SCALABLE AND ADAPTIVE SELF-HEALING BASED ARCHITECTURE FOR AUTOMATED OBSERVABILITY OF MACHINE LEARNING MODELS

• Main Authors: RAY, Atish Shankar, LEUNG PAH HANG, Denis Ching Sem, DI PASQUALE, Ricardo Hector
• Format: Patent
• Language: English
• Published: 27.07.2023
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; PHYSICS

Systems and methods for facilitating an automated observability of a ML model are disclosed. A system may include a processor including a model creator and a monitoring engine. The model creator may generate a configuration artifact based on a pre-defined template and a pre-defined input. The configuration artifact may pertain to expected attributes of the ML model to be created. The model creator may generate the ML model based on the configuration artifact. The monitoring engine may monitor a model attribute associated with each ML model based on monitoring rules stored in a rules engine. This may facilitate to identify an event associated with alteration in the model attribute from a pre-defined value. Based on the identified event, the system may execute an automated response including at least one of an alert and a remedial action to mitigate the event.