Which of the following is a benefit of Cisco AI in observability?

Minimizing service disruption and downtime is a significant benefit of Cisco AI in observability. By leveraging advanced analytics and machine learning, Cisco AI can proactively identify and predict potential issues within the network or system infrastructure. This predictive capability allows organizations to address problems before they escalate into serious disruptions, ensuring higher availability of services. Furthermore, through the automation of monitoring and alerting processes, the system can quickly respond to anomalies, reducing the mean time to resolution (MTTR). This enhanced visibility and responsiveness ultimately lead to an improved user experience and greater operational efficiency.

The other choices do not align with the objectives of Cisco AI in observability. Increasing manual task efforts would negate the benefits that automation brings and is counterproductive in a modern observability framework. Limiting customer feedback would not support the goal of improving services based on user needs and experiences, and promoting local environments only could restrict scalability and flexibility, which are essential in today’s distributed IT architectures.