Operating the Interlude: Why Data Center Operations Can't Scale Like Capacity
Digital infrastructure is in an awkward in-between moment. Capacity is on track to nearly double. The people and processes that keep it running are not.
The interlude, in four numbers
The US data center market is projected to grow from $208 billion today to $309 billion by 2030. Roughly 97 GW of new capacity will come online between 2025 and 2030, nearly doubling the sector. Running it will take an estimated 140,000 additional skilled workers. Meanwhile, colocation vacancy sits at a historic low of 1.4%.
AI is widening the gap. Training and inference workloads are sporadic and compute-intensive, driving sudden spikes in power draw and cooling load that stress electrical, thermal, and network systems at the same moment.
The most telling number may be this one: in Uptime Institute's 2025 global survey, 87% of outages were preventable, and human procedural error climbed ten points year over year. The failure mode is operational, not physical.
Three forces that multiply
Scale. Facility counts, alarm volume, and on-call headcount can't grow at the pace of gigawatt build-outs. Real-time monitoring is outrunning real-time response.
Complexity. DCIM, BMS, SCADA, UPS, CRAC, and network platforms each speak a different incident language, and multi-tenant environments compound that by an order of magnitude.
Resilience. SLA credits, post-mortem discipline, and customer scrutiny are peaking. Tenants want reliability they can measure and audit.
These forces don't add up; they compound. Volatile AI surges hit power, cooling, and generators simultaneously, overwhelming monitoring built for predictable IT loads. Construction cycles have compressed from 36 months to 12, but alarm procedures and call-out trees rarely keep pace. And incidents spanning carriers, colocation providers, cloud tenants, and network operators often have no shared call-out framework or incident bridge.
The case for an orchestration layer
The answer isn't another monitoring tool. It's a layer that sits between your existing tools and your people, listening to DCIM, BMS, SCADA, and MSM at once, correlating signals into single actionable events, and routing each to the right person at the right time.
AlertOps delivers that in three layers on one platform:
Alarm and alert management: pre-built integrations with Schneider, Vertiv, Eaton, Siemens, Honeywell, Datadog, Prometheus, and more; AI correlation across power, cooling, and network domains; up to 80% alarm noise reduction; and heartbeat monitoring that flags when a monitoring system goes silent.
Incident and event management: follow-the-sun on-call scheduling, live call routing, multi-tiered call-out trees with SLA-based auto-escalation before breach, and notifications via phone, SMS, Slack, Teams, email, or mobile app.
Incident orchestration: AI agents for triage and root-cause detection, automatic ITSM tickets, chat channels and status page updates, and AI-generated post-mortems with a full audit trail. Historical alarm insights keep lessons learned in the platform, not in individual engineers' heads.
From noise to signal, in practice
One multinational REIT runs AlertOps across more than 260 facilities in 70+ metros. At the hardware monitoring tier alone, the platform ingested 8,820,954 raw events and turned them into 963,063 actionable alerts. Deduplication, flap suppression, return-to-normal handling, and correlation removed 89% of the noise before it ever reached a responder.
The right alert, to the right team, at the right time, at scale.
