Automated optimization of parameterizable models in distributed computing environments

A method comprising:

• recording or collecting data during an optimization task of a parameterizable model according to a user instruction that defines a sequence of actions to be performed during the optimization task of the parameterizable model implemented across a plurality of compute nodes of a distributed computing environment;
• based at least on recording or collecting at least a portion of the data for one or more actions of the sequence of actions, updating a parameter during the optimization task;
• in response to the updating the parameter during the optimization task, transmitting the updated parameter to a first compute node of the plurality of compute nodes;
• in response to the transmitting the updated parameter to the first compute node of the plurality of compute nodes, receiving a set of values from the first compute node, the set of values corresponding to one or more aggregated parameter values from at least one compute node of the plurality of compute nodes;
• and
• changing the updated parameter based on the receiving the set of values from the first compute node.