Data Center Infrastructure Management (DCIM) system comprising predictive analytics

Abstract

A Data Center Infrastructure Management (DCIM) system comprising predictive analytics and methods for collecting data, analyzing data, optimizing infrastructure efficiency and automating management of data center infrastructure systems and components is disclosed. The DCIM system comprising predictive analytics may generally comprise a DCIM appliance or server, data collection hardware, database hardware, software for collecting data from a plurality of infrastructure systems, infrastructure components and wireless sensors, presentation client software, reporting software and an intelligent predictive analytics engine. The intelligent predictive analytics engine may be employed to identify infrastructure optimization actions enabling the DCIM system software or DCIM element controller to enact changes to the operational state of data center infrastructure systems or components to sustain optimal data center infrastructure efficiency. The DCIM system comprising predictive analytics may continuously collect and analyze infrastructure system, infrastructure components and environmental data.

I/We claim: 
     
         1 . A computer system for data center infrastructure management (DCIM) comprising:
 a processor unit; a memory element coupled to the processor unit; a connection to and means for communicating over a wired and wireless network: wherein the system is configured to:   determine an optimum placement of a single or plurality of servers, which further comprises, estimating a power, a cooling and a network data resource requirement for each rack in a plurality of racks;   based on the determined optimum placement, enforce a pre-defined process for operating the data center;   based on the pre-defined process, determine an operational requirement from collected operational data, which comprises collected environmental, power, cooling, and information technology (IT) data;   via a predictive analytics engine configured to communicate over the network, analyze and store the collected operational data;   based on the collected and analyzed operational data, automatically make zero or more adjustments to the, environmental condition, power condition, cooling condition and IT condition;   wherein the predictive analytics engine is further configured to analyze a single or plurality of virtual machines, an instance or instances over a cloud computing network, and to estimate based on the analyzed virtual machines and instances, a demand for the said virtual machines and cloud instances; and   wherein the analytics for demand comprises:   estimating a baseline of virtual machine or cloud demands based on collected real-time and historical demand data;   estimating a baseline of virtual machine or cloud status based on collected real-time and historical demand data;   predicting future status and demand based on predictive modeling which further comprises the collected real-time estimations; and   based on the predictive modeling and analytics, and via a planning engine configured to communicate over the network, dynamically implementing an action or actions.   
     
     
         2 . The computer system of  claim 1 , wherein the predictive analytics engine is further configured to analyze a future infrastructure system condition, a future environment condition, and a future component or components' condition. 
     
     
         3 . The computer system of  claim 1  wherein the collection of operational data further comprises collecting environmental data from a plurality of wireless sensors and collecting infrastructure system and component data from infrastructure and component elements, wherein said infrastructure system and component data comprise collecting air temperature data, air flow data, water temperature data and water flow data. 
     
     
         4 . The computer system of  claim 1  further comprises a data center infrastructure management (DCIM) element controller, wherein the DCIM element controller is caused to employ the analyzed data, and based on the analyzed data, configure the infrastructure system and components' operational states for optimal efficiency. 
     
     
         5 . The system of  claim 4  wherein the DCIM element controller is further caused to configure based on whether an analyzed ambient air temperature is within a defined range. 
     
     
         6 . The system of  claim 5  wherein based on the analyzed air temperature, the DCIM element controller is caused to make zero or more adjustments to at least one of a computer room air-conditioner (CRAC), a rear door heat exchanger (RDHX), a coolant distribution unit (CDU), and a single or plurality of automated, adjustable flow control valves, to bring the ambient air temperature to within the defined range. 
     
     
         7 . The system of  claim 4  wherein the DCIM element controller is further caused to configure based on whether an analyzed water temperature and water flow is within a defined range. 
     
     
         8 . The system of  claim 7  wherein based on the analyzed water temperature and water flow, the DCIM element controller is caused to make zero or more adjustments to at least one of a coolant distribution unit (CDU), a rear door heat exchanger (RDHX), a single or plurality of automated, adjustable flow control valves, and a single or plurality of variable frequency drive (VFD) pumps to bring the water flow and the water temperature to within a defined range. 
     
     
         9 . The system of  claim 4  wherein the DCIM element controller is further caused to configure based on whether an analyzed, measured air flow is within a defined range. 
     
     
         10 . The system of  claim 9  wherein based on the analyzed, measured air flow, the DCIM element controller is caused to make zero or more adjustments to a single or plurality of variable frequency drive (VFD) fans to bring the said air flow to within the defined range. 
     
     
         11 . The system of  claim 1  wherein the system is further caused to, via a presentation software module, display the collected and analyzed data to a single or plurality of users. 
     
     
         12 . The system of  claim 1  wherein the system further caused to allow access to the system over a secure network. 
     
     
         13 . In a system for data center infrastructure management (DCIM) comprising a processing unit coupled to a memory element, and having instructions encoded thereon, a method comprising:
 determining an optimum placement of a single or plurality of servers, which further comprises, estimating a power, cooling and network data resource requirement for each rack in a plurality of racks;   based on the determined optimum placement, enforcing a pre-defined process for operating the data center;   based on the pre-defined process for operating the data center, determining operational requirements from collected operational data, which comprises collected environmental data, power data, cooling data, and information technology (IT) data;   via a predictive analytics engine configured to communicate over the network, collecting, analyzing and storing data of the said operational requirements;   based on the collected and analyzed data, automatically making zero or more adjustments to the environmental condition, power condition, cooling condition and IT condition;   wherein the predictive analytics engine is further configured to analyze a single or plurality of virtual machines, an instance or instances over a cloud computing network, and to estimate based on the analyzed virtual machines and instances, a demand for the said virtual machines and cloud instances; and   wherein the analytics for demand comprises:   estimating a baseline of virtual machine or cloud demands based on collected real-time and historical demand data;   estimating a baseline of virtual machine or cloud status based on collected real-time and historical demand data;   predicting future status and demand based on predictive modeling which further comprises the collected real-time estimations; and   based on the predictive modeling and analytics, and via a planning engine configured to communicate over the network, dynamically implementing an action or actions.   
     
     
         14 . The method of  claim 13 , further comprising, based on collected and analyzed data, predictively analyzing a future infrastructure system condition, a future environment condition, and a future component or components' condition. 
     
     
         15 . The method of  claim 13  wherein the said collecting further comprises collecting environmental data from a plurality of wireless sensors and collecting infrastructure system and component data from infrastructure and component elements wherein said infrastructure system and component data comprise collecting air temperature data, air flow data, water temperature data and water flow data. 
     
     
         16 . The method of  claim 13  further comprising: employing the analyzed data via a data center infrastructure management (DCIM) element controller; and configuring the infrastructure system and components' operational states for optimal efficiency via the DCIM controller. 
     
     
         17 . The method of  claim 16  wherein the said configuring further comprises configuring based on analyzing if ambient air temperature is within a defined range. 
     
     
         18 . The method of  claim 17  wherein the said configuring further comprises making zero or more adjustments to at least one of a computer room air-conditioner (CRAC), a rear door heat exchanger (RDHX), a coolant distribution unit (CDU), and a single or plurality of automated, adjustable flow control valves, to bring the ambient air temperature to within the defined range. 
     
     
         19 . The method of  claim 16  wherein the said configuring further comprises configuring based on analyzing if the water temperature and water flow is within a defined range. 
     
     
         20 . The method of  claim 19  wherein the said configuring further comprises making zero or more adjustments to at least one of a coolant distribution unit (CDU), a rear door heat exchanger (RDHX), a single or plurality of automated, adjustable flow control valves, and a single or plurality of variable frequency drive (VFD) pumps to bring the water flow and the water temperature to within a defined range. 
     
     
         21 . The method of  claim 16  wherein the said configuring further comprises measuring ambient air flow data, and analyzing if the measured air flow is within a defined range. 
     
     
         22 . The method of  claim 21  wherein the said configuring further comprises making zero or more adjustments to a single or plurality of VFD fans to bring the said air flow within the defined range. 
     
     
         23 . The method of  claim 13  further comprising, via a presentation software module, displaying of the collected and analyzed data to a single or plurality of users. 
     
     
         24 . The method of  claim 13  further comprising allowing access to the system over a secure network. 
     
     
         25 . A system for data center infrastructure management (DCIM) comprising a processing unit coupled to a memory element, and having instructions encoded thereon, wherein the encoded instructions cause the system to:
 collect and store data center infrastructure system condition data, environmental condition data and component condition data;   analyze the collected infrastructure system, environmental and component condition data; and   based on the collected and analyzed data, automatically make zero or more adjustments to data center infrastructure system condition, environmental condition and component condition;   wherein the said zero or more adjustments are based on a predictive analytics functionality configured to continuously collect and analyze data, and wherein the predictive analytics functionality is further configured to implement predictive analytics of a single or plurality of virtual machines, an instance or instances over a cloud computing network, and to estimate demand for the said virtual machines and cloud instances; and   wherein the analytics for demand comprises:   estimating a baseline of virtual machine or cloud demands based on collected real-time and historical demand data;   estimating a baseline of virtual machine or cloud status based on collected real-time and historical demand data;   predicting future status and demand based on predictive modeling which further comprises the collected real-time estimations; and   based on the predictive modeling and analytics, dynamically implementing an action or actions.   
     
     
         26 . In a system for data center infrastructure management (DCIM) comprising a processing unit coupled to a memory element, and having instructions encoded thereon, a method comprising:
 collecting and storing data center infrastructure system condition data, environmental condition data and component condition data;   analyzing the collected infrastructure system, environmental and component condition data; and   based on the collected and analyzed data, automatically making zero or more adjustments to data center infrastructure system condition, environmental condition and component condition;   wherein the said zero or more adjustments are based on a predictive analytics functionality configured for continuously collecting and analyzing data, and wherein the predictive analytics functionality is further configured to implement predictive analytics of a single or plurality of virtual machines, an instance or instances over a cloud computing network, and to estimate demand for the said virtual machines and cloud instances; and   wherein the analytics for demand comprises:   estimating a baseline of virtual machine or cloud demands based on collected real-time and historical demand data;   estimating a baseline of virtual machine or cloud status based on collected real-time and historical demand data;   predicting future status and demand based on predictive modeling which further comprises the collected real-time estimations; and   based on the predictive modeling and analytics, dynamically implementing an action or actions.