SAP-C02 Continuous Improvement for Existing Solutions Practice Question
A company is using AWS CodePipeline to automate deployments of a web application. The deployment to an Amazon ECS cluster often fails during the 'Deploy' stage due to insufficient capacity in the target group. The operations team wants to improve the pipeline to automatically handle such failures without manual intervention. Which solution is MOST operationally efficient?
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 retry action in the CodePipeline stage for the ECS deployment.
The most operationally efficient because it uses CodePipeline's built-in retry mechanism to automatically retry the failed 'Deploy' stage when the ECS deployment fails due to insufficient capacity. This eliminates the need for manual intervention or additional services like Lambda, reducing operational overhead. Option A adds unnecessary complexity with CloudWatch Alarms and Lambda. Option B does not address capacity issues. Option C requires manual approval, which is not automated. Option D would reduce capacity, exacerbating the failure.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use Amazon CloudWatch Alarms to trigger an AWS Lambda function that restarts the pipeline.
Why it's wrong here
This adds unnecessary complexity; CodePipeline already has built-in retry capabilities.
- ✗
Modify the CodeBuild project to run integration tests after deployment.
Why it's wrong here
Smoke tests do not address the capacity failure during deployment.
- ✗
Add a manual approval step before the deploy stage to verify capacity.
Why it's wrong here
Manual approval requires human intervention and is not operationally efficient.
- ✗
Configure the ECS service to automatically scale down the desired count on deployment failure.
Why it's wrong here
Scaling down would reduce capacity, exacerbating the issue.
- ✓
Add a retry action in the CodePipeline stage for the ECS deployment.
Why this is correct
Correct because CodePipeline supports retry actions that automatically retry the stage on failure, reducing operational overhead.
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 |
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