Intelligent threshold leak remediaton of datacenter cooling systems

At least one processor for remediation of threshold leaks in a liquid cooling system, comprising:

• at least one logic unit to control a flow controller and a power controller within a power distribution unit (PDU), the flow controller and the power controller to receive inputs from a learning subsystem adapted to determine that at least one parameter associated with the liquid cooling system is outside a normal threshold of a determined range so that a threshold leak of a coolant has occurred, the threshold leak associated with at least one computing component functioning within a normal temperature threshold and receiving the coolant, the power controller to cause the at least one computing component to change power state to reduce reliance on the coolant and the flow controller to cause a change a flow of the coolant to the at least one computing component.

At least one processor for a liquid cooling system, comprising:

• at least one logic unit to train one or more neural network having hidden layers of neurons to evaluate parameter values associated with the at least one parameter of the liquid cooling system, the evaluation performed using the parameter valves and using prior associated flow rates for a coolant and prior associated power states for at least one computing component, the evaluation to determine a moving range for the at least one parameter that is outside a normal threshold and that is indicative of a threshold leak of the coolant has occurred, the threshold leak associated with the at least one computing component functioning within a normal temperature threshold and receiving the coolant, and the one or more neural network to provide outputs associated with a first change in a power state for the at least one computing component to reduce reliance on the coolant and associated with a second change to a flow of the coolant to the at least one computing component.

A remediation system for threshold leaks in a liquid cooling system, comprising:

• at least one processor to train one or more neural networks having hidden layers of neurons to evaluate parameter values associated with the at least one parameter of the liquid cooling system, the evaluation performed using the parameter valves and using prior associated flow rates for a coolant and prior associated power states for at least one computing component, the evaluation to determine a moving range for the at least one parameter that is outside a normal threshold and that is indicative of a threshold leak of the coolant has occurred, the threshold leak associated with the at least one computing component functioning within a normal temperature threshold and receiving the coolant, and the one or more neural networks to provide outputs associated with a first change in a power state for the at least one computing component to reduce reliance on the coolant and associated with a second change to a flow of the coolant to the at least one computing component.