Amazon Web Services Updated DVA-C02 Exam Questions and Answers by tomos

AWS CodeBuild supports parallel test execution through batch builds and multiple compute environments. This feature allows a single CodeBuild project to divide test workloads across multiple isolated environments that run concurrently. Each environment executes a subset of the test suite, significantly reducing total build time.

AWS documentation emphasizes using native CodeBuild capabilities to minimize operational complexity. Parallel execution eliminates the need to manually manage infrastructure, test orchestration logic, or EC2 fleets. CodeBuild automatically provisions and terminates build environments, scales as needed, and integrates seamlessly with CI/CD pipelines.

Options A and D require manual coordination and infrastructure management, increasing operational overhead. Option C does not address the performance problem.

Therefore, using CodeBuild’s parallel compute environments is the most efficient and AWS-recommended approach.

The destination bucket is in the development account, so the destination encryption key should also be in the development account. A customer managed KMS key is required because its key policy can be edited to allow the production account to use it for encryption during the copy operation. AWS managed keys cannot have their key policies modified to grant cross-account access in the same way. Replicating or copying a KMS key from production is not the correct model for this requirement; KMS keys are regional resources and access is controlled through key policies and IAM permissions. The best design is therefore a new customer managed key in the development account with a key policy that permits the production account to use the key for the copy.

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A Lambda layer is the correct operationally efficient solution because layers are specifically designed to package reusable code, libraries, custom runtimes, or configuration files separately from function code. The developer can publish the shared .zip archive as a layer version and attach that layer to multiple Lambda functions. This avoids copying the same dependency into every deployment package and centralizes dependency management. Amazon S3 alone does not create an importable runtime dependency path for Lambda. A separate Lambda function would add synchronous invocation latency and coupling. A container image could work for container-based functions, but it is heavier and unnecessary when the code is already packaged as a .zip dependency. AWS documentation states that layers are used to separate reusable dependencies from function code and add them to functions. ( AWS Documentation )

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