- A
Deploy the web tier behind a load balancer with auto-scaling. Keep the application tier as a single instance with session replication to a secondary instance. Use a managed database with a read replica.
Why wrong: While this improves scalability for the web tier, the application tier remains stateful and session replication to a single secondary does not provide full high availability; a distributed cache would be better.
- B
Deploy the web tier behind a load balancer with auto-scaling. Move session state from the application tier to a distributed caching service. Deploy the application tier behind a separate load balancer with auto-scaling. Migrate the database to a managed Multi-AZ deployment.
This design is fully cloud-native: the web and application tiers are stateless and auto-scaled, session state is stored externally in a highly available cache, and the database is managed with Multi-AZ for high availability.
- C
Use a load balancer for the web tier with auto-scaling. Deploy the application tier as a single large instance with sticky sessions. Migrate the database to a larger single-instance managed database.
Why wrong: Sticky sessions tie a user to a specific instance, reducing scalability and availability. The database is still a single point of failure.
- D
Deploy both web and application tiers behind a load balancer with auto-scaling. Use sticky sessions to maintain session state. Migrate the database to a managed Multi-AZ deployment.
Why wrong: Sticky sessions limit scalability because sessions are tied to specific instances. The application tier still stores session data in memory, which is lost if the instance fails.
Quick Answer
The correct answer is to deploy the web tier behind a load balancer with auto-scaling, move session state to a distributed caching service, deploy the application tier behind a separate load balancer with auto-scaling, and migrate the database to a managed Multi-AZ deployment. This solution achieves high availability across availability zones during cloud migration by decoupling state from the application tier, making it stateless and scalable, while the Multi-AZ database provides automatic failover. On the CompTIA Cloud+ CV0-004 exam, this scenario tests your ability to redesign monolithic on-premises architectures into cloud-native patterns that eliminate single points of failure. A common trap is leaving session data in local memory, which breaks auto-scaling and availability; the key insight is that distributed caching (like Redis) externalizes state. Remember the mnemonic “WAD” for Web tier, App tier (stateless via cache), and Database (Multi-AZ) to recall the three critical layers for a resilient migration.
CV0-004 Cloud Architecture and Design Practice Question
This CV0-004 practice question tests your understanding of cloud architecture and design. 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.
A company is migrating its on-premises e-commerce application to a public cloud. The application consists of a stateless web tier, a stateful application tier that stores session data in memory, and a relational database. The migration must ensure high availability, scalability, and minimal downtime during cutover. The cloud provider offers load balancers, auto-scaling groups, managed database services, and caching services. The current on-premises architecture uses a single web server, a single application server, and a single database server. The application tier stores session data in local memory, which is lost if the server fails. The team needs to redesign the architecture to be cloud-native. Which of the following is the BEST course of action?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"best"Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
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
Deploy the web tier behind a load balancer with auto-scaling. Move session state from the application tier to a distributed caching service. Deploy the application tier behind a separate load balancer with auto-scaling. Migrate the database to a managed Multi-AZ deployment.
Option B is correct because it addresses the key requirements: high availability, scalability, and minimal downtime. By moving session state from local memory to a distributed caching service (e.g., Amazon ElastiCache or Azure Cache for Redis), the application tier becomes stateless and can be auto-scaled behind its own load balancer. The managed Multi-AZ database provides automatic failover and high availability, while the web tier behind a load balancer with auto-scaling ensures scalability and fault tolerance. This design eliminates single points of failure and allows zero-downtime cutover by scaling out before decommissioning on-premises resources.
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.
- ✗
Deploy the web tier behind a load balancer with auto-scaling. Keep the application tier as a single instance with session replication to a secondary instance. Use a managed database with a read replica.
Why it's wrong here
While this improves scalability for the web tier, the application tier remains stateful and session replication to a single secondary does not provide full high availability; a distributed cache would be better.
- ✓
Deploy the web tier behind a load balancer with auto-scaling. Move session state from the application tier to a distributed caching service. Deploy the application tier behind a separate load balancer with auto-scaling. Migrate the database to a managed Multi-AZ deployment.
Why this is correct
This design is fully cloud-native: the web and application tiers are stateless and auto-scaled, session state is stored externally in a highly available cache, and the database is managed with Multi-AZ for high availability.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use a load balancer for the web tier with auto-scaling. Deploy the application tier as a single large instance with sticky sessions. Migrate the database to a larger single-instance managed database.
Why it's wrong here
Sticky sessions tie a user to a specific instance, reducing scalability and availability. The database is still a single point of failure.
- ✗
Deploy both web and application tiers behind a load balancer with auto-scaling. Use sticky sessions to maintain session state. Migrate the database to a managed Multi-AZ deployment.
Why it's wrong here
Sticky sessions limit scalability because sessions are tied to specific instances. The application tier still stores session data in memory, which is lost if the instance fails.
Common exam traps
Common exam trap: answer the scenario, not the keyword
CompTIA often tests the misconception that sticky sessions or session replication are sufficient for high availability in a cloud environment, but the correct approach is to externalize session state to a distributed cache to achieve true statelessness and scalability.
Detailed technical explanation
How to think about this question
Distributed caching services like Redis or Memcached store session data in memory across multiple nodes, providing sub-millisecond access and automatic replication for fault tolerance. In a cloud-native architecture, the application tier can be designed to read/write session state to the cache, making it stateless and allowing it to scale horizontally behind a load balancer without session affinity. Managed Multi-AZ database deployments (e.g., Amazon RDS Multi-AZ) synchronously replicate data to a standby instance in a different Availability Zone, enabling automatic failover with minimal downtime (typically under 60 seconds).
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 small business has 20 workstations on the 192.168.1.0/24 network and one public IP from its ISP. The router uses PAT (NAT overload) so all 20 devices share one public address using different source ports. NAT questions test whether you understand the four address terms and which direction each translation applies.
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this CV0-004 question test?
Cloud Architecture and Design — This question tests Cloud Architecture and Design — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Deploy the web tier behind a load balancer with auto-scaling. Move session state from the application tier to a distributed caching service. Deploy the application tier behind a separate load balancer with auto-scaling. Migrate the database to a managed Multi-AZ deployment. — Option B is correct because it addresses the key requirements: high availability, scalability, and minimal downtime. By moving session state from local memory to a distributed caching service (e.g., Amazon ElastiCache or Azure Cache for Redis), the application tier becomes stateless and can be auto-scaled behind its own load balancer. The managed Multi-AZ database provides automatic failover and high availability, while the web tier behind a load balancer with auto-scaling ensures scalability and fault tolerance. This design eliminates single points of failure and allows zero-downtime cutover by scaling out before decommissioning on-premises resources.
What should I do if I get this CV0-004 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "best". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
What is the key concept behind this question?
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 →
Same concept, more angles
2 more ways this is tested on CV0-004
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A company runs a critical application on a cloud VM that must achieve a 99.99% monthly uptime SLA. The VM is deployed in a single availability zone. The current architecture has no redundancy. What is the most effective design change to meet the SLA requirement?
hard- A.Schedule daily backups to a different region
- ✓ B.Deploy the application across two availability zones with a load balancer
- C.Upgrade the VM to a larger instance type for better reliability
- D.Add a second VM in the same availability zone with a load balancer
Why B: Option B is correct because deploying the application across two availability zones with a load balancer provides high availability by eliminating a single point of failure. A 99.99% monthly uptime SLA requires a design that can withstand an entire availability zone failure, which a single-zone deployment cannot achieve. The load balancer distributes traffic to healthy VMs, automatically failing over if one zone becomes unavailable, thus meeting the SLA target.
Variation 2. A cloud architect is designing a multi-tier web application in a cloud environment. The application must handle unpredictable traffic spikes while minimizing costs. The architect decides to use auto-scaling groups for the web tier and a managed database service for the data tier. Which additional design consideration is MOST important to ensure the application remains available during a regional outage?
medium- ✓ A.Distribute the auto-scaling group across multiple availability zones
- B.Configure the auto-scaling group to burst into on-premises resources during spikes
- C.Increase the size of the web tier instances to handle more traffic
- D.Use a read replica of the database to distribute read traffic
Why A: Distributing the auto-scaling group across multiple Availability Zones (AZs) ensures that if one AZ fails, the web tier continues to serve traffic from the remaining AZs. This is the most critical design consideration for maintaining availability during a regional outage because it provides fault isolation at the AZ level, which is a fundamental principle of high availability in cloud architecture.
Keep practising
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Last reviewed: Jun 30, 2026
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