Generating predictions for host machine deployments

A method comprising:

• identifying host data for a plurality of host machines in a data center, the host data identifying the host machines comprising the data center, the host data further identifying end-of-life information associated with respective ones of the plurality of host machines;
• identifying resource utilization data associated with the plurality of host machines, the resource utilization data comprising time series data identifying resource utilization by a plurality of workloads deployed across the host machines;
• generating a plurality of clusters of workloads based upon the resource utilization data, the clusters generated by clustering workloads that are similar to each other based upon the utilization data;
• generating respective usage predictions for the workloads based upon the resource utilization data;
• generating a forecasted resource requirement for the clusters based upon the respective usage predictions, the forecasted resource requirement having a time horizon until a subsequent server upgrade;
• generating a collective resource requirement for a plurality of replacement host machines based upon the forecasted resource requirement and the respective usage predictions;
• identifying benchmark data for a plurality of candidate replacement host machines to replace one or more of the host machines, the benchmark data comprising computing capabilities and a cost of respective candidate host machines;
• and
• generating a recommendation for the plurality of replacement host machines based upon the benchmark data and the collective resource requirement.

A non-transitory computer-readable medium comprising machine readable instructions, wherein the instructions, when executed by at least one processor, cause at least one computing device to at least:

• identify host data for a plurality of host machines in a data center, the host data identifying the host machines comprising the data center, the host data further identifying end-of-life information associated with respective ones of the plurality of host machines;
• identify resource utilization data associated with the plurality of host machines, the resource utilization data comprising time series data identifying resource utilization by a plurality of workloads deployed across the host machines;
• generate a plurality of clusters of workloads based upon the resource utilization data, the clusters generated by clustering workloads that are similar to each other based upon the utilization data;
• generate respective usage predictions for the workloads based upon the resource utilization data;
• generate a forecasted resource requirement for the clusters based upon the respective usage predictions, the forecasted resource requirement having a time horizon until a subsequent server upgrade;
• generate a collective resource requirement for a plurality of replacement host machines based upon the forecasted resource requirement and the respective usage predictions;
• identify benchmark data for a plurality of candidate replacement host machines to replace one or more of the host machines, the benchmark data comprising computing capabilities and a cost of respective candidate host machines;
• and
• generate a recommendation for the plurality of replacement host machines based upon the benchmark data and the collective resource requirement.