Deploying workloads in a cloud computing system based on energy efficiency

A computing system having a memory having computer readable instructions and one or more processors for executing the computer readable instructions, the computer readable instructions controlling the one or more processors to perform operations comprising:

• obtaining an energy efficiency metric for each of a plurality of compute nodes in a cloud computing environment;
• classifying each of the plurality of compute nodes into one of a plurality of energy efficiency groups based on the energy efficiency metric of each of the plurality of compute nodes;
• creating a partition of nodes from the plurality of compute nodes, wherein the partition includes one compute node selected from each of the plurality of energy efficiency groups;
• deploying a replica of a workload to each of the plurality of compute nodes in the partition;
• monitoring an energy consumption and a computing performance of each of the plurality of compute nodes in the partition during a probing period;
• identifying, based on the energy consumption and performance, a selected energy efficiency group from the plurality of energy efficiency groups;
• and
• deploying the workload to one or more of the plurality of compute nodes in the selected energy efficiency group.

A computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform operations comprising:

• obtaining an energy efficiency metric for each of a plurality of compute nodes in a cloud computing environment;
• classifying each of the plurality of compute nodes into one of a plurality of energy efficiency groups based on the energy efficiency metric of each of the plurality of compute nodes;
• creating a partition of nodes from the plurality of compute nodes, wherein the partition includes one compute node selected from each of the plurality of energy efficiency groups;
• deploying a replica of a workload to each of the plurality of compute nodes in the partition;
• monitoring an energy consumption and a computing performance of each of the plurality of compute nodes in the partition during a probing period;
• identifying, based on the energy consumption and performance, a selected energy efficiency group from the plurality of energy efficiency groups;
• and
• deploying the workload to one or more of the plurality of compute nodes in the selected energy efficiency group.

A method for deploying workloads in a cloud computing system based on energy efficiency, the method comprising:

• obtaining an energy efficiency metric and a resource availability for each of a plurality of compute nodes in the cloud computing environment;
• classifying each of the plurality of compute nodes into one of a plurality of energy efficiency groups based on the energy efficiency metric of each of the plurality of compute nodes;
• creating a partition of nodes from the plurality of compute nodes, wherein the partition includes one compute node selected from each of the plurality of energy efficiency groups;
• deploying a replica of a workload to each of the plurality of compute nodes in the partition;
• monitoring an energy consumption and a computing performance of each of the plurality of compute nodes in the partition during a probing period;
• identifying, based on the energy consumption and performance, a selected energy efficiency group from the plurality of energy efficiency groups;
• and
• deploying the workload to one or more of the plurality of compute nodes in the selected energy efficiency group, the one or more of the plurality of compute nodes in the selected energy efficiency group selected based on the resource availability of each of the plurality of compute nodes in the selected energy efficiency group.

A method for deploying a workload in a cloud computing system based on energy efficiency, the method comprising:

• obtaining resource requirements of the workload;
• identifying a plurality of compute nodes in the cloud computing system that have a resource availability sufficient for the resource requirements of the workload;
• obtaining an energy efficiency metric for each of the plurality of compute nodes;
• classifying each of the plurality of compute nodes into one of a plurality of energy efficiency groups based on the energy efficiency metric of each of the plurality of compute nodes;
• creating a partition of nodes from the plurality of compute nodes, wherein the partition includes one compute node selected from each of the plurality of energy efficiency groups;
• deploying a replica of the workload to each of the plurality of compute nodes in the partition;
• monitoring an energy consumption and a computing performance of each of the plurality of compute nodes in the partition during a probing period;
• identifying, based on the energy consumption and performance, a selected energy efficiency group from the plurality of energy efficiency groups;
• and
• deploying the workload to one or more of the plurality of compute nodes in the selected energy efficiency group.