Pass the Amazon Web Services AWS Certified Associate DVA-C02 Questions and answers with CertsForce

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

AWS CloudFormation is a service that enables developers to model and provision AWS resources using templates. The developer can use the following steps to avoid accidental database deletion in the future:

Set up AWS CodeDeploy to deploy the most recent version of the application at runtime. This will ensure that the application code is always up to date and does not depend on the AMI.

Remove any commands that perform operating system patching from the UserData script. This will reduce the time that the UserData script takes to run and speed up the instance launch process.

The correct answer is D because the current DynamoDB table design is causing a hot partition problem. The table uses order_date as the partition key, which means that during peak ordering periods, a very large number of writes are likely targeting the same partition key value for the current date. In DynamoDB, write throttling often occurs when traffic is not evenly distributed across partition keys, even when the table uses on-demand mode . On-demand capacity can automatically scale, but it still depends on proper key distribution to avoid concentrated activity on a small number of partitions.

By changing the partition key to customer_id and using order_id as the sort key, writes will be spread across many customers instead of being concentrated on a small number of date values. This creates a more balanced write pattern and better aligns with DynamoDB best practices for high-scale workloads. DynamoDB documentation emphasizes choosing partition keys with high cardinality and even request distribution to avoid throttling and improve performance.

Option A is not a good design because a sequential partition key can still create uneven access patterns and usually does not support meaningful access requirements. Option B is not the best answer because simply increasing capacity does not fix a poor partition key design; hot partitions can still throttle. Option C is unnecessary because the issue is not that DynamoDB is the wrong service, but that the table schema needs redesign.

Therefore, the best solution is to refactor the key schema so that writes distribute more evenly across partitions, which is exactly what D achieves.

This solution allows the CloudFormation service role to access the S3 bucket from any account, as long as it has the S3 GetObject permission. The bucket policy grants access to any principal with the GetObject permission, which is the least privilege needed to deploy the Lambda code. This is more secure than granting ListBucket permission, which is not required for deploying Lambda code, or using a service-based link, which is not supported for Lambda functions.

The requirement is real-time UI updates “immediately” without refreshing the dashboard. The most operationally efficient AWS-native method is to use API Gateway WebSocket APIs to push updates from the backend to the browser.

With option A, the client establishes a WebSocket connection and receives a connection ID. The application can associate uploads (or job IDs) with that connection ID (commonly storing the mapping in DynamoDB or another datastore). When the long-running validation finishes, the backend uses the WebSocket management API to post a message to the specific connection ID, and the browser updates the UI dynamically. This eliminates polling/refresh and scales well without managing servers.

Option B requires running and maintaining an EC2-hosted WebSocket server (patching, scaling, uptime), which is more operational overhead.

Option C uses email, which is not immediate UI updating and doesn’t update the dashboard without user action.

Option D is not appropriate: SNS does not directly push notifications to a web browser in a standard way, and it adds unnecessary complexity.

Therefore, using API Gateway WebSocket to push validation results to connected clients is the most operationally efficient solution.

Amazon API Gateway is a service that enables developers to create, publish, maintain, monitor, and secure APIs at any scale. The developer can enable API caching in API Gateway to cache responses from the backend integration point for a specified time-to-live (TTL) period. This can improve the responsiveness of the APIs by reducing the number of calls made to the backend service.

This is a classic cross-account S3 access requirement: EC2 instances in Account A must read from a private S3 bucket in Account B without making the bucket public.

The correct pattern is to grant access using IAM + S3 bucket policy while keeping the bucket private. In Account B, you create an IAM role that has the necessary S3 read permissions (such as s3:GetObject and potentially s3:ListBucket depending on access needs). That is Option A.

However, permissions on the role alone are not sufficient, because the S3 bucket is in a different account and is private by default. AWS requires that the bucket owner explicitly grants access to the external principal. This is done by adding a bucket policy in Account B that allows the principal (either the role in Account A or a role session via STS) to access the bucket objects. That is Option D.

Option B is not correct in the “select two” sense because adding permissions to Account A’s instance profile role does not, by itself, grant access to a bucket owned by Account B. You still need the bucket policy or another resource-based policy from the bucket owner.

Option C violates the requirement (“without exposing the S3 bucket to anyone else”). Making the bucket public is unnecessary and insecure.

Option E is incorrect because a trust policy controls who can assume a role (sts:AssumeRole), not what S3 permissions the role has. Also, trust policies do not grant s3:Get* access.

Therefore, create an IAM role with S3 read permissions in Account B and grant access via the Account B bucket policy.

Lambda Destinations on Failure: Allow routing asynchronous function invocations to specified resources (like another Lambda function) upon failure.

Error Handling: The error-handling Lambda receives details about the failure, enabling logging and custom actions.

Direct Integration: This solution leverages native Lambda functionality for a simpler implementation.

Requirement Summary:

Prevent unauthorized code changes in AWS Lambda

Ensure only trusted code is deployed

AWS Lambda supports Code Signing:

You can configure code signing in Lambda using AWS Signer

Packages must be digitally signed and verified against the signing profile

Rejects unauthorized/modified packages automatically

Evaluate Options:

A. Trusted code option in CodeDeploy

No such feature exists for Lambda

CodeDeploy is more for EC2/On-Prem/Containers, not Lambda code signing

B. Define code signing config + use AWS Signer

This is exactly how AWS enforces trusted code deployment

Attach a code signing configuration to the Lambda function

Use AWS Signer to digitally sign deployment packages

C. Link to KMS to sign code

KMS is not used to sign Lambda packages

KMS is for data encryption, not application code integrity

D. Set KmsKeyArn

This configures data encryption, not code signing

Lambda code signing: https://docs.aws.amazon.com/lambda/latest/dg/configuration-codesigning.html

AWS Signer overview: https://docs.aws.amazon.com/signer/latest/developerguide/what-is-signer.html