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

Amazon API Gateway is a service that enables developers to create, publish, maintain, monitor, and secure APIs at any scale. The developer can define a development stage on the API Gateway API and instruct the other developers to point the endpoints to the development stage. This way, the developer can provide beta access to the new version of the API without affecting customers who use the production stage. This solution will meet the requirements with the least operational overhead.

AWS Elastic Beanstalk supports several deployment policies, and in this case, the requirement is to forward a specific percentage of traffic to the new version without causing downtime. The Traffic-splitting deployment policy is the most appropriate choice.

Traffic-splitting Deployment: This deployment method allows you to gradually shift a specified percentage of incoming traffic from the old environment version to the new one. During the evaluation period, if any issues are detected, the traffic can be redirected back to the old version.

No Downtime: This method ensures no downtime since both versions of the application run concurrently, and traffic is split between them.

Alternatives:

Rolling deployments (Option A): These gradually replace instances but may result in partial downtime if some instances fail during deployment.

In-place deployments (Option C): In-place deployments replace instances without creating new ones, which can lead to downtime.

Immutable deployments (Option D): While this ensures no downtime by creating entirely new instances, it doesn ' t provide traffic splitting during the evaluation phase.

Elastic Beanstalk Deployment Policies

The safest way to prevent cross-tenant data leakage during processing is to enforce tenant isolation at the authorization layer , not only in application logic. AWS supports this with ABAC (attribute-based access control) using IAM principal/session tags and policy condition keys. The goal is to ensure that, for each invocation, the function can access only the S3 prefix and DynamoDB items that match the tenant being processed.

First, the Lambda execution role should be permitted to assume a dedicated data access role (B). This creates a clear separation: the execution role has minimal base permissions and can obtain tenant-scoped permissions only by assuming the data role.

Second, the Lambda function should assume that data access role with the tenant name as a session tag and then use the temporary credentials for all S3/DynamoDB calls (F). Session tagging ties the caller’s identity attributes (tenant) to the credentials used for data access.

Third, attach policies to the data access role that restrict access using conditions that compare the session tag to the requested resource attributes (C). For S3, policies can restrict access to object ARNs like arn:aws:s3:::bucket/${aws:PrincipalTag/tenant}/*. For DynamoDB, policies can restrict access by partition key using dynamodb:LeadingKeys so the role can read/write only items whose partition key equals the tenant tag. This ensures that even if the function code has a bug or receives unexpected input, AWS authorization prevents it from reading or writing another tenant’s data.

Option A is not required as stated; you typically need permission to pass session tags (and the trust/policy must allow tagging), but the key actions here are: enable assume role (B), enforce tag-based data policies (C), and actually assume the role with tenant tag (F). Option D is not generally the primary control for DynamoDB; the standard enforcement is via IAM identity policies (and dynamodb:LeadingKeys). Option E (RCP) is an AWS Organizations guardrail and is not necessary for this single-application isolation pattern.