Operations | Monitoring | ITSM | DevOps | Cloud

Every second of a flight test produces a torrent of telemetry from engines, sensors, and control systems. Aerospace teams have captured this data for decades to verify performance and maintain safety, yet analysis often happens long after the mission ends. Engineers wait for downloads, conversions, and compliance checks before they can interpret results. That delay turns telemetry into a historical record instead of a feedback loop.

The first time an AI assistant suggests "restart the service" during a live incident and nobody on the bridge can tell whether that suggestion came from a current runbook, a stale wiki page, or thin air, you stop caring about model benchmarks. You start caring about what the agent actually knew, where that knowledge came from, and whether you can trust the chain of reasoning behind it.

Here is a reality that every network admin eventually runs into: users report slow apps, dropped calls, and broken connections, and the first instinct is to blame the ISP or the cloud provider. The ticket gets escalated, the ISP pushes back, and hours later, you find out the problem was sitting inside your own building the whole time. A saturated switch port. A misconfigured VLAN. A flaky patch cable in the server room.

A single hour of unplanned downtime can cost a mid-sized enterprise more than $300,000, according to ITIC report. Most of that cost comes from one place: teams find out about the problem after users do. That is the core limitation of reactive monitoring. It tells you something has failed, but doesn't tell you something is about to fail. This guide is for IT operations leads, platform and SRE engineers, and IT directors deciding how to evolve their monitoring practice.

Takeaway: Having workloads on two clouds is not the same as being able to move workloads between them freely. Portability is about the friction of movement, not the number of providers in use. Most teams that call themselves multicloud are not portable. They have separate workloads siloed on separate providers, each with its own toolchain, deployment pipeline, and set of operational conventions. Moving anything between those environments means starting from scratch. That is not portability.

When people talk about trusting AI, they usually focus on the interface. It summarizes and uses confident language with a level of clarity that feels reliable. But that’s all window dressing. None of it builds trust. Trust doesn’t come from what the AI says. A verifiable record of what the AI did makes it trustworthy.

Note: This post originally published in October 2023 and was updated in May 2026 to include new methods and options for embedding Grafana dashboards. Grafana dashboards are powerful and flexible tools for observing applications and infrastructure, so it’s no surprise we get a lot of questions from the community about how to embed them into their web applications.

Jira is the system of record for engineering work at nearly every enterprise that runs agile delivery. It tracks epics, stories, bugs, sprints, releases, and the long tail of technical debt that keeps platform teams awake. What Jira was never designed to be is an alerting system.

Why Fixing Incidents Is Only Half the Work Fixing an incident is not the same as solving a problem. In enterprise IT operations, that distinction carries significant operational weight. Organizations that treat every disruption as a discrete, isolated event to be resolved and closed will continue to encounter the same disruptions, on the same infrastructure, from the same root causes. The cycle does not end because the underlying problem was never addressed.

Two weeks after a payments outage took a regional bank offline for ninety-three minutes, the post-incident report landed on the CIO’s desk. It ran forty pages. It named the failed service, the ticket numbers, the restoration steps, and the engineers who paged in. It did not answer the question the board had actually asked, which was why the on-call team had spent the first forty-one minutes chasing a downstream symptom rather than the upstream cause.