Amazon Web Services AWS Certified Associate DVA-C02 New Questions

AWS IAM role permissions are evaluated dynamically . According to AWS documentation, when an IAM role attached to an EC2 instance is updated, the updated permissions are available to applications running on that instance without requiring a restart . The EC2 instance retrieves temporary credentials through the instance metadata service, and those credentials are refreshed automatically.

In this scenario, the least disruptive approach is to update the IAM role policy to include the required s3:GetObject permission. Once the permission is added, the application can immediately retry access to the S3 bucket without restarting, stopping, or terminating the EC2 instance.

Terminating or restarting the instance (Options A and C) introduces unnecessary downtime and operational overhead. Modifying the S3 bucket policy (Option D) is unnecessary because the problem lies with missing role permissions, not bucket access configuration.

AWS best practices strongly recommend using IAM roles for EC2 and updating permissions dynamically to avoid service interruption. Therefore, simply adding the required permission to the role is the correct and most efficient solution.

S3Bucket and S3Key: These properties in a CloudFormation AWS::Lambda::Function resource specify the location of the function ' s code in S3.

Least Development Effort: This solution minimizes code changes, relying on CloudFormation to reference the existing S3 deployment package.

In the CloudFormation template, the developer should create a parameter with the list of approved EC2 instance types as AllowedValues. This way, users can select the instance type they want to use when launching the CloudFormation stack, but only from the approved list.

To monitor end-to-end requests and debug issues across microservices, you need distributed tracing. Among AWS tools, AWS X-Ray is specifically built for this use case.

Step-by-Step Breakdown:

Step 1: Understand the Requirement

The developer needs:

End-to-end request tracing across microservices

Debugging capability for performance issues or failures

This points directly to a distributed tracing solution rather than just logs or metrics.

Step 2: Evaluate the Options

Option A: Amazon CloudWatch

CloudWatch is powerful for metrics, logs, and alerts.

But it does not provide distributed tracing or request path visualization between microservices.

So, it ' s not sufficient alone for the requirement.

Option B: AWS CloudTrail

CloudTrail tracks API calls made through the AWS Management Console, CLI, SDKs.

It is meant for auditing and governance, not microservices request tracing.

Not suitable for debugging microservices interactions.

Option C: AWS X-Ray SDK with X-Ray service map

Purpose-built for distributed tracing

Automatically collects data about requests as they travel through your microservices

You can instrument your code with the AWS X-Ray SDK in Java, Node.js, Python, Go, .NET, etc.

Visualizes requests using a service map, showing latency, errors, and time spent in downstream services.

How it works:

Instrument each microservice using the AWS X-Ray SDK.

Use the SDK to trace requests, propagate trace headers across services.

The X-Ray daemon collects and sends trace data to the X-Ray service.

You can view the service map, see bottlenecks, error rates, etc.

Option D: AWS Health

AWS Health provides information on AWS service outages or account-level events.

It does not monitor your application or microservices health or request flows.

Correct Choice: C is the only option that meets the developer ' s requirement to monitor end-to-end request paths and debug issues in a microservices architecture.

AWS Developer References:

AWS X-Ray Documentation:

Instrumenting your application:

Viewing the Service Map:

Tracing Microservices with AWS X-Ray: