Software update compatibility assessment

A computer program product comprising a non-transitory processor-readable storage medium having stored therein program code of one or more software programs, wherein the program code when executed by at least one processing device causes the at least one processing device to perform steps of:

• identifying at least one software update available for a given computing device;
• determining a state of the given computing device;
• utilizing a machine learning-based predictive model to assess compatibility of the at least one software update with the given computing device based at least in part on the state of the given computing device, the machine learning-based predictive model being trained utilizing historical incident data for a plurality of incidents associated with application of software updates to a plurality of computing devices;
• generating a recommendation notification indicating compatibility of the at least one software update with the given computing device, wherein generating the recommendation notification comprises selecting a type of visual indicator based at least in part on the assessed compatibility indicating that the at least one software update has at least a designated threshold probability of affecting operation of the given computing device;
• and providing the recommendation notification in conjunction with presentation of one or more user interface features controlling whether to apply the at least one software update to the given computing device, wherein providing the recommendation notification in conjunction with presentation of the one or more user interface features controlling whether to apply the at least one software update to the given computing device comprises displaying the visual indicator;
• wherein the designated threshold probability is dynamically adjusted based at least in part on one or more characteristics of the at least one software update.

A method comprising steps of:

• identifying at least one software update available for a given computing device;
• determining a state of the given computing device;
• utilizing a machine learning-based predictive model to assess compatibility of the at least one software update with the given computing device based at least in part on the state of the given computing device, the machine learning-based predictive model being trained utilizing historical incident data for a plurality of incidents associated with application of software updates to a plurality of computing devices;
• generating a recommendation notification indicating compatibility of the at least one software update with the given computing device, wherein generating the recommendation notification comprises selecting a type of visual indicator based at least in part on the assessed compatibility indicating that the at least one software update has at least a designated threshold probability of affecting operation of the given computing device;
• and providing the recommendation notification in conjunction with presentation of one or more user interface features controlling whether to apply the at least one software update to the given computing device, wherein providing the recommendation notification in conjunction with presentation of the one or more user interface features controlling whether to apply the at least one software update to the given computing device comprises displaying the visual indicator;
• wherein the designated threshold probability is dynamically adjusted based at least in part on one or more characteristics of the at least one software update;
• and wherein the method is performed by at least one processing device comprising a processor coupled to a memory.