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Monitoring and management for liquid-cooled environments

8 dakika Okundu

Intelligent monitoring for chip-level protection.

Liquid-cooled AI facilities run across multiple infrastructure layers, each generating data that most operations teams monitor separately. Without a unified view, detecting a fault early, understanding its impact, and coordinating a response all take longer than they should.

What is secondary fluid network management?

Secondary fluid network management refers to managing the coolant distribution infrastructure that transports cooling fluid between liquid-cooling systems and IT equipment to maintain reliable data center operation.

Centralizing monitoring and management across liquid-cooled infrastructure supports operational visibility and coordinated control, collecting telemetry from rack, row, and site layers simultaneously. Response actions coordinate automatically, and data publishes to existing management systems — reducing manual steps while preserving operator visibility.

Scale without complexity.
Expand liquid cooling deployments with a modular rack-to-row-to-site architecture without additional headcount or engineering complexity as you grow.

Speed of deployment.
Auto-discover Vertiv™ thermal units for automated metrics and data, intended to reduce deployment and commissioning time from the first rack through a full-site rollout.

Optimize operation.
Access telemetry data across your full liquid cooling stack to drive automation and support uptime and energy efficiency across liquid-cooled environments.

Improve intelligence.
Monitor multiple deployments across campuses on a single interface. Precise temperature visibility and consolidated Building Management System (BMS) integration help teams maintain IT Service Level Agreements (SLAs) without managing separate monitoring tools.

Operating liquid-cooled infrastructure in real time

Centralized management and monitoring keep liquid cooling infrastructure protected and performing through continuous monitoring, automated response, and real-time optimization.

  • Leak detection and response. Integrated detection and response platform that coordinates mitigation actions such as valve isolation, coolant distribution unit (CDU) shutdown, and controlled rack power sequencing.
  • Enable AI-driven cooling optimization. Centralized telemetry from environmental systems, CDUs, and servers helps establish the data foundation for AI-driven cooling optimization, supporting cooling efficiency and system stability as capabilities evolve.
  • Data aggregation and system visibility. Unified visibility for infrastructure data across racks, rows, and site layers, with direct integration into Vertiv on-premises and cloud management platforms via standard application programming interfaces (APIs).

From deployment to day-to-day operations

Vertiv supports liquid cooling infrastructure at every stage — site assessment, design, commissioning, and ongoing maintenance. Pair centralized monitoring and management with Vertiv Liquid Cooling Services for end-to-end coverage of your liquid-cooled environment.

Explore Vertiv™ Liquid Cooling Services >

Features overview

Rack layer

Direct interface to cooling hardware, sensors, and IT equipment.

  • Collect and normalize telemetry from sensors, CDUs, servers, and power devices
  • Detect leaks and trigger local control actions
  • Monitor device health and communication status
  • Buffer telemetry locally during network interruptions

Benefits:

Fast leak response, vendor-agnostic integration, and modular rack expansion

Row layer

Aggregate rack data and coordinate row-level CDU optimization.

  • Collect and normalize telemetry from rack managers and row-level devices
  • Coordinate leak response across multiple racks
  • Optimize CDU setpoints for cooling efficiency

Benefits:

Reduced data complexity, scalable expansion, and improved system stability

Site layer

Provide site-wide visibility, integration, and analytics.

  • Collect telemetry from row managers and monitor site-wide health
  • Publish telemetry to external systems (BMS,DCIM, Vertiv Unify) via APIs
  • Enable fleet-level analytics and optimization services

Benefits:

Reduced data complexity, scalable expansion, and improved system stability

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