Content based log retrieval by using embedding feature extraction

A non-transitory machine-readable medium having instructions stored therein, which when executed by a processor, cause the processor to perform operations for managing data processing systems, the operations comprising:

• obtaining logs for the data processing systems, each of the logs comprising log entries associated with an event;
• obtaining a trained machine learning model using the logs for the data processing systems, the trained machine learning model comprising a plurality of embedding vectors;
• selecting, after obtaining the trained machine learning model, one of the embedding vectors as an output for an embedding generator, wherein the embedding generator is obtained by pruning the trained machine learning model;
• obtaining, using the logs and the embedding generator, vector representations for the logs;
• storing the vector representations in a vector indexing based database;
• obtaining a data processing system support request for a data processing system of the data processing systems, the support request including a log pattern, wherein the method is executed by a data processing system manager that is distinct and separate from the data processing system from which the data processing system support request is obtained;
• indexing, using the log pattern, the database to identify a related log of the logs;
• identifying the event associated with the related log;
• and
• performing an action set, based on the event, to service the data processing system support request, wherein performing the action set based on the event comprises:
• disabling, by a data processing system manager, one or more hardware components of the data processing system from which the data processing system support request is obtained.

A data processing system manager, comprising:

• a processor;
• and
• a memory coupled to the processor to store instructions, which when executed by the processor, cause the processor to perform operations for managing data processing systems, the operations comprising:
• obtaining logs for the data processing systems, each of the logs comprising log entries associated with an event;
• obtaining a trained machine learning model using the logs for the data processing systems, the trained machine learning model comprising a plurality of embedding vectors;
• selecting, after obtaining the trained machine learning model, one of the embedding vectors as an output for an embedding generator, wherein the embedding generator is obtained by pruning the trained machine learning model;
• obtaining, using the logs and the embedding generator, vector representations for the logs;
• storing the vector representations in a vector indexing based database;
• obtaining a data processing system support request for a data processing system of the data processing systems, the support request including a log pattern, wherein the method is executed by a data processing system manager that is distinct and separate from the data processing system from which the data processing system support request is obtained;
• indexing, using the log pattern, the database to identify a related log of the logs;
• identifying the event associated with the related log;
• and
• performing an action set, based on the event, to service the data processing system support request, wherein performing the action set based on the event comprises:
• disabling, by a data processing system manager, one or more hardware components of the data processing system from which the data processing system support request is obtained.