Operations | Monitoring | ITSM | DevOps | Cloud

Most organizations have responded to the rapid growth of AI by creating written policies that define acceptable use. A clear AI policy can establish expectations, assign responsibilities, and help employees understand how AI should and shouldn’t be used. But policy alone can’t provide oversight and is almost impossible to enforce at scale without the right tools.

How to export a Microsoft Teams chat - manual options, Purview eDiscovery for admins, what happens after a user leaves the organization, and why retention is not export.

We didn’t set out to build a new category of product. We set out to stop juggling. That’s the word Gyo, the senior engineer who built the first version of Kepler, keeps coming back to when he talks about where it started. “I have a lot of terminals opened, and with all those tabs, it was very difficult for me to keep focused on what I was doing,” he says. “I’m not a juggler.”

Amazon WorkSpaces is a powerful option for delivering cloud desktops at enterprise scale, but the platform only performs well when it is monitored with the same level of care as any mission-critical application. This guide explains how Amazon WorkSpaces work, why monitoring matters, what to measure, and how to choose the right monitoring software for a modern enterprise environment.

In April, Harness announced the Harness Cursor Plugin, a native integration that lets developers manage CI/CD pipelines, deployments, and security posture using natural language inside Cursor, governed by the same RBAC, OPA policies, and audit trails already enforced across the Harness platform. That experience has, until now, lived entirely at a desk.

As developers, we sometimes find ourselves in situations where something feels slower than it should be. The first thing we tell ourselves is “Maybe I need a different tool.” And sure, at times, it might be due to the tool, I’ll give you that. But most of the time, it comes down to how you’ve implemented certain features. That’s one of the downsides that comes with having too much freedom.

Confidential computing is moving quickly. The foundation is already here: AMD SEV-SNP and Intel TDX have made it possible to run confidential virtual machines (VMs) with stronger protection for data in use. Ubuntu 26.04 Long Term Support (LTS) brings integrated host and guest support for both of these technologies, making confidential computing a native part of the Ubuntu virtualization offering..

For the past two years, the conversation around AI in software engineering has focused on one thing: productivity. Engineers are shipping faster, writing more code, and completing work in hours that once took days. Every new model promises another leap forward. What gets far less attention is what all that speed demands from the people using it. Guillaume Moigneu, Field CTO at Upsun, has spent the past year watching engineering teams adapt to AI-assisted development.

Business continuity planning has a quiet assumption built into most of it: that the infrastructure the plan runs on will cooperate. Backup systems will be accessible. Recovery procedures will work as documented. The provider whose services underpin the critical path will be available, or at least recoverable within the window the plan specifies. That assumption is tested every time a major provider has an outage, a regional failure, or a service disruption that cascades across dependent workloads.

Ask ten engineering leaders how far their organization has actually gotten with autonomous AI, and most will admit the same thing once the marketing language drops away: not nearly as far as it looks from the outside. That was the undercurrent of a roundtable Logz.io and Twingate hosted on July 22, 2026, bringing together VPs of engineering, CTOs, senior security directors, and several product leaders across different industries and company stages.