The correct answer is a KEDA-based scale rule for the queue trigger. This is because Azure Container Apps natively integrates with KEDA (Kubernetes Event-Driven Autoscaling) to enable event-driven scaling, allowing a containerized booking backend to scale to zero replicas when the Azure Queue Storage is empty and scale out dynamically as queue length grows. On the AZ-204 exam, this scenario tests your understanding of how to configure custom scale rules beyond the default HTTP-based scaling, often appearing in questions about cost optimization and idle resource management. A common trap is confusing KEDA with standard Azure Autoscale, which cannot scale to zero; remember that KEDA is the only native solution for zero-replica scaling in Container Apps. Memory tip: KEDA = "Kill Empty, Deploy Active" — it kills idle pods and deploys more when the queue demands action.
AZ-204 Develop Azure compute solutions Practice Question
This AZ-204 practice question tests your understanding of develop azure compute solutions. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A containerized booking backend deployed to Azure Container Apps must scale to zero when idle and scale out based on queue length. What should the developer configure?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
A KEDA-based scale rule for the queue trigger
Option D is correct because KEDA (Kubernetes Event-Driven Autoscaling) is natively integrated with Azure Container Apps to enable event-driven scaling. By configuring a KEDA-based scale rule with an Azure Queue Storage trigger, the container app can scale to zero replicas when the queue is empty and scale out based on the queue length, meeting the requirement for idle scaling and queue-driven scaling.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
A manual replica count only
Why it's wrong here
Manual replicas do not scale to zero or react to queue length.
✗
An Availability Set
Why it's wrong here
Availability Sets apply to VMs, not Container Apps scaling.
✗
An Azure Front Door health probe
Why it's wrong here
Health probes route traffic but do not scale Container Apps based on queue length.
✓
A KEDA-based scale rule for the queue trigger
Why this is correct
Azure Container Apps uses KEDA scale rules to scale replicas based on event sources such as queues.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse Azure Front Door health probes (used for traffic routing) with scaling triggers, or assume manual replica counts or Availability Sets are relevant to container scaling, when in fact KEDA is the specific technology for event-driven scaling in Azure Container Apps.
Detailed technical explanation
How to think about this question
KEDA works by querying the Azure Queue Storage REST API to monitor the approximate message count of a queue. When the queue length exceeds a configured threshold, KEDA triggers the Container Apps scaling controller to increase replica count; when the queue is empty, it scales down to zero. This is achieved through the `azure-queue` trigger in the KEDA ScaledObject, which uses the `connection` and `queueName` parameters to authenticate and poll the queue.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this AZ-204 question in full detail.
Develop Azure compute solutions — This question tests Develop Azure compute solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: A KEDA-based scale rule for the queue trigger — Option D is correct because KEDA (Kubernetes Event-Driven Autoscaling) is natively integrated with Azure Container Apps to enable event-driven scaling. By configuring a KEDA-based scale rule with an Azure Queue Storage trigger, the container app can scale to zero replicas when the queue is empty and scale out based on the queue length, meeting the requirement for idle scaling and queue-driven scaling.
What should I do if I get this AZ-204 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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Variation 1. A containerized checkout API deployed to Azure Container Apps must scale to zero when idle and scale out based on queue length. What should the developer configure?
hard
✓ A.A KEDA-based scale rule for the queue trigger
B.A manual replica count only
C.An Availability Set
D.An Azure Front Door health probe
Why A: Azure Container Apps supports KEDA (Kubernetes Event-Driven Autoscaling) for scaling based on external metrics. A KEDA-based scale rule configured with an Azure Queue Storage trigger allows the containerized checkout API to scale to zero when no messages are in the queue and scale out dynamically as queue length increases, meeting the requirement precisely.
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Question Discussion
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