CodePipeline Manual Approval Step
A developer has set up an AWS CodePipeline pipeline that automatically deploys a web application through a series of stages: Source, Build, Staging, and Production. The developer wants to require a manual approval before the pipeline proceeds to the Production stage. How should the developer implement this?
Quick Answer
The correct answer is to add a manual approval action between the Staging and Production stages. This is the proper implementation because AWS CodePipeline allows you to insert a manual approval step as an action within a stage or as a standalone stage, which pauses the pipeline execution until an authorized user manually approves or rejects the transition. By placing this approval action between Staging and Production, the pipeline will halt after the Staging stage completes, preventing any automatic deployment to production without human oversight. On the AWS Certified Developer Associate DVA-C02 exam, this scenario tests your understanding of pipeline safety controls and the difference between automated and manual transitions—a common trap is thinking you can add the approval inside the Production stage itself, but the approval must gate the entry to that stage. Remember the memory tip: "Approve before you arrive"—the manual approval must occur before the pipeline reaches the production stage, not within it.
⚠ Common exam trap
Test-takers frequently think a manual approval action must be placed inside a stage (like Staging) rather than as a separate stage between stages, but CodePipeline allows stages to be ordered sequentially, and the approval action must be in its own stage or at the end of a stage to block the transition to the next stage.
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
✓
Add a manual approval action between the Staging and Production stages
AWS CodePipeline supports manual approval actions that can be added as a stage or between stages to pause the pipeline and require explicit approval before proceeding. By placing the manual approval action between the Staging and Production stages, the pipeline will halt after the Staging stage completes and wait for an approver to manually approve the transition to the Production stage, ensuring no automatic deployment to production occurs without human oversight.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Add a manual approval action in the Staging stage
Why it's wrong here
Incorrect. Adding approval in the Staging stage would halt the pipeline before Staging completes, which is not desired.
- ✓
Add a manual approval action between the Staging and Production stages
Why this is correct
Correct. A manual approval action placed as a separate stage or as an action in the transition between stages pauses the pipeline until approval is granted.
- ✗
Configure the Production stage to use a CloudFormation change set with execution role
Why it's wrong here
Incorrect. Change sets do not enforce manual approval in the pipeline; they are a deployment mechanism.
- ✗
Use an SNS topic to notify developers of the deployment
Why it's wrong here
Incorrect. SNS notifications do not block the pipeline; they just send alerts.
Go deeper
Related to this question
About these practice questions
One of 1,135 original DVA-C02 practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →
Same concept, more angles
1 more way this is tested on DVA-C02
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 developer is using AWS CodePipeline to automate the deployment of a microservices application. The pipeline consists of a source stage (GitHub), a build stage (AWS CodeBuild), and a deploy stage (Amazon ECS). The developer wants to ensure that only approved changes are deployed to production. Which THREE actions should the developer take? (Choose THREE.)
medium- A.Configure the pipeline to automatically deploy every commit to production.
- B.Deploy all feature branches directly to production.
- ✓ C.Add a manual approval step before the deploy stage.
- ✓ D.Use separate pipelines for different environments (e.g., dev, staging, prod).
- ✓ E.Implement integration tests in the build stage to catch errors early.
Why C: Option C is correct because inserting a manual approval action (an Approval action in CodePipeline, typically using Amazon SNS to notify approvers) between the build stage and the ECS deploy stage gates production deployment so that only changes a human explicitly approves proceed to production. Option D is correct because using separate pipelines for dev, staging, and prod isolates environments, so a change must pass through the earlier pipelines before a production pipeline is triggered, preventing unvetted commits from reaching production. Option E is correct because adding integration tests in the CodeBuild build stage (via buildspec.yml commands) validates the microservices against their dependencies and fails the pipeline on errors, so broken or unapproved-quality changes never reach the deploy stage. Option A is incorrect because automatically deploying every commit to production removes any approval gate and directly contradicts the requirement that only approved changes be deployed. Option B is incorrect because deploying all feature branches directly to production bypasses review, testing, and approval, which is exactly the risk the developer wants to eliminate.
JA
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.