Methods and systems for identifying and resolving root causes of performance problems in data center object

A computer system for identifying runtime problems with objects of a data center, the computer system comprising:

• one or more processors;
• one or more data-storage devices;
• and
• machine-readable instructions stored in the one or more data-storage devices that when executed using the one or more processors control the system to performance operations comprising:
• using machine learning to construct a model for identifying performance problems with the objects based on baseline distributions of events of the objects in a historical time period and event distributions of events of the objects in a time window located outside the historical time period;
• constructing a root causes and recommendations database for resolving performance problems based on remedial measures previously performed for resolving performance problems;
• using the model to monitor the objects for performance problems in a sliding runtime window;
• in response to detecting an object with a performance problem, using the root causes and recommendations database to identify a root cause of the performance problem and generate a recommendation for resolving the performance problem;
• and
• displaying an alert in a graphical user interface, the alert identifying the object, the root cause of the performance problem, and the recommendation for resolving the performance problem.

A non-transitory computer-readable medium having instructions encoded thereon for enabling one or more processors of a computer system to perform operations comprising:

• using machine learning to construct a model for identifying objects of a data center with performance problems based on baseline distributions of events of objects in a historical time period and event distributions of events of the objects in a time window located outside the historical time period;
• constructing a root causes and recommendations database for resolving performance problems based on remedial measures previously performed for resolving performance problems;
• using the model to monitor the objects for performance problems in a sliding runtime window;
• in response to detecting an object with a performance problem, using the root causes and recommendations database to identify a root cause of the performance problem and generate a recommendation for resolving the performance problem;
• and
• displaying an alert in a graphical user interface, the alert identifying the object, the root cause of the performance problem, and the recommendation for resolving the performance problem.