The answer is Rolling with additional batch. This deployment policy is correct because it launches a new batch of instances before taking the old ones out of service, ensuring full capacity is maintained throughout the update. By adding a temporary batch of instances to absorb traffic during the rolling replacement, the environment remains highly available across multiple Availability Zones without any downtime, while also minimizing the number of new instances compared to an immutable deployment that would double the instance count. On the AWS Certified Developer Associate DVA-C02 exam, this question tests your understanding of how Elastic Beanstalk deployment policies balance availability, cost, and speed—a common trap is confusing “Rolling” (which reduces capacity) with “Rolling with additional batch” (which preserves capacity). For the exam, remember the key distinction: if the scenario emphasizes zero downtime and minimal new instances, choose Rolling with additional batch. A helpful memory tip is “add a batch to keep the batch running.”
DVA-C02 Deployment Practice Question
This DVA-C02 practice question tests your understanding of deployment. 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. A key principle to apply: rolling with additional batch ensures zero downtime during deployment.. 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 using AWS Elastic Beanstalk to deploy a web application. The application requires a highly available environment across multiple Availability Zones. The developer wants to update the application without any downtime while minimizing the number of new instances launched. Which deployment policy should the developer use?
Why wrong: This policy replaces all instances at the same time, causing application downtime during the deployment.
B
Rolling
Why wrong: Rolling updates instances in batches, but it terminates old instances before new ones are put into service, which can temporarily reduce capacity and cause downtime.
C
Rolling with additional batch
This policy launches a new batch of instances alongside the existing ones, ensuring capacity is never reduced. It achieves zero downtime with minimal additional instances compared to immutable.
D
Immutable
Why wrong: Immutable deployments launch a completely new environment with new instances, then swap the CNAME. This provides zero downtime but launches many new instances, not minimizing the number.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Rolling with additional batch
Option C (Rolling with additional batch) is correct because it launches a new batch of instances before taking the old ones out of service, ensuring full capacity is maintained during the deployment. This provides high availability across multiple Availability Zones while minimizing the number of new instances compared to an immutable deployment, which would double the instance count. The additional batch absorbs the traffic during the rolling update, preventing any downtime.
Key principle: Rolling with additional batch ensures zero downtime during deployment.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
All at once
Why it's wrong here
This policy replaces all instances at the same time, causing application downtime during the deployment.
✗
Rolling
Why it's wrong here
Rolling updates instances in batches, but it terminates old instances before new ones are put into service, which can temporarily reduce capacity and cause downtime.
✓
Rolling with additional batch
Why this is correct
This policy launches a new batch of instances alongside the existing ones, ensuring capacity is never reduced. It achieves zero downtime with minimal additional instances compared to immutable.
Related concept
Rolling with additional batch ensures zero downtime during deployment.
✗
Immutable
Why it's wrong here
Immutable deployments launch a completely new environment with new instances, then swap the CNAME. This provides zero downtime but launches many new instances, not minimizing the number.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse 'Rolling' with 'Rolling with additional batch', assuming both provide zero downtime, but only the latter guarantees full capacity throughout the update by adding an extra batch to absorb traffic.
Detailed technical explanation
How to think about this question
Under the hood, Elastic Beanstalk's 'Rolling with additional batch' policy first launches a new batch of instances (e.g., one extra instance per batch size) into the existing Auto Scaling group, then updates the original instances in batches, and finally terminates the extra batch. This ensures the environment's capacity never drops below the desired count, which is critical for applications that require a minimum number of healthy instances to serve traffic, such as those behind an Application Load Balancer with strict health check thresholds.
KKey Concepts to Remember
Rolling with additional batch ensures zero downtime during deployment.
It launches new instances before terminating old ones, maintaining capacity.
Temporarily exceeds desired instance count during the update process.
Minimizes new instance count compared to immutable deployments.
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
Rolling with additional batch ensures zero downtime during deployment.
Real-world example
How this comes up in practice
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
Got this wrong? Here's your next step.
Review rolling with additional batch ensures zero downtime during deployment., then practise related DVA-C02 questions on the same topic to reinforce the concept.
Deployment — This question tests Deployment — Rolling with additional batch ensures zero downtime during deployment..
What is the correct answer to this question?
The correct answer is: Rolling with additional batch — Option C (Rolling with additional batch) is correct because it launches a new batch of instances before taking the old ones out of service, ensuring full capacity is maintained during the deployment. This provides high availability across multiple Availability Zones while minimizing the number of new instances compared to an immutable deployment, which would double the instance count. The additional batch absorbs the traffic during the rolling update, preventing any downtime.
What should I do if I get this DVA-C02 question wrong?
Review rolling with additional batch ensures zero downtime during deployment., then practise related DVA-C02 questions on the same topic to reinforce the concept.
What is the key concept behind this question?
Rolling with additional batch ensures zero downtime during deployment.
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Variation 1. A developer is deploying a web application on AWS Elastic Beanstalk. The application needs to run on multiple instances behind a load balancer. Which deployment policy will cause the LEAST downtime?
easy
A.All at once
B.Rolling
✓ C.Rolling with additional batch
D.Immutable
Why C: Option D is correct because rolling with additional batch adds new instances before taking old ones out of service, resulting in zero downtime. Option A is wrong because all at once causes downtime. Option B is wrong because rolling causes some downtime. Option C is wrong because immutable launches a full new set, causing temporary doubling of instances.
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Question Discussion
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