DVA-C02 Deployment Practice Question
A company uses AWS CodePipeline to automate releases. The pipeline includes a source stage from CodeCommit, a build stage with CodeBuild, and a deploy stage with CodeDeploy. The build stage fails intermittently due to insufficient memory. What should the developer do to resolve this?
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
✓
Increase the compute type of the CodeBuild project.
AWS CodeBuild allows you to increase the compute type of the build project, which provides more memory and CPU resources, directly addressing the insufficient memory issue. Option B (changing deployment configuration) only affects the CodeDeploy stage and not the build stage. Option C (switching source to S3) does not resolve memory constraints. Option D (modifying buildspec.yml to use less memory) may help but is not a reliable solution and might require application changes; increasing the compute type is a more direct and effective fix.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Increase the compute type of the CodeBuild project.
Why this is correct
Increasing the CodeBuild compute type (for example moving from BUILD_GENERAL1_SMALL to BUILD_GENERAL1_MEDIUM or LARGE) provisions the build container with more vCPUs and RAM, directly addressing an out-of-memory failure that occurs intermittently under heavier build loads such as large dependency installs or parallel compilation steps.
- ✗
Change the deployment configuration to CodeDeploy.Default.AllAtOnce.
Why it's wrong here
CodeDeploy.Default.AllAtOnce is a deployment configuration that governs how many instances or tasks receive a new revision simultaneously during the Deploy stage; it has no bearing on the Build stage's compute resources and cannot resolve an out-of-memory error occurring in CodeBuild.
- ✗
Switch the source to an S3 bucket.
Why it's wrong here
Changing the pipeline's source provider from CodeCommit to an S3 bucket only changes where the source artifact originates from before the build starts; it does not alter the memory or CPU allocated to the CodeBuild compute environment, so it cannot fix a memory-related build failure.
- ✗
Modify the buildspec.yml to use less memory.
Why it's wrong here
The buildspec.yml file defines the sequence of build phases and shell commands CodeBuild executes; it has no directive for constraining or allocating memory to the build environment, since memory allocation is tied to the compute type setting on the CodeBuild project itself, not the buildspec.
Visual reference
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DVA-C02 practice question is part of Courseiva's free Amazon Web Services 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 DVA-C02 exam.