Load balancing scalable storage utilizing optimization modules

One or more computer-storage media storing computer-useable instructions that, when executed by a computing device, perform a method for load balancing a scalable storage, the method comprising:

• for each triggered optimization module, of a plurality of optimization modules, optimizing the scalable storage based on an optimization routine, the optimization routine comprising:
• providing a plurality of candidate operations, wherein the plurality of candidate operations are potential load balancing operations associated with partitions assigned to servers of the scalable storage;
• for a selected optimization module of the plurality of optimization modules that has a higher priority than the triggered optimization module, removing a candidate operation from the plurality of candidate operations that would diminish a modeled state of the scalable storage as quantified by an evaluation score of the selected optimization module;
• determining at least one operation of the plurality of candidate operations that would improve the modeled state of the scalable storage as quantified by an evaluation score of the triggered optimization module;
• adding the at least one operation to a set of proposed operations;
• and
• updating the modeled state of the scalable storage to model executing the at least one operation on the scalable storage;
• executing the set of proposed operations on the scalable storage.

A computer-implemented method for load balancing a scalable storage, the method comprising:

• determining, for a triggered optimization module of a plurality of optimization modules, that partitions of an account hosted by the scalable storage have an imbalance in assignments with respect to servers of the scalable storage, and in response to the determining, performing a selection comprising:
• selecting a plurality of candidate operations based on an amount of the assignments belonging to ones of the servers as compared to others of the servers, wherein the plurality of candidate operations are potential load balancing operations associated with the partitions assigned to the servers of the scalable storage;
• for a selected optimization module of the plurality of optimization modules that has a higher priority than the triggered optimization module, removing a candidate operation from the plurality of candidate operations that would diminish a modeled state of the scalable storage as quantified by an evaluation score of the selected optimization module;
• and
• determining at least one operation of the plurality of candidate operations that would improve the modeled state of the scalable storage with respect to the imbalance in the assignments as quantified by an evaluation score of the triggered optimization module;
• adding the at least one operation to a set of proposed operations;
• updating the modeled state of the scalable storage to model executing the at least one operation on the scalable storage;
• executing the set of proposed operations on the scalable storage.