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Amazon AWS Certified Developer - Associate Sample Questions (Q802-Q807):

NEW QUESTION # 802
Two containerized microservices are hosted on Amazon EC2 ECS. The first microservice reads an Amazon RDS Aurora database instance, and the second microservice reads an Amazon DynamoDB table.
How can each microservice be granted the minimum privileges?

A. Set ECS_ENABLE_TASK_IAM ROLE to true on EC2 instance boot in the ECS agent configuration file. Run the first microservice with an IAM role for ECS tasks with read-only access for the Aurora database. Run the second microservice with an IAM role for ECS tasks with read- only access to DynamoDB.
B. Set ECS_ENABLE_TASK_IAM_ROLE to false on EC2 instance boot in ECS agent configuration file. Run the first microservice with an IAM role for ECS tasks with read-only access for the Aurora database. Run the second microservice with an IAM role for ECS tasks with read-only access to DynamoDB.
C. Set ECS_ENABLE_TASK_IAM_ROLE to true on EC2 instance boot in the ECS agent configuration file. Grant the instance profile role read-only access to the Aurora database and DynamoDB.
D. Set ECS_ENABLE_TASK_IAM ROLE to false on EC2 instance boot in the ECS agent configuration file. Grant the instance profile role read-only access to the Aurora database and DynamoDB.

Answer: A

NEW QUESTION # 803
A developer is designing a serverless application with two AWS Lambda functions to process photos. One Lambda function stores objects in an Amazon S3 bucket and stores the associated metadata in an Amazon DynamoDB table. The other Lambda function fetches the objects from the S3 bucket by using the metadata from the DynamoDB table. Both Lambda functions use the same Python library to perform complex computations and are approaching the quota for the maximum size of zipped deployment packages.
What should the developer do to reduce the size of the Lambda deployment packages with the LEAST operational overhead?

A. Package each Python library in its own .zip file archive. Deploy each Lambda function with its own copy of the library.
B. Combine the two Lambda functions into one Lambda function. Deploy the Lambda function as a single
.zip file archive.
C. Create a Lambda layer with the required Python library. Use the Lambda layer in both Lambda functions.
D. Download the Python library to an S3 bucket. Program the Lambda functions to reference the object URLs.

Answer: C

Explanation:
Explanation
AWS Lambda is a service that lets developers run code without provisioning or managing servers. Lambda layers are a distribution mechanism for libraries, custom runtimes, and other dependencies. The developer can create a Lambda layer with the required Python library and use the layer in both Lambda functions. This will reduce the size of the Lambda deployment packages and avoid reaching the quota for the maximum size of zipped deployment packages. The developer can also benefit from using layers to manage dependencies separately from function code.
References:
[What Is AWS Lambda? - AWS Lambda]
[AWS Lambda Layers - AWS Lambda]

NEW QUESTION # 804
A company wants to ensure that only one user from its Admin group has the permanent right to delete an Amazon EC2 resource. The company must not modify the existing Admin group policy.
What should a developer use to meet these requirements?

A. AWS STS
B. IAM trust relationship
C. AWS managed policy
D. Inline policy

Answer: D

Explanation:
An inline IAM policy is directly attached to a specific IAM user, group, or role and applies only to that principal. AWS documentation states that inline policies are useful when permissions should be tightly scoped and not reused.
In this scenario, the Admin group policy cannot be changed, but one specific user needs permanent delete permissions. Attaching an inline policy directly to that user grants the required permissions without impacting other Admin users.
AWS managed policies (Option A) are reusable and not suitable for user-specific access. IAM trust relationships (Option C) control role assumption, not resource permissions. AWS STS (Option D) provides temporary credentials, not permanent access.
Therefore, an inline policy is the correct solution.

NEW QUESTION # 805
A developer is automating a new application deployment with AWS SAM. The new application has one AWS Lambda function and one Amazon S3 bucket. The Lambda function must access the S3 bucket to only read objects.
How should the developer configure AWS SAM to grant the necessary read permission to the S3 bucket?

A. Add the S3ReadPolicy template to the Lambda function's execution role.
B. Add a custom S3 bucket policy to the Lambda function.
C. Create an Amazon SQS topic for only S3 object reads. Reference the topic in the template.
D. Reference a second Lambda authorizer function.

Answer: A

Explanation:
Step-by-Step Breakdown:
Requirement Summary:
* UseAWS SAMto deploy:
* 1 Lambda Function
* 1 S3 Bucket
* Lambda needsread-only accessto the S3 bucket
* Solution must be expressed viaAWS SAM template
Option A: Reference a second Lambda authorizer function
* #Incorrect: Lambda authorizers are used inAPI Gateway for authentication, not for granting S3 permissions.
Option B: Add a custom S3 bucket policy to the Lambda function
* #Incorrect: Bucket policiescontrol who can access the bucket, not what the Lambda function can do.
* The permission must be granted to the Lambda'sIAM execution role.
Option C: Create an Amazon SQS topic for only S3 object reads
* #Incorrect: SQS cannot read objects from S3 and is not relevant to this scenario.
Option D: Add the S3ReadPolicy template to the Lambda function's execution role
* #Correct: AWS SAM providesmanaged policy templateslike AmazonS3ReadOnlyAccess and shortcuts like S3ReadPolicy.
* You can apply these to the Lambda's execution role using the Policies: section in your SAM template.
Example SAM YAML:
yaml
CopyEdit
Resources:
MyFunction:
Type: AWS::Serverless::Function
Properties:
CodeUri: my-code/
Handler: app.handler
Runtime: python3.11
Policies:
- S3ReadPolicy:
BucketName: !Ref MyBucket
MyBucket:
Type: AWS::S3::Bucket
Properties:
BucketName: my-personal-bucket-name
* SAM Policy Templates:https://docs.aws.amazon.com/serverless-application-model/latest
/developerguide/serverless-policy-templates.html
* Example using S3ReadPolicy:https://docs.aws.amazon.com/serverless-application-model/latest
/developerguide/serverless-policy-templates.html#s3-readpolicy

NEW QUESTION # 806
A developer is trying get data from an Amazon DynamoDB table called demoman-table. The developer configured the AWS CLI to use a specific IAM use's credentials and ran the following command.

The command returned errors and no rows were returned.
What is the MOST likely cause of these issues?

A. The developer needs to log a ticket with AWS Support to enable access to the demoman-table
B. Amazon DynamoOB cannot be accessed from the AWS CLI and needs to called via the REST API
C. The IAM user needs an associated policy with read access to demoman-table
D. The command is incorrect; it should be rewritten to use put-item with a string argument

Answer: C

Explanation:
This solution will most likely solve the issues because it will grant the IAM user the necessary permission to access the DynamoDB table using the AWS CLI command. The error message indicates that the IAM user does not have sufficient access rights to perform the scan operation on the table. Option A is not optimal because it will change the command to use put-item instead of scan, which will not achieve the desired result of getting data from the table. Option B is not optimal because it will involve contacting AWS Support, which may not be necessary or efficient for this issue. Option C is not optimal because it will state that DynamoDB cannot be accessed from the AWS CLI, which is incorrect as DynamoDB supports AWS CLI commands.

NEW QUESTION # 807
......

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