 1,000 monitored devices changes the job.

Obkio’s new Severity Summary widget is built to answer one question fast: “How healthy was my network overall, across every session I'm tracking?” Instead of opening session after session to check each one individually, you get a single combined view showing how much time your network spent in each severity level.

ICMP has no port number. It is an IP-layer protocol, number 1 in the IP header, that sits beside TCP and UDP rather than on top of them, so ping does not use a port and there is no "ping port" to open. When a firewall form asks for one, select the ICMP protocol and the echo request type instead. This post covers where ICMP sits in the stack, which types and codes you will actually meet, how to allow it through Linux, Windows and cloud firewalls, and when a ping check is the wrong check.

Someone on your team says "the Internet is slow." Twenty minutes later, IT finds out the Internet was never the problem. Maybe it was a laptop with a full RAM disk. Maybe it was an ISP outage two towns over that had nothing to do with your office. Misdiagnosing slow Internet wastes time. It sends you down the wrong fix path, like rebooting a router when the real issue is sitting on someone's desktop.

Discover how Megaport and Wasabi are expanding cloud object storage to support AI workloads, enterprise data growth, and predictable costs.