Using machine learning to dynamically determine a protocol for collecting system state information from enterprise devices

A method comprising:

• receiving data collected from a plurality of managed devices in a plurality of data collections, wherein the plurality of data collections are performed using a plurality of collection protocols;
• determining, for given ones of the plurality of data collections, a trigger of a plurality of triggers that generated each of the given ones of the plurality of data collections;
• identifying a collection protocol of the plurality of collection protocols used for each of the given ones of the plurality of data collections;
• determining one or more attributes of a plurality of attributes that have been collected using given ones of the plurality of collection protocols, wherein the plurality of attributes are of the plurality of managed devices;
• generating a mapping between the plurality of triggers, the plurality of collection protocols and the plurality of attributes using one or more machine learning algorithms;
• predicting, using the generated mapping, one or more collection protocols of the plurality of collection protocols to use to collect data from one or more of the plurality of managed devices;
• wherein the mapping comprises a decision tree;
• and
• determining a plurality of weights of given nodes of the decision tree, wherein the weights of the given nodes of the decision tree are based on at least one of a type of one or more of the plurality of triggers and a number of the plurality of attributes collected by given ones of the plurality of collection protocols;
• wherein the method is performed by at least one processing platform comprising at least one processing device comprising a processor coupled to a memory.

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 platform causes said at least one processing platform:

• to receive data collected from a plurality of managed devices in a plurality of data collections, wherein the plurality of data collections are performed using a plurality of collection protocols;
• to determine, for given ones of the plurality of data collections, a trigger of a plurality of triggers that generated each of the given ones of the plurality of data collections;
• to identify a collection protocol of the plurality of collection protocols used for each of the given ones of the plurality of data collections;
• to determine one or more attributes of a plurality of attributes that have been collected using given ones of the plurality of collection protocols, wherein the plurality of attributes are of the plurality of managed devices;
• to generate a mapping between the plurality of triggers, the plurality of collection protocols and the plurality of attributes using one or more machine learning algorithms;
• to predict, using the generated mapping, one or more collection protocols of the plurality of collection protocols to use to collect data from one or more of the plurality of managed devices;
• wherein the mapping comprises a decision tree;
• and
• to determine a plurality of weights of given nodes of the decision tree, wherein the weights of the given nodes of the decision tree are based on at least one of a type of one or more of the plurality of triggers and a number of the plurality of attributes collected by given ones of the plurality of collection protocols.