Quick Answer
The correct answer is the HTTP scaling rule using KEDA, because it is purpose-built for Azure Container Apps to scale based on the number of concurrent HTTP requests, directly addressing high CPU usage and slow response times by reacting to incoming request volume before resource saturation occurs. Unlike CPU or memory-based rules, which respond only after resources are already strained, KEDA’s HTTP scaler proactively triggers scaling based on request load, making it the ideal choice for microservices handling variable traffic. On the AZ-204 exam, this concept tests your understanding of event-driven autoscaling versus metric-based scaling; a common trap is selecting CPU or memory rules, which are reactive rather than proactive. Remember the memory tip: “HTTP hits first, CPU catches up later”—KEDA’s HTTP scaler handles the surge before CPU spikes, so always choose the request-based rule when the prompt mentions slow responses due to high load.
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.
You have an Azure Container Apps environment running multiple microservices. One microservice is experiencing high CPU usage and slow response times. You need to configure autoscaling rules to scale based on HTTP requests. Which scaling rule should you add?
HTTP scaling rule (KEDA)
HTTP scaling rule scales based on request rate, ideal for web microservices.
CPU percentage scaling rule
Why wrong: CPU scaling does not directly respond to HTTP request spikes.
Memory percentage scaling rule
Why wrong: Memory scaling is not appropriate for HTTP request bursts.
Custom scaling rule using Azure Monitor metrics
Why wrong: Custom metrics are possible but not as straightforward as built-in HTTP scaler.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
HTTP scaling rule (KEDA)
Option A is correct because KEDA's HTTP scaling rule is specifically designed to scale Azure Container Apps based on the number of concurrent HTTP requests, which directly addresses high CPU usage and slow response times caused by request load. Unlike CPU or memory metrics, HTTP scaling reacts to incoming request volume proactively, allowing the microservice to handle spikes before resource saturation occurs.
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.
HTTP scaling rule (KEDA)
Why this is correct
HTTP scaling rule scales based on request rate, ideal for web microservices.
Related concept
Read the scenario before looking for a memorised answer.
CPU percentage scaling rule
Why it's wrong here
CPU scaling does not directly respond to HTTP request spikes.
Memory percentage scaling rule
Why it's wrong here
Memory scaling is not appropriate for HTTP request bursts.
Custom scaling rule using Azure Monitor metrics
Why it's wrong here
Custom metrics are possible but not as straightforward as built-in HTTP scaler.
Common exam traps
The trap here is that candidates often choose CPU or memory scaling rules because they seem directly related to high CPU usage, but the question explicitly asks for scaling based on HTTP requests, which requires a request-based scaler like KEDA's HTTP scaler, not resource-based metrics.
Detailed technical explanation
KEDA's HTTP scaler works by deploying an intercepting component (the HTTP add-on) that measures the average number of pending HTTP requests per pod over a sliding window (default 5 seconds). It then scales the number of replicas to maintain a target requests-per-second (default 50) per instance, enabling proactive scaling before CPU or memory metrics degrade. This is particularly effective in event-driven architectures where request bursts are unpredictable, such as e-commerce checkout flows during flash sales.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
What to study next
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Develop Azure compute solutions — study guide chapter
Learn the concepts, then practise the questions
Develop Azure compute solutions practice questions
Targeted practice on this topic area only
All AZ-204 questions
997 questions across all exam domains
Microsoft Azure Developer Associate AZ-204 study guide
Full concept coverage aligned to exam objectives
AZ-204 practice test guide
How to use practice tests most effectively before exam day
Related practice questions
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
Practise AZ-204 questions linked to Develop Azure compute solutions.
Practise AZ-204 questions linked to Develop for Azure storage.
Practise AZ-204 questions linked to Implement Azure security.
Practise AZ-204 questions linked to Connect to and consume Azure services and third-party services.
Practise AZ-204 questions linked to Monitor, troubleshoot, and optimize Azure solutions.
Practise AZ-204 questions linked to AZ-204 fundamentals.
Practise AZ-204 questions linked to AZ-204 scenario.
Practise AZ-204 questions linked to AZ-204 troubleshooting.
Practice this exam
Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.
FAQ
Develop Azure compute solutions — This question tests Develop Azure compute solutions — Read the scenario before looking for a memorised answer..
The correct answer is: HTTP scaling rule (KEDA) — Option A is correct because KEDA's HTTP scaling rule is specifically designed to scale Azure Container Apps based on the number of concurrent HTTP requests, which directly addresses high CPU usage and slow response times caused by request load. Unlike CPU or memory metrics, HTTP scaling reacts to incoming request volume proactively, allowing the microservice to handle spikes before resource saturation occurs.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Last reviewed: Jun 24, 2026
This AZ-204 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 AZ-204 exam.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.