Predictive reserved instance for hyperscaler management

A computing device comprising:

• a memory containing machine readable medium comprising machine executable code having stored thereon instructions for performing a method of using cloud computing;
• a processor coupled to the memory, the processor configured to execute the machine executable code to cause the processor to:
• retrieve a current price list of a plurality of cloud computing costs of a cloud computing provider and a usage report of cloud services;
• generate usage information based on the usage report as a graph of past usage, wherein
• the graph of past usage is configured to accept user input of a function based on expected future use;
• receive user input of the function;
• update the graph of past usage with the received user input of the function to make an updated graph;
• predict future usage based on the usage report and the updated graph;
• and
• determine a number of reservations based on the predicted future usage and the retrieved current price list, including minimizing a cost function that takes into account the number of reservations, a price of a non-reserved cloud service, and a variance in machine hour usage.

A non-transitory machine readable medium having stored thereon instructions for performing a method comprising machine executable code which when executed by at least one machine, causes the machine to:

• retrieve a current price list of a plurality of cloud computing costs of a first cloud computing provider and a usage report of cloud services;
• generate usage information based on the usage report as a graph of past usage, wherein
• the graph of past usage is configured to accept user input of a first function based on expected future use;
• receive user input of the first function;
• update the graph of past usage with the received user input of the first function to make an updated graph;
• predict future usage based on the usage report and the updated graph;
• and
• determine a number of reservations based on the predicted future usage and the retrieved current price list, including minimizing a cost function that takes into account the number of reservations, a price of a non-reserved cloud service, and a variance in machine hour usage.