Hardware, firmware, and software anomaly handling based on machine learning

A system comprising:

• a memory having computer readable instructions;
• and
• one or more processors for executing the computer readable instructions, the computer readable instructions controlling the one or more processors to perform operations comprising:
• detecting an anomaly in a database of hardware, firmware, and software events;
• determining whether a previously addressed anomaly is a duplicate of the anomaly;
• addressing the anomaly according to a state of the previously addressed anomaly based on the previously addressed anomaly being a duplicate of the anomaly;
• and
• addressing the anomaly according to machine learning based on the previously addressed anomaly not being the duplicate of the anomaly.

A 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 operations comprising:

• detecting an anomaly in a database of hardware, firmware, and software events;
• determining whether a previously addressed anomaly is a duplicate of the anomaly;
• addressing the anomaly according to a state of the previously addressed anomaly based on the previously addressed anomaly being a duplicate of the anomaly;
• and
• addressing the anomaly according to machine learning based on the previously addressed anomaly not being the duplicate of the anomaly.