Managing computing workloads within a computing environment

1. A computer-implemented method of managing computing workloads within a computing environment, the method comprising:

identifying computing parameters of a plurality of datacenter elements of each computing cluster of a computing environment, the data center elements including one or more of computing nodes, storage devices, network devices, and power devices;

for each computing cluster of the computing environment:

determining a health of the power device of the computing cluster based on telemetry data of the power device;

for each computing node of the computing cluster:

determining a computational processing load of the computing node;

determining a computing cost associated with a geo-location of the computing node;

calculating, for each computing cluster of the computing environment, an availability of computing resources of the computing cluster based on the computing parameters of the data center elements of the computing cluster, the health of the power device of the computing cluster, the computational processing load of each computing node of the computing cluster, and the computing cost of each computing node of the computing cluster;

generating a ranking of each computing cluster based on the availability of the computing resources of the computing cluster;

detecting a disruption of execution of a computing workload at a first computing cluster of the computing environment;

in response to detecting the disruption of execution of the computing workload at the first computing cluster:

identifying a second computing cluster of the computing environment based on the ranking; and

migrating the computing workload from the first computing cluster to the second computing cluster.

2. The computer-implemented method of claim 1 , wherein detecting the disruption of execution of the computing workload includes identifying an emergency power reduction at the first computing cluster.

3. The computer-implemented method of claim 1 , wherein identifying the computing parameters of the plurality of datacenter elements of each computing cluster further includes identifying a generation and a model of each datacenter element, and identifying a classification of each component of each datacenter element.

4. The computer-implemented method of claim 1 , wherein the ranking is a static ranking.

5. The computer-implemented method of claim 1 , wherein the ranking is a dynamic ranking.

6. The computer-implemented method of claim 1 , wherein determining the computational processing load of the computing node further comprises:

monitoring telemetry data of the computing node, the telemetry data including power utilized by the computing node, power utilized by each component of the computing node, compute utilization per second (CUPS) of the computing node, and health of each component of the computing node; and

determining the computing processing load of the computing node based on the monitored telemetry data.

7. An information handling system comprising a processor having access to memory media storing instructions executable by the processor to perform operations, comprising:

identifying computing parameters of a plurality of datacenter elements of each computing cluster of a computing environment, the data center elements including one or more of computing nodes, storage devices, network devices, and power devices;

for each computing cluster of the computing environment:

determining a health of the power device of the computing cluster based on telemetry data of the power device;

for each computing node of the computing cluster:

determining a computational processing load of the computing node;

determining a computing cost associated with a geo-location of the computing node;

calculating, for each computing cluster of the computing environment, an availability of computing resources of the computing cluster based on the computing parameters of the data center elements of the computing cluster, the health of the power device of the computing cluster, the computational processing load of each computing node of the computing cluster, and the computing cost of each computing node of the computing cluster;

generating a ranking of each computing cluster based on the availability of the computing resources of the computing cluster;

detecting a disruption of execution of a computing workload at a first computing cluster of the computing environment;

in response to detecting the disruption of execution of the computing workload at the first computing cluster:

identifying a second computing cluster of the computing environment based on the ranking; and

migrating the computing workload from the first computing cluster to the second computing cluster.

8. The information handling system of claim 7 , wherein detecting the disruption of execution of the computing workload includes identifying an emergency power reduction at the first computing cluster.

9. The information handling system of claim 7 , wherein identifying the computing parameters of the plurality of datacenter elements of each computing cluster further includes identifying a generation and a model of each datacenter element, and identifying a classification of each component of each datacenter element.

10. The information handling system of claim 7 , wherein the ranking is a static ranking.

11. The information handling system of claim 7 , wherein the ranking is a dynamic ranking.

12. The information handling system of claim 7 , wherein determining the computational processing load of the computing node further comprises:

monitoring telemetry data of the computing node, the telemetry data including power utilized by the computing node, power utilized by each component of the computing node, compute utilization per second (CUPS) of the computing node, and health of each component of the computing node; and

determining the computing processing load of the computing node based on the monitored telemetry data.

13. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising:

identifying computing parameters of a plurality of datacenter elements of each computing cluster of a computing environment, the data center elements including one or more of computing nodes, storage devices, network devices, and power devices;

for each computing cluster of the computing environment:

determining a health of the power device of the computing cluster based on telemetry data of the power device;

for each computing node of the computing cluster:

determining a computational processing load of the computing node;

determining a computing cost associated with a geo-location of the computing node;

calculating, for each computing cluster of the computing environment, an availability of computing resources of the computing cluster based on the computing parameters of the data center elements of the computing cluster, the health of the power device of the computing cluster, the computational processing load of each computing node of the computing cluster, and the computing cost of each computing node of the computing cluster;

generating a ranking of each computing cluster based on the availability of the computing resources of the computing cluster;

detecting a disruption of execution of a computing workload at a first computing cluster of the computing environment;

in response to detecting the disruption of execution of the computing workload at the first computing cluster:

identifying a second computing cluster of the computing environment based on the ranking; and

migrating the computing workload from the first computing cluster to the second computing cluster.

14. The non-transitory computer-readable medium of claim 13 , wherein detecting the disruption of execution of the computing workload includes identifying an emergency power reduction at the first computing cluster.

15. The non-transitory computer-readable medium of claim 13 , wherein identifying the computing parameters of the plurality of datacenter elements of each computing cluster further includes identifying a generation and a model of each datacenter element, and identifying a classification of each component of each datacenter element.

16. The non-transitory computer-readable medium of claim 13 , wherein the ranking is a static ranking.

17. The non-transitory computer-readable medium of claim 13 , wherein the ranking is a dynamic ranking.