System and method for intelligent data center power management and energy market disaster recovery

1. A computer automated system for intelligent power management, comprising a processing unit coupled to a memory element, and having instructions encoded thereon, which instructions cause the system to:

trigger a collection of infrastructure data, application data, power data, and machine element data;

based on the collected data, trigger an operational state change, wherein the triggered operational state change further comprises an infrastructure load balancing, an application load balancing and a power load balancing by the processing unit, across a plurality of data centers by real-time migration of an infrastructure load, an application load and a power load from one data center to another; and

wherein the system is configured to allow each data center to communicate with each other data center over a network and to connect to a plurality of energy providers over the network.

2. The computer automated system of claim 1 wherein the system is further caused to:

analyze the collected infrastructure data, application data, power data, and machine element data by an analytic engine comprised in the computer automated system; and

wherein the triggered operational state change further comprises a machine element load balancing by the processing unit.

3. The computer automated system of claim 1 wherein the system is further caused to:

via an energy market analysis layer, automatically in real-time, manage data center and application disaster recovery from utility energy market outages based on data collected from the plurality of energy providers over the network.

4. The computer automated system of claim 1 wherein the system is further caused to:

based on the collected data, measure a plurality of parameters wherein if the measured plurality of parameters fall outside of a predefined range, execute a predefined action to bring the said measured plurality of parameters within the predefined range.

5. The computer automated system of claim 1 , wherein the system is further configured to:

manage in real time, data center power distribution loads, application loads and virtual machine loads, across multiple data centers.

6. The computer automated system of claim 1 wherein the system is further caused to:

automatically initiate datacenter operation state changes to balance infrastructure loads, power loads and application loads across multiple datacenters.

7. The computer automated system of claim 1 wherein the computer system is further configured to:

analyze data collected from the plurality of energy providers over the network; and

based on the analyzed data, enable automatic datacenter operation state changes.

8. The computer automated system of claim 1 wherein the system is further caused to:

enable scenario modeling for and of designated applications, virtual machines, and power loads; and

predict outages caused by energy provider failures to pre-empt real-time back-up or migration of infrastructure loads, application loads, virtual machine loads or power loads in a data center.

9. The computer automated system of claim 1 wherein the instructions further cause the system to:

automatically manage virtual machine instances, which comprises killing of virtual servers or banks of physical computer systems during low application loads and turning up virtual machines or banks of physical computer systems prior to expected peak loads.

10. In a computer automated system for intelligent power management and comprising a processing unit coupled to a memory element having instructions encoded thereon, a method comprising:

triggering a collection of infrastructure data, application data, power data, and machine element data;

based on the collected data, triggering an operational state change, wherein the triggered operational state change further comprises an infrastructure load balancing, an application load balancing and a power load balancing by the processing unit, across a plurality of data centers by real-time migration of an infrastructure load, an application load and a power load from one data center to another; and

wherein the system is configured to allow each data center to communicate with each other data center over a network and to connect to a plurality of energy providers over the network.

11. The method of claim 10 further comprising:

analyzing the collected infrastructure data, application data, power data, and machine element data by an analytic engine comprised in the computer automated system; and

wherein the triggered operational state change further comprises a machine element load balancing by the processing unit.

12. The method of claim 10 further comprising:

via an energy market analysis layer, automatically in real-time, managing data center and application disaster recovery from utility energy market outages based on data collected from the plurality of energy providers over the network.

13. The method of claim 10 further comprising:

based on the collected data, measuring a plurality of parameters wherein if the measured plurality of parameters fall outside of a predefined range, executing a predefined action to bring the said measured plurality of parameters within the predefined range.

14. The method of claim 10 , further comprising:

managing in real time, data center power distribution loads, application loads and virtual machine loads, across multiple data centers.

15. The method of claim 10 further comprising:

automatically initiating datacenter operation state changes to balance infrastructure loads, power loads and application loads across multiple datacenters.

16. The method of claim 10 further comprising:

analyzing data collected from the plurality of energy providers over the network; and

based on the analyzed data, enabling automatic datacenter operation state changes.

17. The method of claim 10 further comprising: enabling scenario modeling for and of designated applications, virtual machines, and power loads; and predicting outages caused by energy provider failures to pre-empt real-time back-up or migration of infrastructure loads, application loads, virtual machine loads or power loads in a data center.

18. The method of claim 10 further comprising:

automatically managing virtual machine instances, which comprises killing of virtual servers or banks of physical computer systems during low application loads and turning up virtual machines or banks of physical computer systems prior to expected peak loads.