DVA-C02 Deployment Practice Question
Which THREE steps are required to set up a continuous delivery pipeline using AWS CodePipeline, CodeBuild, and CodeDeploy? (Select THREE.)
⚠ Common exam trap
Many candidates think a database or a Lambda trigger is a required component, but the core pipeline only needs source, build, and deploy stages; additional services like RDS or Lambda are optional and not part of the minimal setup.
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
✓
Create a deploy stage with CodeDeploy to deploy the artifacts.
Option B is correct because a CodePipeline continuous delivery pipeline requires a deploy stage, and CodeDeploy is the AWS service used in that stage to deploy the built artifacts to targets such as EC2 instances, Lambda functions, or ECS services. Option D is correct because CodeBuild provides the build stage where the source code is compiled, tested, and packaged into deployable artifacts, which is a core step in a CodePipeline workflow. Option E is correct because every CodePipeline must begin with a source stage that retrieves the code from a repository such as AWS CodeCommit, GitHub, or Amazon S3, which then triggers the pipeline on changes. Option A is incorrect because CodePipeline and CodeDeploy do not require an Amazon RDS database to store deployment logs; logs are handled by CloudWatch Logs and S3 artifacts. Option C is incorrect because CodePipeline is natively triggered by source changes or EventBridge rules, not by a custom Lambda function, so creating a Lambda trigger is not a required setup step.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Set up an Amazon RDS database to store deployment logs.
Why it's wrong here
Setting up an Amazon RDS database specifically for storing deployment logs is not a required or standard practice for continuous delivery pipelines on AWS. While RDS is excellent for relational data, AWS CloudWatch Logs is the purpose-built and integrated service for collecting, monitoring, and analyzing logs from various AWS services, including CodePipeline and CodeDeploy. Utilizing CloudWatch Logs offers better scalability, cost-effectiveness, and native integration for log management within the AWS ecosystem compared to a relational database.
- ✓
Create a deploy stage with CodeDeploy to deploy the artifacts.
Why this is correct
A deploy stage is an absolutely essential component of any continuous delivery pipeline, responsible for taking the validated build artifacts and deploying them to the target environment. AWS CodeDeploy is the primary service used within CodePipeline for this purpose, supporting deployments to Amazon EC2 instances, AWS Lambda functions, and Amazon ECS services. This stage automates the release process, ensuring that the application is consistently and reliably delivered to production or staging environments after successful compilation and testing.
- ✗
Configure an AWS Lambda function to trigger the pipeline.
Why it's wrong here
Configuring an AWS Lambda function to trigger a CodePipeline is not a required step for setting up a continuous delivery pipeline. CodePipeline offers native integrations with source control services like AWS CodeCommit, Amazon S3, and GitHub, which automatically trigger the pipeline upon code changes or new object uploads. While Lambda could be used for highly custom or external triggering mechanisms, it is not necessary for a standard CD setup, as built-in triggers handle most common scenarios efficiently.
- ✓
Create a build stage with CodeBuild to compile and test the code.
Why this is correct
A build stage is a fundamental requirement in a continuous delivery pipeline, transforming raw source code into deployable artifacts. AWS CodeBuild is the managed service designed for this purpose, capable of compiling source code, running unit tests, and producing packaged application artifacts. This stage ensures that the code is syntactically correct, functionally sound, and ready for deployment, serving as a critical gate before the application moves to the deployment phase.
- ✓
Create a source stage that retrieves code from a repository.
Why this is correct
The source stage is the initial and indispensable step in any continuous delivery pipeline, serving as the entry point for the entire workflow. This stage is responsible for retrieving the application's source code from a version control repository, such as AWS CodeCommit, GitHub, or an Amazon S3 bucket. Without a source stage, there would be no code to process, build, or deploy, making it the foundational element that initiates every pipeline execution.
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.