The correct answer is client facing error rate.

A user facing SLI should measure what customers actually see and experience. The client facing error rate reflects failed API requests and payment errors and it therefore maps directly to end user impact. That makes it easy to convert into an SLO and to use for incident prioritization and rollback decisions.

memory utilization percentage is an internal resource metric and it does not directly indicate whether customers are succeeding or failing when they use the API. High memory use may correlate with problems but it is not a user facing SLI.

Cloud Monitoring uptime check success rate is a synthetic probe and it can be useful as a health signal. It is not as precise a measure of real customer experience as actual client error rates because probes may not exercise the same code paths or workloads as real users.

database replication lag is an internal operational metric that can affect correctness and latency in some cases. It is not a direct measure of user observed errors and so it is not the best choice for a user facing SLI.

Full AWS Practitioner Certification Question