Abstract: Systems, computer program products, and methods are described herein for machine learning (ML) based system for network resilience and steering. An example system monitors data movement across one or more network ports; extracts network performance indicators associated with the data movement; determines, via a machine learning (ML) subsystem, that a status of a first network port is indicative of operational failure based on at least the network performance indicators; determines that the first network port is associated with a first network port cluster; determines a redundant network port and an intermediate network switch associated with the first network port cluster; and triggers the intermediate network switch to reroute a portion of network traffic from the first network port to the redundant network port in response to the status of the first network port.

Abstract: Systems, computer program products, and methods are described herein for machine learning (ML) based network resilience and steering. An example system monitors data traffic across one or more network ports and determines a first data traffic pattern from the data traffic. The system further determines, via a ML subsystem, that the first data traffic pattern is indicative of a security threat to a first network port. In response to determining that the first data traffic pattern is indicative of the security threat to the first network port, the system further isolates the first network port from the one or more network ports.