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

Why Option B is Correct:Setting the visibility timeout ensures that once a message is being processed, it is temporarily hidden from other consumers. The Lambda function must delete processed messages to avoid re-processing when the visibility timeout expires.

Why Other Options are Incorrect:

Option A:Message retention affects how long messages stay in the queue, not how they are processed.

Option C:Receive message wait time optimizes long polling but does not prevent re-processing.

Option D:Delivery delay introduces latency for new messages and does not address message re-processing.

AWS Documentation References:

Using SQS Visibility Timeout

Tracing Distributed Systems: AWS X-Ray is designed to trace requests across services, helping identify bottlenecks in distributed applications like this one.

No Code Changes: Enabling X-Ray tracing often requires minimal code changes, meeting the requirement.

Identifying Bottlenecks: Analyzing X-Ray traces and logs will reveal latency in communications between different AWS services, leading to the high duration time.

Why Option B is Correct:The RetainExceptOnCreate deletion policy ensures that the IAM user is retained after successfulstack creation but is deleted if the stack creation fails or rolls back. This meets both requirements.

Why Other Options are Incorrect:

Option A:The Retain policy retains the resource regardless of stack status and does not delete the IAM user upon rollback.

Option C:Updating the service role for termination protection does not address the specific deletion behavior for the IAM user.

Option D:Stack policy controls updates, not resource deletion behavior during rollbacks.

AWS Documentation References:

CloudFormation DeletionPolicy Attribute

The correct answer is A. Add a configuration file in TOML format to group configuration entries to every environment. Add a table for each testing and staging environment. Deploy updates to the environments by using the sam deploy command and the --config-env flag that corresponds to the each environment.

A. Add a configuration file in TOML format to group configuration entries to every environment. Add a table for each testing and staging environment. Deploy updates to the environments by using the sam deploy command and the --config-env flag that corresponds to the each environment. This is correct.This solution will meet the requirements with the least development effort, because it uses a feature of the AWS SAM CLI that supports a project-level configuration file that can be used to configureAWS SAM CLI command parameter values1.The configuration file can have multiple environments, each with its own set of parameter values, such as stack name, region, capabilities, and more2.The developer can use the --config-env option to specify which environment to use when deploying the application3. This way, the developer can avoid creating multiple templates or scripts, or manually overriding parameters for each environment.

B. Create additional AWS SAM templates for each testing and staging environment. Write a custom shell script that uses the sam deploy command and the --template-file flag to deploy updates to the environments. This is incorrect. This solution will not meet the requirements with the least development effort, because it requires creating and maintaining multiple templates and scripts for each environment. This can introduce duplication, inconsistency, and complexity in the deployment process.

C. Create one AWS SAM configuration file that has default parameters. Perform updates to the testing and staging environments by using the —parameter-overrides flag in the AWS SAM CLI and the parameters that the updates will override. This is incorrect. This solution will not meet the requirements with the least development effort, because it requires manually specifying and overriding parameters for each environment every time the developer deploys the application. This can be error-prone, tedious, and inefficient.

D. Use the existing AWS SAM template. Add additional parameters to configure specific attributes for the serverless function and database table resources that are in eachenvironment. Deploy updates to the testing and staging environments by using the sam deploy command. This is incorrect. This solution will not meet the requirements with the least development effort, because it requires modifying the existing template and adding complexity to the resource definitions for each environment. This can also make it difficult to manage and track changes across different environments.

This solution allows the Lambda function to be invoked by the DynamoDB stream whenever updates are made to items in the DynamoDB table. Event source mapping is a feature of Lambda that enables a function to be triggered by an event source, such as a DynamoDB stream, an Amazon Kinesis stream, or an Amazon Simple Queue Service (SQS) queue. The developer can configure event source mapping for the Lambda function using the AWS Management Console, the AWS CLI, or the AWS SDKs. Changing the StreamViewType parameter value to NEW_AND_OLD_IMAGES for the DynamoDB table will not affect the invocation of the Lambda function, but only change the information that is written to the stream record. Mapping an Amazon Simple Notification Service (Amazon SNS) topic to the DynamoDB stream will not invoke the Lambda function directly, but require an additional subscription from the Lambda function to the SNS topic. Increasing the maximum runtime (timeout) setting of the Lambda function will not affect the invocation of the Lambda function, but only change how long the function can run before it is terminated.

This solution will limit the ability to download a premier content file in the S3 bucket to paid subscribers only because it uses a pre-signed object URL that grants temporary access to an S3 object for a specified duration. The pre-signed object URL can be generated by the company’s website when a paid subscriber requests a download, and can be verified by Amazon S3 using the signature in the URL. Option A is not optimal because it will allow anyone to download the content from the S3 bucket without verifying their subscription status. Option C is not optimal because it will require additional steps and costs to configure multi-factor authentication for accessing the S3 bucket objects, which may not be feasible or user-friendly for paid subscribers. Option D is not optimal because it will not prevent non-paying website visitors from accessing the S3 bucket objects, but only encrypt them at rest.

Requirement Summary:

Simple REST endpointforweather data

Light backend usage (POC, testing)

Wantscachingsupport to reduce backend calls

Must becost-effective

Evaluate Options:

✅B: Lambda + API Gateway + SAM

✅Serverless = No idle costs

✅API Gateway canenable caching(response caching at endpoint level)

✅SAM makes deployment simple and repeatable

✅Perfect for low-traffic testing

A: EKS + API Gateway

❌High overhead

Not cost-effective for POC/testing

C: ECS + API Gateway

❌Similar to A: Container orchestration not needed for light REST endpoint

D: Elastic Beanstalk + ALB + Lambda

❌Overly complex and does not directly expose Lambda

Beanstalk better suited for full apps, not small REST functions

AWS SAM:https://docs.aws.amazon.com/serverless-application-model/latest/developerguide/what-is-sam.html

API Gateway caching:https://docs.aws.amazon.com/apigateway/latest/developerguide/api-gateway-caching.html

Serverless Best Practices:https://docs.aws.amazon.com/lambda/latest/dg/best-practices.html

Requirement Summary:

Deployserverless applicationusing:

API Gateway

AWS Lambda

Needdev, test, and prodenvironments

Wantleast development effort

Evaluate Options:

Option A: API Gateway stage variables + Lambda aliases

✅Most efficient and scalable

API Gateway supportsstage variables(like env)

Lambda supportsaliases(e.g., dev, test, prod)

You can configureeach stage to point to a different aliasof the same function version

Enablesversioning,isolation, andlow effort management

Option B: Use Amazon ECS

❌Overkill for a serverless setup

ECS is container-based, not serverless

Introduces unnecessary complexity

Option C: Duplicate code for each environment

❌High operational overhead and poor maintainability

Option D: Use Elastic Beanstalk

❌Not applicable: Elastic Beanstalk is for traditional app hosting, not optimal forLambda + API Gateway

Lambda Aliases:https://docs.aws.amazon.com/lambda/latest/dg/configuration-aliases.html

API Gateway Stage Variables:https://docs.aws.amazon.com/apigateway/latest/developerguide/stage-variables.html

Why Option B is Correct:RDS Proxy manages database connections efficiently, reducing overhead on the RDS instance and mitigating "too many connections" errors.

Why Other Options are Incorrect:

Option A:DAX is for DynamoDB, not RDS.

Option C:Migration to PostgreSQL does not address the current issue.

Option D:ElastiCache is useful for caching but does not solve connection pool issues.

AWS Documentation References:

Amazon RDS Proxy