Implement natural language processing solutions →mediumMultiple Choice

AI-102 Practice Question: Implement natural language processing solutions

Exhibit

Refer to the exhibit. You have the following KQL query for monitoring Azure AI Language service usage:

AzureDiagnostics
| where ResourceProvider == "MICROSOFT.COGNITIVESERVICES"
| where OperationName == "AnalyzeText"
| where TimeGenerated > ago(7d)
| summarize TotalCalls = count() by bin(TimeGenerated, 1d), StatusCode
| render timechart

You notice a spike in errors (HTTP 429) on a specific day. What is the most likely cause?

⚠ Common exam trap

In Azure AI services, HTTP 429 indicates rate limiting rather than service unavailability. Candidates often confuse 429 with 503 (service unavailable) or authentication errors (401/403).

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 number of calls exceeded the rate limit for the service tier.

HTTP 429 (Too Many Requests) is a rate-limiting response that occurs when the number of API calls exceeds the allowed threshold for the service tier. In Azure AI services, each pricing tier has a specific requests-per-second (RPS) or requests-per-minute (RPM) limit, and exceeding this limit triggers a 429 error to protect backend resources.

Answer analysis

Option-by-option breakdown

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

✗
Network connectivity issues.
Why it's wrong here
Network connectivity failures surface as timeouts or connection errors, not HTTP 429, which the service returns deliberately after throttling. It is tempting because intermittent connectivity is a frequent cause of API errors, and diagnosing it is correct when requests fail before reaching the endpoint.
✓
The number of calls exceeded the rate limit for the service tier.
Why this is correct
HTTP 429 signals throttling: the subscription or resource tier's requests-per-second or token quota was exceeded, so Azure rejects calls until the window resets. A spike in call volume against a fixed tier limit is the classic trigger, distinguishing it from authentication (401) or server faults (500).
✗
Authentication tokens expired.
Why it's wrong here
Expired authentication tokens produce HTTP 401, not 429, so token expiry cannot explain the spike. It is tempting because credential problems are a common cause of API failures, and refreshing tokens is the correct fix when the service returns 401 responses instead.
✗
Invalid API keys were used.
Why it's wrong here
Invalid API keys yield HTTP 401 or 403, not 429, so key misuse cannot cause this spike. It is tempting because key rotation and misconfiguration are common operational faults, and correcting them is the right action when the service rejects requests as unauthorised.

Go deeper

AI-102 Practice Question: Implement natural language processing solutions

Exhibit

Why each option matters

Option-by-option breakdown

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