Amazon Web Services DOP-C02 Exam With Confidence Using Practice Dumps

AWS CodeDeploy supports deployment of both Lambda functions and ECS services with native integration.

It provides deployment strategies such as canary deployments for Lambda and blue/green deployments for ECS, which minimize downtime and risk.

CodeDeploy automates the deployment process, which reduces manual effort and improves consistency.

AWS Systems Manager Parameter Store is a simple, managed solution for storing configuration data securely and at scale.

Option A uses CloudFormation stack updates with resource replacement, which can cause downtime and is less flexible for minimizing downtime compared to CodeDeploy’s deployment strategies.

Option C adds unnecessary orchestration complexity with Step Functions and cross-region deployments, increasing deployment effort.

Option D’s all-at-once deployments for Lambda and rolling updates for ECS do not minimize downtime as effectively as canary and blue/green strategies.Hence, option B meets the requirement with the least deployment effort and maximizes automation and availability.

Reference from AWS Official Documentation:

Deploying Lambda Functions with CodeDeploy:"AWS CodeDeploy supports canary and linear deployment strategies for AWS Lambda functions to reduce deployment risk."(CodeDeploy Lambda Deployment)

Deploying ECS Services with CodeDeploy Blue/Green:"CodeDeploy supports blue/green deployments for ECS to minimize downtime during service updates."(CodeDeploy ECS Blue/Green)

AWS Systems Manager Parameter Store:"Parameter Store provides secure, hierarchical storage for configuration data management."(Systems Manager Parameter Store)

The requirement is to prevent any product files containing unannounced product IDs (prefixed with a specific UUID) from being stored in the production S3 bucket that users can access.

To achieve this, a best practice is to use a staging bucket as a control point before files go to production, combined with Amazon Macie’s data classification capabilities.

Creating a custom data identifier in Amazon Macie allows precise detection of product IDs starting with the specific UUID, which default managed identifiers will not detect.

By running a Macie sensitive data discovery job on the staging bucket, you can identify files containing these sensitive product IDs.

Only files without findings (i.e., files that do not contain unannounced product IDs) are copied to the production bucket, ensuring no sensitive information is exposed.This approach aligns with AWS best practices for data classification and staged deployment workflows, maximizing control and reducing risk.Using Macie on the production bucket directly (options B and D) risks exposing sensitive data before detection and deletion. Option C uses managed data identifiers, which will likely not detect the custom UUID prefix pattern.

Reference from AWS Official Documentation and Study Guide:

Amazon Macie Custom Data Identifiers:"You can create custom data identifiers in Amazon Macie to find sensitive data that is unique to your organization."(Amazon Macie User Guide)

Data Security Best Practices:"Use staging environments to inspect and sanitize data before moving it to production to reduce exposure risks."(AWS Security Best Practices)