Amazon Web ServicesAssociate levelDVA-C02Page 4 of 4

DVA-C02 exam dumps: questions 301 to 398 of 398

Page 4 of the free DVA-C02 question bank for the AWS Certified Developer - Associate exam. Questions 301 to 398 are listed below, the first 5 in full with answers and explanations. Back to page 1 for the exam overview and FAQ.

Question bank last updated December 2024

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Free DVA-C02 practice questions

Questions 301 to 305 of 398

Pick an answer before you open the explanation. Each question also has its own page with a permalink.

DVA-C02 Question 301

Single answer

You are tasked with deploying a serverless application on AWS that requires a Lambda function, an API Gateway endpoint, and an S3 bucket for static content. The team wants to use Infrastructure as Code (IaC) to manage the deployment. Which AWS service/tool is best suited for this use case, providing a simplified approach specifically tailored for serverless applications?

A
AWS CloudFormation
B
AWS Serverless Application Model (AWS SAM)
C
AWS Cloud Development Kit (AWS CDK)
D
AWS Amplify

Show answer and explanation

Correct answer: B

Explanation

AWS SAM (Serverless Application Model) is purpose-built for serverless application development and deployment. It extends AWS CloudFormation with simplified syntax and abstractions for common serverless resources, such as Lambda, API Gateway, and S3. While AWS CloudFormation and AWS CDK can also achieve the same result, SAM is specifically optimized for serverless use cases, making it the best choice in this scenario.

A. Incorrect.
AWS CloudFormation is a powerful IaC tool but does not provide serverless-specific abstractions out of the box. AWS SAM is better suited for this serverless use case.
B. Correct.
AWS SAM (Serverless Application Model) is specifically designed for building and deploying serverless applications, making it the ideal choice for this scenario.
C. Incorrect.
AWS CDK can be used to define serverless resources, but it requires writing code and does not provide the same level of serverless-specific simplifications as AWS SAM.
D. Incorrect.
AWS Amplify is focused on frontend and mobile application development and is not ideal for managing serverless backend resources like Lambda, API Gateway, or S3.

DVA-C02 Question 302

Single answer

A developer is tasked with deploying a serverless application on AWS. The application consists of a Lambda function, an API Gateway endpoint, and an Amazon DynamoDB table. The developer wants to automate the deployment process and manage infrastructure as code. Which AWS service or tool should the developer use to achieve this efficiently?

A
AWS CloudFormation
B
AWS Cloud Development Kit (AWS CDK)
C
AWS Serverless Application Model (AWS SAM)
D
AWS Amplify

Show answer and explanation

Correct answer: C

Explanation

AWS SAM (Serverless Application Model) is the best choice for this scenario because it is specifically designed to simplify the definition and deployment of serverless applications. It provides a higher-level abstraction for common serverless services like AWS Lambda, Amazon API Gateway, and Amazon DynamoDB, and integrates seamlessly with AWS CloudFormation for managing infrastructure as code. While other tools like AWS CloudFormation and AWS CDK can also achieve similar results, AWS SAM is purpose-built for serverless application use cases, making it the most efficient option in this scenario.

A. Incorrect.
AWS CloudFormation can be used to define infrastructure as code, but it is not specifically optimized for serverless applications. Using AWS SAM would be more efficient for this use case.
B. Incorrect.
AWS CDK is a powerful tool for defining cloud infrastructure using programming languages, but it is not purpose-built for serverless applications like AWS SAM.
C. Correct.
AWS SAM is specifically designed for serverless application development and deployment. It simplifies the process of defining, deploying, and managing serverless resources like Lambda, API Gateway, and DynamoDB.
D. Incorrect.
AWS Amplify is a development framework that simplifies front-end and mobile application development. It is not the best choice for managing serverless back-end infrastructure.

DVA-C02 Question 303

Single answer

You are developing a serverless application using AWS Lambda that processes images uploaded to an Amazon S3 bucket. You want a deployment strategy that allows you to define and manage the infrastructure as code, while also simplifying the creation, testing, and deployment of the Lambda function using pre-built templates. Which AWS tool would best meet these requirements?

A
AWS CloudFormation
B
AWS Cloud Development Kit (AWS CDK)
C
AWS Serverless Application Model (AWS SAM)
D
AWS Amplify

Show answer and explanation

Correct answer: C

Explanation

AWS SAM (Serverless Application Model) is the best tool for this scenario because it is tailored specifically for serverless applications. It extends AWS CloudFormation with simplified syntax for defining serverless resources and includes features for local testing, packaging, and deploying Lambda functions. While other tools like AWS CloudFormation and AWS CDK can handle serverless deployments, they do not provide the same level of simplicity and serverless-specific capabilities as AWS SAM.

A. Incorrect.
AWS CloudFormation allows you to define and provision infrastructure as code, but it does not provide serverless-specific templates or tools for simplifying the deployment of Lambda functions.
B. Incorrect.
AWS CDK allows you to define infrastructure as code using programming languages, but while it supports serverless architectures, it does not provide out-of-the-box serverless-specific features like AWS SAM.
C. Correct.
AWS SAM is specifically designed for serverless applications and provides pre-built templates, simplified deployment mechanisms, and testing capabilities for AWS Lambda and other serverless resources.
D. Incorrect.
AWS Amplify is intended for building and deploying full-stack web and mobile applications, and it is not specifically designed for serverless infrastructure management or deployment of Lambda functions.

DVA-C02 Question 304

Single answer

You are developing a serverless application using AWS Lambda. Your function has several dependencies from third-party Python libraries. The deployment package size exceeds the maximum Lambda deployment package size limit of 50 MB when compressed. Which approach should you take to successfully deploy your Lambda function?

A
Use AWS Lambda Layers to include your dependencies separately from the function code.
B
Compress the deployment package further using advanced compression algorithms to reduce the size.
C
Upload the deployment package to an S3 bucket and reference it directly in the Lambda function configuration.
D
Split the Lambda function into smaller functions to reduce the size of individual deployment packages.

Show answer and explanation

Correct answer: A

Explanation

When the deployment package size exceeds the Lambda limit, using AWS Lambda Layers is the recommended solution. Layers allow you to package and manage dependencies separately from your function code, reducing the size of the deployment package and enabling reusability across multiple functions.

A. Correct.
Correct. AWS Lambda Layers allow you to include external dependencies separately from your function's deployment package, helping you manage large dependencies effectively.
B. Incorrect.
Incorrect. While compression reduces size, it is unlikely to sufficiently reduce the size beyond AWS Lambda's limits if the package already exceeds the 50 MB compressed limit.
C. Incorrect.
Incorrect. AWS Lambda does not natively support referencing deployment packages directly from S3. The deployment package must still adhere to Lambda's size limits.
D. Incorrect.
Incorrect. Splitting the function may not address the core issue of large dependencies. This approach also increases architectural complexity unnecessarily.

DVA-C02 Question 305

Select 2

You are developing an AWS Lambda function to process image uploads. The function uses a custom library for image manipulation that is not included in the default AWS Lambda runtime. The library requires specific native dependencies. How should you package and deploy the Lambda function to ensure all dependencies are included and compatible?

A
Use the AWS Management Console to directly paste the function code and rely on Lambda to automatically install the required dependencies.
B
Package the function code and dependencies into a ZIP file locally, ensuring the dependencies are compiled for the Lambda runtime environment, and upload it to Lambda.
C
Use AWS Serverless Application Model (SAM) or AWS CloudFormation to package and deploy the Lambda function without explicitly handling the dependencies.
D
Use a Docker container image to package the function code and dependencies, ensuring they are compatible with the Lambda runtime environment, and deploy the image to Lambda.

Show answer and explanation

Correct answers: B, D

Explanation

AWS Lambda supports two main deployment packaging options: ZIP archives and container images. For ZIP deployments, you must ensure all dependencies, including native ones, are included and compatible with the Lambda runtime environment. For container image deployments, you can package your function code and dependencies into a Docker image, which provides more flexibility for custom dependencies and runtime compatibility. Both approaches are valid for handling native dependencies, but using the AWS Management Console or relying solely on SAM/CloudFormation does not handle dependency packaging.

A. Incorrect.
AWS Lambda does not automatically install dependencies for code pasted directly into the Management Console. Instead, you must package and include dependencies yourself.
B. Correct.
Packaging the function code and dependencies into a ZIP file locally is a valid method, but you must ensure the dependencies are compiled for the Lambda runtime environment (e.g., Amazon Linux).
C. Incorrect.
While SAM and CloudFormation can help deploy Lambda functions, they do not automatically package native dependencies or ensure compatibility with the runtime.
D. Correct.
Using a Docker container image is another valid approach, especially for functions with custom dependencies, as you can build the image to include all necessary libraries and ensure compatibility with the Lambda runtime environment.

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DVA-C02 practice questions 301 to 398 of 398

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