Operations | Monitoring | ITSM | DevOps | Cloud

Traces are a goldmine of information that can help you, or your AI, find slow pages and fix them. Next.js comes out of the box with support for tracing. Incoming requests, fetch() calls, middleware, and server-side rendering are all wired up and ready to send traces to any OpenTelemetry-compatible backend. The catch is, unless you configure an exporter, you’ll never see those traces.

For many EUC and digital workplace leaders, the challenge isn't a lack of technology. It's understanding why workplace issues continue to surface despite years of investment in automation, AI, and digital transformation. Support teams are still dealing with high ticket volumes. Rollouts intended to improve employee experience can create new sources of disruption, and IT often struggles to understand what employees are experiencing until problems escalate into complaints, incidents, or support requests.

It feels less like managing devices and more like remote babysitting. You check the dashboard, everything is green, and then a customer in the field tells you a device has been down for two days. At a handful of servers, the rare failure is an event.

Cloud Monitoring Observability Analytics lets you create alerts from (and get alerted about) analytical SQL queries of logs and traces.

Your organization has approved AI platforms for development, data science, and productivity. Procurement signed off. Legal reviewed the terms. Employees are using them. The tools are sanctioned. What isn’t sanctioned is invisibility. The administrative layer of every AI platform in your environment — OpenAI, Amazon Bedrock, Google Gemini, Cursor, Databricks, Glean and others — generates security-relevant events that your SIEM has never seen.