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

The problem has two distinct requirements: securely managing rotating external API credentials and encrypting CodeBuild artifacts with a specific KMS key.

For credentials that must be reset each month and are sensitive, AWS Secrets Manager is the appropriate service, not Parameter Store. Secrets Manager provides built-in support for secret rotation, versioning, access control, and auditability. The external API credentials can be updated monthly either manually or via an automated rotation Lambda. CodeBuild can read the secret at build time by assuming an IAM role that allows secretsmanager:GetSecretValue .

To encrypt CodeBuild outputs, the correct pattern is to set the CODEBUILD_KMS_KEY_ID environment variable (or CodeBuild project setting) to the desired KMS key. The CodeBuild IAM service role must be granted kms:Encrypt , kms:Decrypt , and related actions on that KMS key via the key policy or IAM policy. This ensures build artifacts and logs are encrypted using the specified customer managed key.

Option C captures both requirements precisely: store credentials in Secrets Manager and update the KMS key policy for the CodeBuild role , not the CodePipeline role. Options A and B misuse Parameter Store and/or the wrong IAM principal. Option D updates the wrong role and does not connect the KMS key to CodeBuild’s artifact encryption.

To meet the requirements, the company needs to create a solution that alerts the Senior Manager when the creation of resources approaches the service limits for the account with the least amount of development effort. The company can use AWS Trusted Advisor, which is a service that provides best practice recommendations for cost optimization, performance, security, and service limits. The company can deploy an AWS Lambda function that refreshes Trusted Advisor checks, and configure an Amazon CloudWatch Events rule to run the Lambda function periodically. This will ensure that Trusted Advisor checks are up to date and reflect the current state of the account. The company can then create another CloudWatch Events rule with an event pattern matching Trusted Advisor events and a target Lambda function. The event pattern can filter for events related to service limit checks and their status. The target Lambda function can notify the Senior Manager via a third-party API call if the event indicates that the account is approaching or exceeding a service limit.

The condition is deterministic: maximum CPU utilization must be below 2% for the previous 24 one-hour periods. That requires a static threshold, not anomaly detection. Anomaly detection learns a normal band from historical behavior, which is useful for unusual patterns but not for a fixed business definition of “idle.” CloudWatch alarms use “Datapoints to Alarm” as an M-out-of-N evaluation model, so 24 out of 24 means all 24 hourly datapoints must breach the threshold. AWS also documents idle-instance alarm examples based on CPU utilization staying below a threshold for 24 consecutive periods. Option D would alarm if only one hour was below 2%, which is far too sensitive. Options A and C use the wrong threshold type.

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