Extracting corrective actions from information technology operations

A computer system for storing successful technical support actions from prior interactions with IT operations, the computer system comprising:

• one or more processors, one or more computer-readable memories, one or more computer-readable storage media, and program instructions stored on at least one of the one or more computer-readable storage media for execution by at least one of the one or more processors via at least one of the one or more computer-readable memories, wherein the computer system is capable of performing a method comprising:
• obtaining a prior ticket from a server, wherein the prior ticket comprises text;
• identifying a domain and a corrective action in the prior ticket by parsing the text of the prior ticket using a natural language processing algorithm, wherein the corrective action comprises specific words in the text of the prior ticket;
• generating a cluster of prior tickets using a machine learning clustering algorithm, wherein the cluster of prior tickets is associated with an identified domain;
• determining a sentiment in parsed text of the prior ticket using a deep machine learning model, wherein the sentiment associates the corrective action with a successful resolution of the prior ticket;
• and
• storing the specific words of the corrective action in a database of corrective actions, wherein the corrective action is associated with the cluster of tickets.

A computer program product for storing successful technical support actions from prior interactions with IT operations, the computer program product comprising:

• a computer-readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform a method comprising:
• obtaining a prior ticket from a server, wherein the prior ticket comprises text;
• identifying a domain and a corrective action in the prior ticket by parsing the text of the prior ticket using a natural language processing algorithm, wherein the corrective action comprises specific words in the text of the prior ticket;
• generating a cluster of prior tickets using a machine learning clustering algorithm, wherein the cluster of prior tickets is associated with an identified domain;
• determining a sentiment in parsed text of the prior ticket using a deep machine learning model, wherein the sentiment associates the corrective action with a successful resolution of the prior ticket;
• and
• storing the specific words of the corrective action in a database of corrective actions, wherein the corrective action is associated with the cluster of tickets.