The answer is to use KEDA autoscaling for Service Bus queue in AKS, as this approach directly ties pod scaling to the number of messages waiting in the queue. KEDA (Kubernetes Event-Driven Autoscaling) monitors the Service Bus queue length and dynamically adjusts the number of pods in your AKS cluster, scaling to zero when no messages are present, which minimizes cost by avoiding idle compute resources. On the AZ-204 exam, this scenario tests your understanding of event-driven scaling patterns versus traditional metrics-based autoscaling; a common trap is choosing the Service Bus SDK with manual scaling, which lacks automation, or Azure Functions on a dedicated plan, which incurs cost even when idle. Remember that KEDA is purpose-built for Kubernetes to handle queue-driven workloads efficiently, making it the cost-effective, automatic choice. Memory tip: KEDA = "Kubernetes Event-Driven Autoscaler" — think "KEDA queues the pods to match the messages."
AZ-204 Practice Question: Connect to and consume Azure services and third-party services
This AZ-204 practice question tests your understanding of connect to and consume azure services and third-party services. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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 developer is building a microservices application on Azure Kubernetes Service (AKS). One service needs to consume messages from an Azure Service Bus queue. The solution must minimize cost and automatically scale based on the number of messages. Which approach should the developer choose?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "minimum / minimize"
Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use KEDA to scale the pods based on the Service Bus queue length
Option A is correct because KEDA (Kubernetes Event-Driven Autoscaling) can scale pods based on Service Bus queue length, and it's cost-effective. Option B is incorrect because the Service Bus SDK with manual scaling doesn't provide automatic scaling. Option C is incorrect because Azure Functions running on a dedicated plan would incur cost even when idle. Option D is incorrect because Azure Event Grid is for event routing, not queue consumption.
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.
✓
Use KEDA to scale the pods based on the Service Bus queue length
Why this is correct
KEDA provides event-driven autoscaling for Kubernetes based on queue length, optimizing cost.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Use Azure Event Grid to route messages to the microservice
Why it's wrong here
Event Grid is not designed for queuing messages.
✗
Use Azure Functions with a Service Bus trigger on a dedicated App Service plan
Why it's wrong here
Azure Functions on a dedicated plan incur cost even when idle.
✗
Use the Azure Service Bus SDK in the pod code and manually scale pods
Why it's wrong here
Manual scaling does not provide automatic scaling based on demand.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
Use explanations to understand the rule behind the answer.
TExam Day Tips
→Underline the problem statement mentally.
→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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this AZ-204 question in full detail.
Identify which AZ-204 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Connect to and consume Azure services and third-party services — This question tests Connect to and consume Azure services and third-party services — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use KEDA to scale the pods based on the Service Bus queue length — Option A is correct because KEDA (Kubernetes Event-Driven Autoscaling) can scale pods based on Service Bus queue length, and it's cost-effective. Option B is incorrect because the Service Bus SDK with manual scaling doesn't provide automatic scaling. Option C is incorrect because Azure Functions running on a dedicated plan would incur cost even when idle. Option D is incorrect because Azure Event Grid is for event routing, not queue consumption.
What should I do if I get this AZ-204 question wrong?
Identify which AZ-204 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Are there clue words in this question I should notice?
Yes — watch for: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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