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The DVA-C02 certification exam evaluates a candidate's ability to design, develop, and deploy scalable and fault-tolerant applications on AWS. DVA-C02 exam covers a wide range of topics, including AWS compute, storage, database, networking, security, and developer tools. DVA-C02 Exam also tests the candidate's knowledge of AWS services such as AWS Lambda, AWS Elastic Beanstalk, AWS CodePipeline, AWS CloudFormation, and AWS CloudTrail.
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The DVA-C02 exam is an associate-level certification, which means that candidates should have a good understanding of AWS services and be able to demonstrate their knowledge of AWS best practices. DVA-C02 exam covers a wide range of topics, including AWS core services, security, and deployment. It also covers topics such as how to design and develop scalable AWS applications, how to troubleshoot issues, and how to optimize application performance.
The DVA-C02 Exam is designed to assess the developer's ability to develop, deploy, and maintain AWS-based applications using AWS SDKs, APIs, and AWS CLI. DVA-C02 exam is also designed to test the developer's understanding of AWS services such as AWS Lambda, Amazon Elastic Beanstalk, Amazon EC2, and Amazon RDS. DVA-C02 exam requires the candidate to have a deep understanding of AWS services and how they can be used to create robust and scalable applications.
NEW QUESTION # 648
A developer needs to automate deployments for a serverless, event-based workload. The developer needs to create standardized templates to define the infrastructure and to test the functionality of the workload locally before deployment.
The developer already uses a pipeline in AWS CodePipeline. The developer needs to incorporate any other infrastructure changes into the existing pipeline.
Which solution will meet these requirements?
Answer: D
Explanation:
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.
NEW QUESTION # 649
A company uses AWS CloudFormation to deploy an application that uses an Amazon API Gateway REST API with AWS Lambda function integration. The application uses Amazon DynamoDB for data persistence.
The application has three stages: development, testing, and production. Each stage uses its own DynamoDB table. The company has encountered unexpected issues when promoting changes to the production stage. A developer needs to route 20% of the traffic to the new production stage API with the next production release.
The developer needs to route the remaining 80% of the traffic to the existing production stage. The solution must minimize the number of errors that any single customer experiences. Which approach should the developer take to meet these requirements?
Answer: A
Explanation:
The correct answer is D because Amazon API Gateway REST APIs support canary deployments for stages , which allow a developer to send a controlled percentage of production traffic to a new API deployment while the rest of the traffic continues to use the current deployment. Setting the canary percentage to 20% directly satisfies the requirement to route 20% of traffic to the new release and 80% to the existing production release.
This is the best approach because API Gateway canary deployments are specifically designed to reduce the blast radius of new releases in production. AWS documentation explains that canary releases enable testing of a new deployment with a subset of client traffic before promoting it fully. Since the canary runs within the same production stage , this minimizes the number of errors experienced by any single customer compared to less controlled alternatives. It is also cleaner than routing users to the testing stage, because a testing stage often has different configuration, data, or dependencies and is not intended to serve production traffic.
Option A is incorrect because partially deploying only some planned changes is not a safe traffic-routing strategy. Option B is incorrect because weighted Route 53 routing between production and testing stages does not provide the same controlled deployment semantics and may send the same customer to inconsistent backends. Option C is incorrect because placing an ALB in front of API Gateway is unnecessary and not the intended deployment pattern for API Gateway stage traffic shifting.
Therefore, API Gateway stage canary settings are the AWS-native solution that best meets the requirement.
NEW QUESTION # 650
A developer is creating a new application that will be accessed by users through an API created using Amazon API Gateway. The users need to be authenticated by a third-party Security Assertion Markup Language (SAML) identity provider. Once authenticated, users will need access to other AWS services, such as Amazon S3 and Amazon DynamoDB.
How can these requirements be met?
Answer: A
Explanation:
The requirement has two parts: (1) authenticate users with a third-party SAML IdP, and (2) after authentication, allow those users to access AWS services like Amazon S3 and DynamoDB. The AWS pattern for this is to federate the external identity into AWS and then exchange that identity for temporary AWS credentials.
Amazon Cognito identity pools are designed to provide AWS credentials to authenticated users (via AWS STS) so the users can call AWS services directly or through an application backend. Identity pools support federation with external identity providers, including SAML 2.0. When a user authenticates with the third- party SAML IdP, the identity pool can accept the SAML assertion, map the user to an IAM role, and return temporary, scoped credentials (AccessKeyId/SecretAccessKey/SessionToken) associated with that role.
Those credentials can be restricted using IAM policies to only the required S3 buckets, DynamoDB tables, and actions, satisfying least privilege.
Option A is incorrect because a Cognito user pool is primarily a user directory and OIDC/OAuth provider for application authentication; while user pools can integrate with SAML IdPs for federation, user pools alone do not directly issue AWS service credentials. The key requirement here is access to S3/DynamoDB, which is the role of an identity pool. Option C is not appropriate because IAM is not intended to provide end-user sign- up/sign-in for external users; it is for AWS identities and permissions. Option D is unrelated: CloudFront signed URLs control access to CloudFront-distributed content and do not authenticate users with SAML or provide AWS credentials.
Therefore, B meets both requirements: federate SAML authentication through a Cognito identity pool and provide temporary AWS credentials for accessing S3 and DynamoDB.
NEW QUESTION # 651
A developer is troubleshooting an application mat uses Amazon DynamoDB in the uswest-2 Region. The application is deployed to an Amazon EC2 instance. The application requires read-only permissions to a table that is named Cars The EC2 instance has an attached IAM role that contains the following IAM policy.
When the application tries to read from the Cars table, an Access Denied error occurs.
How can the developer resolve this error?
Answer: A
Explanation:
Explanation
https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/access-control-overview.html#access-con
NEW QUESTION # 652
A developer needs to build an AWS CloudFormation template that self-populates the AWS Region variable that deploys the CloudFormation template What is the MOST operationally efficient way to determine the Region in which the template is being deployed?
Answer: B
Explanation:
* Pseudo Parameters: CloudFormation provides pseudo parameters that reference runtime context, including the current AWS Region.
* Operational Efficiency: The AWS::Region pseudo parameter offers the most direct and self-contained way to obtain the Region dynamically within the template.
References:
* CloudFormation Pseudo Parameters: https://docs.aws.amazon.com/AWSCloudFormation/latest
/UserGuide/pseudo-parameter-reference.html
NEW QUESTION # 653
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