AI-200 Containerized AI Workloads Practice Question
You are deploying a custom text-embedding model container to Azure Container Apps. You need to configure scaling rules so that the container scales out based on incoming HTTP traffic and Azure Service Bus queue length. Which TWO scalers can you configure? Each correct answer presents part of the solution.
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
✓
azure-servicebus scaler
Azure Container Apps uses KEDA under the hood and natively supports scaling based on HTTP traffic (http scaler) and Azure Service Bus queues (azure-servicebus scaler).
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
cpu memory-limit scaler
Why it's wrong here
CPU and memory scaling are standard rules, but the requirements specifically call out HTTP traffic and queue length.
- ✓
azure-servicebus scaler
Why this is correct
The azure-servicebus scaler monitors queue or topic message counts to scale container app replicas.
- ✗
azure-blob-storage scaler
Why it's wrong here
While Blob Storage triggers exist in KEDA, Service Bus and HTTP are the specified requirements for this workload.
- ✗
container-registry scaler
Why it's wrong here
Container registry scalers do not exist for runtime autoscaling based on queue length or HTTP requests.
- ✓
http scaler
Why this is correct
The http scaler scales container app replicas based on concurrent HTTP requests or traffic load.
About these practice questions
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed August 2026 · checked against the official Microsoft exam blueprint
This AI-200 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI-200 exam.