Utilizing machine learning models with a centralized repository of log data to predict events and generate alerts and recommendations

A device, comprising:

• one or more memories;
• and
• one or more processors, communicatively coupled to the one or more memories, configured to:
• receive log data from application logs associated with applications, service logs associated with services, and server logs associated with server devices;
• store the log data in a centralized log repository for a predetermined retention time period;
• perform natural language processing on the log data, stored in the centralized log repository, to convert the log data into event data identifying events associated with categories;
• selectively:
• process the event data, with one or more first machine learning models, to identify patterns in the event data and to generate an alert based on the patterns;
• process the event data, with one or more second machine learning models, to generate a correlation matrix for the event data and to predict an event based on the correlation matrix;
• or
• process the event data, with one or more third machine learning models, to classify the event data based on the categories and to generate a recommendation based on classifying the event data;
• and
• perform one or more actions based on one or more of the alert, the event, or the recommendation.

A non-transitory computer-readable medium storing instructions, the instructions comprising:

• one or more instructions that, when executed by one or more processors, cause the one or more processors to:
• receive log data from application logs associated with applications, service logs associated with services, and server logs associated with server devices;
• store the log data in a centralized log repository;
• process the log data, with one or more first machine learning models, to identify patterns in the log data and to generate an alert based on the patterns;
• process the log data, with one or more second machine learning models, to generate a correlation matrix for the log data and to predict an event based on the correlation matrix;
• process the log data, with one or more third machine learning models, to classify the log data based on categories and to generate a recommendation based on classifying the log data;
• and
• perform one or more actions based on one or more of the alert, the event, or the recommendation.