Operations | Monitoring | ITSM | DevOps | Cloud

A ServiceNow incident that notifies one person and stops isn’t escalation. It’s a coin flip on whether that one phone is on do not disturb. The record is correct, the SLA timer is running, and the whole response rests on one human feeling a buzz at three in the morning.

Plenty of ServiceNow incidents have a known fix. Restart the stuck service, clear the backed-up queue, fail over to the standby node. The runbook spells out every step, and a human still gets paged at three in the morning to follow it by hand. This guide covers what’s safe to automate, how Workflows trigger runbooks and RPA on a ServiceNow condition, how the automated action stays on the record, and where to keep a person in the loop.

Education is becoming more connected than ever across classrooms and campuses. Students learn through cloud platforms. Teachers use digital tools to collaborate and engage students. Institutions rely on connected systems to manage research, administration, communications, and campus safety. Technology is not just creating new possibilities for education, but it is also introducing new risks. Behind every device, application, and online account is a piece of valuable information.

What 554 developers and engineering leaders told us about AI, agents, and the measurement gap nobody’s closing. Ask a developer if AI made them faster this year, and 84% will say yes. Ask their VP to put a number on it for the board, and 39% will have nothing to show. That gap, not adoption, is the real story in engineering right now.

Every AI agent architecture diagram shows the same five layers: perception, memory, reasoning, action, and feedback. Each layer assumes the one before it worked correctly, and none of them can confirm that once the agent runs against live production data. Runtime context is the sixth layer most designs leave out, and it’s the one that decides whether any of the other five can be trusted.

Infrastructure for AI agents usually forces a choice between two bad options. A sandbox is safe but blind, cut off from the data and services that would make the agent's output useful. Full access means paying to keep a container idle between runs, waiting on a prompt that might not arrive for hours. Task containers, which Upsun released on August 12, 2026, are built to avoid that choice. A task container is a single-purpose container defined in a project's.upsun/config.yaml file.

You push a branch. If your team is like most, that branch now waits: for the shared staging server to free up, for someone to remember to refresh the seed data, for whoever broke staging last to fix it. By the time you actually test your change, you're testing it in an environment that's drifted from production in ways nobody fully tracked. The alternative isn't a better staging server. It doesn't need one.

Organizations replace their DCIM vendor when an unresolved pain point becomes urgent enough to act on — not because a competing platform has a longer feature list. Understanding what those pain points actually are, for each type of stakeholder in the data center ecosystem, is the clearest way to predict where DCIM displacement is happening now and where vendor stickiness will hold.

As businesses rely on cloud computing, AI, real-time communications and globally distributed applications, network latency has become a defining factor in overall network performance. While bandwidth determines how much data can be transferred, latency determines how quickly that data reaches its destination. Even a high-bandwidth connection can deliver poor application performance if latency is too high or inconsistent.

MCP is generating a lot of hype nowadays (but then again, almost anything that emerges in AI seems to attract hype). The anticipation around it is similar to the level of excitement that would break out if Apple were to finally introduce USB-C to iPhones. To be fair, though, some of that hype is warranted, considering the fact that MCP provides a standardized approach to connecting agents with third-party tools, which significantly simplifies this type of integration (hence the USB-C analogy).