Get Amazon DVA-C02 Exam Practice Questions - Real and Updated

Answer : A

This solution will meet the requirements by using Amazon CloudFront, which is a content delivery network (CDN) service that speeds up the delivery of web content and APIs to end users. The developer can configure the CloudFront cache, which is a set of edge locations that store copies of popular or recently accessed content close to the viewers. The developer can also update the application to return cached content based upon the default request headers, which are a set of HTTP headers that CloudFront automatically forwards to the origin server and uses to determine whether an object in an edge location is still valid. By caching the POST requests, the developer can optimize the API resources and reduce the latency for repeated queries. Option B is not optimal because it will override the cache method in the selected stage of API Gateway, which is not possible or effective as API Gateway does not support caching for POST methods by default. Option C is not optimal because it will save the latest request response in Lambda /tmp directory, which is a local storage space that is available for each Lambda function invocation, not a cache that can be shared across multiple invocations or requests. Option D is not optimal because it will save the latest request in AWS Systems Manager Parameter Store, which is a service that provides secure and scalable storage for configuration data and secrets, not a cache for API responses.

Answer : A

The requirements call for (1) standardized templates to define serverless infrastructure, (2) the ability to test locally before deployment, and (3) integrating deployment and infrastructure changes into an existing AWS CodePipeline workflow. AWS Serverless Application Model (AWS SAM) is designed specifically for serverless applications and extends CloudFormation with serverless-specific resources (such as AWS::Serverless::Function, APIs, event sources). SAM also provides the SAM CLI, which includes local testing capabilities (for example, sam local invoke and sam local start-api) that emulate Lambda and API Gateway behavior for rapid iteration before deployment.

Option A fits all requirements: create an AWS SAM template as the infrastructure definition and add pipeline stages that execute the necessary SAM CLI commands (commonly sam build and sam deploy, and optionally test commands) as part of the CI/CD process. This makes deployments repeatable and automated, ensures infrastructure changes are deployed in lockstep with application changes, and keeps everything governed by the existing CodePipeline.

Option D uses SAM but relies on a standalone script outside the pipeline, which conflicts with the requirement to incorporate infrastructure changes into the existing pipeline. Option C (plain CloudFormation) can define infrastructure, but it does not inherently provide the same streamlined local testing workflow that SAM CLI provides for serverless event sources and APIs. Option B is unrelated: Step Functions is an orchestration service and its definition language is not a general infrastructure templating and local-testing solution for serverless deployments.

Therefore, A is the correct strategy: use AWS SAM templates and integrate SAM CLI build/deploy steps into CodePipeline to automate deployments and support local testing while managing infrastructure as code.

Answer : B

Answer : A

Step-by-Step Breakdown:

Requirement Summary:

Get notified when EC2 CPU Utilization > 80%

Option A: CloudWatch Alarm with SNS

Correct and standard AWS practice

CloudWatch automatically collects EC2 metrics, including CPUUtilization.

You can set a CloudWatch Alarm with a threshold (80% in this case).

Then, trigger an SNS notification to email, SMS, Lambda, etc.

Option B: AWS CloudTrail alarm

Incorrect: CloudTrail logs API activity, not performance metrics.

It doesn't track metrics like CPU utilization.

Option C: Cron job on EC2 running --describe-instance-information

Incorrect: This doesn't give CPU usage.

Also inefficient, and polling is bad practice when CloudWatch already monitors this natively.

Option D: Lambda function querying CloudTrail for CPU usage

Incorrect and conceptually flawed.

CloudTrail does not store performance metrics; CloudWatch does.

CloudWatch Alarms for EC2: https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/AlarmThatSendsEmail.html

EC2 Metrics in CloudWatch: https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/viewing_metrics_with_cloudwatch.html

Amazon SNS Notification Setup: https://docs.aws.amazon.com/sns/latest/dg/sns-email-notifications.html

Answer : D

This solution will meet the requirements by using DynamoDB Accelerator (DAX), which is a fully managed, highly available, in-memory cache for DynamoDB that delivers up to a 10 times performance improvement - from milliseconds to microseconds - even at millions of requests per second. The developer can use DAX to cache the trading data that is used to process each trading request, which will reduce the data retrieval time with the least possible effort. Option A is not optimal because it will add local secondary indexes (LSIs) for the trading data, which may not improve the performance or reduce the latency of data retrieval, as LSIs are stored on the same partition as the base table and share the same provisioned throughput. Option B is not optimal because it will store the trading data in Amazon S3 and use S3 Transfer Acceleration, which is a feature that enables fast, easy, and secure transfers of files over long distances between S3 buckets and clients, not between DynamoDB and clients. Option C is not optimal because it will add retries with exponential backoff for DynamoDB queries, which is a strategy to handle transient errors by retrying failed requests with increasing delays, not by reducing data retrieval time.