1Z0-1127-25 Deploying and Managing Generative AI on OCI Practice Question
A company has deployed a model on a Dedicated AI Cluster and needs to monitor inference performance metrics such as request latency, throughput, and error rates. Which OCI service provides built-in monitoring dashboards for these metrics?
⚠ Common exam trap
Oracle often tests the distinction between monitoring (real-time metrics and dashboards) and logging (text-based event records), leading candidates to mistakenly choose OCI Logging for performance metrics when it is actually designed for troubleshooting and compliance, not live dashboarding.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
OCI Monitoring
OCI Monitoring is the correct service because it provides built-in dashboards and metrics for inference performance, including request latency, throughput, and error rates, specifically for Dedicated AI Cluster deployments. These metrics are automatically collected and visualized in the OCI Monitoring console, allowing real-time tracking of model inference health without additional configuration.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
OCI Logging
Why it's wrong here
Logging captures log entries, not metric time-series data.
- ✗
OCI Notifications
Why it's wrong here
Notifications send alarms, but do not provide dashboards.
- ✓
OCI Monitoring
Why this is correct
Monitoring provides dashboards for metrics like latency and throughput.
- ✗
OCI Events
Why it's wrong here
Events trigger actions, not monitoring dashboards.
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