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Question 1,749 of 1,750

SDLC Automation →mediumMultiple ChoiceObjective-mapped

Configuring AWS CodePipeline to Run Tests on Every Branch but Deploy to Production Only from Main

This DOP-C02 practice question tests your understanding of sdlc automation. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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 DevOps team uses AWS CodePipeline with a multi-branch strategy. The pipeline should deploy to production only from the 'main' branch, but run unit tests for all branches. How should the team configure the pipeline?

A
Configure the pipeline source stage to trigger on all branches, use branch-specific logic in the test stage, and add a manual approval step for production deployment only when the branch is 'main'.
Branch filtering in source stage and conditional deployment is the recommended approach.
B
Use an AWS Lambda function to check the branch name and invoke different CodePipeline executions for testing and deployment.
Why wrong: Complex and not as straightforward as built-in branch filtering.
C
Create one pipeline with two source stages: one for 'main' and one for all other branches, each with its own test and deploy actions.
Why wrong: Pipeline stages are sequential; cannot have two source stages for different branches in same pipeline.
D
Create a separate pipeline for each branch, each with identical test and deploy stages.
Why wrong: Managing many pipelines is inefficient and error-prone.

Full breakdown with real-world context →

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

✓

Configure the pipeline source stage to trigger on all branches, use branch-specific logic in the test stage, and add a manual approval step for production deployment only when the branch is 'main'.

Option A is correct because AWS CodePipeline supports branch filtering in the source stage to trigger on all branches, and you can use a condition in the deploy stage (e.g., via a Lambda function or a manual approval step) to restrict production deployment to the 'main' branch only. This approach avoids duplicating pipelines while ensuring unit tests run for every branch, meeting the multi-branch strategy requirement efficiently.

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.

✓
Configure the pipeline source stage to trigger on all branches, use branch-specific logic in the test stage, and add a manual approval step for production deployment only when the branch is 'main'.
Why this is correct
Branch filtering in source stage and conditional deployment is the recommended approach.
Related concept
Read the scenario before looking for a memorised answer.
✗
Use an AWS Lambda function to check the branch name and invoke different CodePipeline executions for testing and deployment.
Why it's wrong here
Complex and not as straightforward as built-in branch filtering.
✗
Create one pipeline with two source stages: one for 'main' and one for all other branches, each with its own test and deploy actions.
Why it's wrong here
Pipeline stages are sequential; cannot have two source stages for different branches in same pipeline.
✗
Create a separate pipeline for each branch, each with identical test and deploy stages.
Why it's wrong here
Managing many pipelines is inefficient and error-prone.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates may think they need separate pipelines or multiple source stages to handle branch-specific logic, but CodePipeline's branch filtering and conditional actions (like Lambda checks or manual approvals) allow a single pipeline to handle all branches efficiently.

Detailed technical explanation

How to think about this question

Under the hood, CodePipeline's source stage uses webhook events from AWS CodeCommit or GitHub to trigger on branch pushes, and you can configure branch filters (e.g., 'main' or '*') at the source action level. For conditional deployment, you can use a Lambda-based approval action or a custom action that checks the branch name from the pipeline context (e.g., via the 'SourceVariables.CommitBranch' variable) to skip or proceed with the deploy stage. In real-world scenarios, teams often combine this with a manual approval step to add a safety gate for production, ensuring only 'main' branch changes reach production while all branches trigger tests.

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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.

Quick reference

Cloud Service Model Comparison

Model	You Manage	Provider Manages	Examples
IaaS	OS, runtime, apps, data	Hardware, hypervisor, networking	EC2, Azure VMs, GCP Compute Engine
PaaS	Apps and data	OS, runtime, middleware, hardware	Elastic Beanstalk, Azure App Service
SaaS	Data and settings only	Everything else	Microsoft 365, Salesforce, Workday
FaaS / Serverless	Function code only	Infra, scaling, runtime	Lambda, Azure Functions, Cloud Run
CaaS	Containers and apps	Kubernetes, OS, hardware	EKS, AKS, GKE

What to study next

Got this wrong? Here's your next step.

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

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FAQ

Questions learners often ask

What does this DOP-C02 question test?

SDLC Automation — This question tests SDLC Automation — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Configure the pipeline source stage to trigger on all branches, use branch-specific logic in the test stage, and add a manual approval step for production deployment only when the branch is 'main'. — Option A is correct because AWS CodePipeline supports branch filtering in the source stage to trigger on all branches, and you can use a condition in the deploy stage (e.g., via a Lambda function or a manual approval step) to restrict production deployment to the 'main' branch only. This approach avoids duplicating pipelines while ensuring unit tests run for every branch, meeting the multi-branch strategy requirement efficiently.

What should I do if I get this DOP-C02 question wrong?

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

About these practice questions

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Same concept, more angles

1 more ways this is tested on DOP-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. An organization uses AWS CodePipeline with a multi-branch strategy. They want to run unit tests on every push to any branch, but only deploy to production on pushes to the 'main' branch. What is the most efficient way to achieve this?

medium

✓ A.Configure a single pipeline with a source action that triggers on all branches, then use a 'branch' condition on the deployment stage to only proceed if the branch is 'main'.
B.Use a single pipeline with a source action that triggers on all branches, and deploy to a test environment for all branches, then promote to production manually.
C.Create separate pipelines for each branch, each with its own test and deploy stages.
D.Use a single pipeline with a source action that only triggers on the 'main' branch, and run tests in a separate system.

Why A: Option A is correct because AWS CodePipeline supports a single pipeline with a source action configured to trigger on all branches (e.g., using a webhook event filter for 'refs/heads/*'). You can then add a 'branch' condition on the deployment stage using a Lambda function or a manual approval action that checks the branch name, ensuring only pushes to 'main' proceed to production. This approach avoids duplicating pipelines while still running unit tests on every push.

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