Deploying and Managing Generative AI on OCI →mediumMultiple ChoiceObjective-mapped

1Z0-1127-25 Deploying and Managing Generative AI on OCI Practice Question

Exhibit

Refer to the exhibit.

```
$ oci generative-ai dedicated-ai-cluster get --dedicated-ai-cluster-id ocid1.dedicatedaicluster.oc1.iad.xxxxx
{
  "data": {
    "capacity": 10,
    "id": "ocid1.dedicatedaicluster.oc1.iad.xxxxx",
    "lifecycle-state": "ACTIVE",
    "time-created": "2024-01-15T10:00:00Z",
    "time-updated": "2024-01-15T10:00:00Z"
  }
}
```

An administrator runs the above CLI command to check the status of a dedicated AI cluster. The cluster is ACTIVE with capacity 10. However, a user reports that inference requests to this cluster are failing with a '429 Too Many Requests' error. What is the most likely cause?

⚠ Common exam trap

Test-takers frequently confuse capacity (number of nodes) with rate limits, assuming a cluster with available compute resources cannot produce a 429 error, when in fact the 429 is tied to a separate API-level throttling mechanism.

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

✓

The cluster is hitting the maximum inference requests per minute limit

The '429 Too Many Requests' error is an HTTP status code indicating rate limiting has been exceeded. In OCI Generative AI, dedicated AI clusters have a configurable 'maximum inference requests per minute' limit. Even if the cluster is ACTIVE and has capacity (e.g., 10 nodes), hitting this per-minute request cap will cause the API gateway to reject further requests with a 429 error. The administrator must increase the rate limit or implement client-side throttling to resolve this.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

✓
The cluster is hitting the maximum inference requests per minute limit
Why this is correct
429 indicates rate limit; the cluster has a requests-per-minute limit separate from node count.
✗
The cluster does not have enough nodes to handle the load
Why it's wrong here
Capacity 10 nodes may be sufficient; error is rate limiting.
✗
The user is not in the same compartment as the cluster
Why it's wrong here
Compartment mismatch would cause 404 or 401, not 429.
✗
The cluster is not in ACTIVE state
Why it's wrong here
The output shows ACTIVE.

Visual reference

Go deeper

1Z0-1127-25 Deploying and Managing Generative AI on OCI Practice Question

Exhibit

Why each option matters

Option-by-option breakdown

Related to this question