Operations | Monitoring | ITSM | DevOps | Cloud

OpenTelemetry graduated from the CNCF in May 2026 as, in the foundation’s own words, the de facto observability standard. The JavaScript API package alone did 1.36 billion downloads in twelve months. That kind of win has a side effect nobody plans for. Once a wire format is everywhere, has a receiver for every source, a transform language, and an agent your platform team already operates, people start putting things on it that have nothing to do with knowing whether a service is healthy.

Over the summer, Fly.io founder Kurt Mackey announced a complete pivot for the company toward "Computers for Agents", which are ephemeral virtual machines (called Sprites) optimized for AI coding workflows. He was refreshingly explicit about what this means: they are not trying to do both traditional application hosting and AI agent compute. They are choosing one over the other. This is a completely rational bet on the future of developer tooling.

Data center capacity planning concerns are growing. The Uptime Institute Global Data Center Survey 2026 reveals that the share of data center managers and operators who are at least somewhat concerned about forecasting future capacity requirements has risen from 68% in 2024 to 76% in 2026. Data center professionals are caught between accelerating business demands, aggressive artificial intelligence rollouts, higher-density GPU clusters, and intense scrutiny over power and cooling.

What does a typical day look like for the people working behind the scenes of a data centre? From hardware installations and cabling to troubleshooting, customer requests and supporting critical works, every shift brings something different. In this 'day in the life', Leon Strong, Data Centre Services Engineer for Maidenhead, shares what it’s like to work in a hands-on technical role, what they enjoy most and their advice for anyone considering a career in data centre engineering.

Low disk space remediation is the process of diagnosing storage consumption, safely recovering capacity, and confirming that the affected system and its dependent services are healthy. Automated remediation begins when a monitoring or AIOps platform detects a threshold breach and triggers a governed workflow.

AI agents can help investigate failed builds, fix flaky tests and automate other development tasks. But setting up those agents has required more Pipelines configuration than it should. Agent-powered steps often need different compute, permissions and runtime settings from ordinary build and test steps. Until now, teams have either repeated those settings across every agent-powered step or tried to make one set of global defaults work for everything.

Somewhere in every compliance program is a person who spends the week before an audit pulling logs out of several different systems, reconstructing who had access to what, and hoping the screenshots match what the auditor actually asks for. None of this work makes the system more secure. It just makes the existing security visible to someone who's checking. That gap, between the controls that are actually in place and the evidence that proves it, is where most audit prep time goes.

How much of your database delivery can you actually see? For most teams, the picture is scattered. Deployment status lives in CI logs and scripts. Drift appears outside the process. And with AI multiplying the volume and speed of changes moving through pipelines, the risk that comes with low visibility rises with every release.