DOP-C02 SDLC Automation Practice Question
A DevOps team is designing a CI/CD pipeline for a containerized application. Which THREE components are essential for a complete pipeline? (Choose three.)
⚠ Common exam trap
A common mix-up: candidates confuse 'deployment service' (CodeDeploy) with a pipeline component, or mistake monitoring (CloudWatch) as essential, when the question specifically asks for the three core stages that form a complete pipeline: source, build/test, and artifact storage.
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
✓
Artifact storage
Artifact storage (Option B) is essential because a complete CI/CD pipeline must store build outputs (e.g., Docker images, JAR files) in a durable, versioned repository. Without artifact storage, subsequent deployment stages cannot reliably retrieve the exact build artifact that passed testing, breaking traceability and rollback capabilities. Services like Amazon ECR or S3 serve this role, ensuring immutability and consistent delivery across environments.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
AWS CodeDeploy
Why it's wrong here
AWS CodeDeploy is a deployment service that orchestrates app deployment to EC2, on-premises, or ECS, but it is not an essential component of a CI/CD pipeline. A containerized pipeline can deploy using native ECS rolling updates, Kubernetes controllers, or third-party tools like Argo CD, meaning CodeDeploy can be swapped out without breaking the core flow. The fundamental pipeline elements—source control, build/test, and artifact storage—remain intact even when CodeDeploy is replaced, so it is optional rather than mandatory.
- ✓
Artifact storage
Why this is correct
Artifact storage is the durable, versioned repository that holds the output of the build stage, such as Docker images in Amazon ECR or packages in S3, until the deployment stage consumes them. Without this component, builds are ephemeral and you cannot reliably reproduce a release, roll back to a known-good version, or audit exactly what was deployed. In a container context, the image registry is a distinct stateful service that integrates with IAM and image scanning, making it a non-negotiable pipeline component.
- ✗
Amazon CloudWatch
Why it's wrong here
Amazon CloudWatch is an observability service used to collect and monitor metrics, logs, and alarms; it does not execute or coordinate any CI/CD pipeline stage. A pipeline can run to completion without CloudWatch by relying on alternative logging or no logging at all, because the core stages of source control, build/test, and artifact storage are unaffected. CloudWatch becomes valuable only when you add operational feedback loops, but that does not make it a core pipeline component.
- ✓
Build and test automation
Why this is correct
Build and test automation is the heart of continuous integration: it automatically compiles code, runs unit and integration tests, and performs static analysis or image scanning on every commit. In a containerized pipeline, this stage typically invokes a Docker build and executes tests inside the container, converting source code into a testable artifact. Without this automated gate, defects go undetected until later stages, eliminating the primary benefit of CI/CD, which is early, fast feedback to developers.
- ✓
Source control repository
Why this is correct
A source control repository provides the single source of truth for all application code and infrastructure-as-code, using Git-based systems like AWS CodeCommit, GitHub, or GitLab. It triggers the pipeline via webhooks or polling on every push, and it enables traceability through commits, pull requests, and branch-based strategies that control which versions get deployed. Without versioned source, the build stage has no deterministic input, making reproducible builds and auditable deployments impossible.
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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