Quick Answer
The correct choice is the Kubernetes Event-driven Autoscaler (KEDA) because it is the only solution that supports scaling AKS pods to zero when there is no HTTP traffic, directly addressing the need to minimize cost. KEDA works by monitoring external event sources—such as HTTP request metrics—and dynamically adjusting the replica count, including scaling down to zero pods when the event source is idle, which the standard Horizontal Pod Autoscaler (HPA) cannot do since HPA enforces a minimum replica count of one. On the Microsoft Azure Solutions Architect Expert AZ-305 exam, this question tests your understanding of autoscaling boundaries within AKS, often appearing as a trap where candidates confuse the Cluster Autoscaler (which scales nodes, not pods) or the Vertical Pod Autoscaler (which adjusts CPU/memory, not pod count) with event-driven scaling. A helpful memory tip: think of KEDA as the “zero hero” for event-driven workloads—if the event stops, KEDA stops the pods.
This AZ-305 practice question tests your understanding of design infrastructure solutions. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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.
You are designing a containerized microservices application on Azure Kubernetes Service (AKS). The application must scale automatically based on HTTP traffic. You need to minimize cost by scaling down to zero pods when there is no traffic. Which scaling solution should you use?
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.
Horizontal Pod Autoscaler (HPA)
Why wrong: HPA cannot scale to zero pods.
Cluster Autoscaler
Why wrong: Cluster Autoscaler scales nodes, not pods.
Kubernetes Event-driven Autoscaler (KEDA)
KEDA can scale to zero based on HTTP traffic.
Vertical Pod Autoscaler (VPA)
Why wrong: VPA adjusts resource limits, not pod count.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Kubernetes Event-driven Autoscaler (KEDA)
Option B is correct. The Kubernetes Event-driven Autoscaler (KEDA) can scale based on HTTP requests and supports scaling to zero pods when there is no traffic. Option A is wrong because the horizontal pod autoscaler (HPA) cannot scale to zero. Option C is wrong because the cluster autoscaler scales nodes, not pods. Option D is wrong because the vertical pod autoscaler adjusts resource requests, not number of pods.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Horizontal Pod Autoscaler (HPA)
Why it's wrong here
HPA cannot scale to zero pods.
Cluster Autoscaler
Why it's wrong here
Cluster Autoscaler scales nodes, not pods.
Kubernetes Event-driven Autoscaler (KEDA)
Why this is correct
KEDA can scale to zero based on HTTP traffic.
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.
Vertical Pod Autoscaler (VPA)
Why it's wrong here
VPA adjusts resource limits, not pod count.
Common exam traps
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
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.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
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.
What to study next
Identify which AZ-305 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.
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FAQ
Design infrastructure solutions — This question tests Design infrastructure solutions — Read the scenario before looking for a memorised answer..
The correct answer is: Kubernetes Event-driven Autoscaler (KEDA) — Option B is correct. The Kubernetes Event-driven Autoscaler (KEDA) can scale based on HTTP requests and supports scaling to zero pods when there is no traffic. Option A is wrong because the horizontal pod autoscaler (HPA) cannot scale to zero. Option C is wrong because the cluster autoscaler scales nodes, not pods. Option D is wrong because the vertical pod autoscaler adjusts resource requests, not number of pods.
Identify which AZ-305 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.
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.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 20, 2026
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