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

This solution meets the requirements most cost-effectively because it optimizes the photos on demand and caches them for future requests. Lambda@Edge allows the developer to run Lambda functions at AWS locations closer to viewers, which can reduce latency and improve photo quality. The developer can create a Lambda@Edge function that uses the GET parameters from each request to optimize the photos with the required dimensions and resolutions and returns them as a response. The function can also store a copy of the processed photos on Amazon S3 for subsequent requests, which can reduce processing time and costs. Using S3 Batch Operations to create new variants of the photos will incur additional storage costs and may not cover all possible dimensions and resolutions. Creating a dynamic CloudFront origin or a Lambda@Edge function to route requests to corresponding photo variants will require maintaining a mapping of device types and photo variants, which can be complex and error-prone.

The IAM policy shown in the image is a resource-based policy that grants or denies access to an S3 bucket based on certain conditions. The first statement allows access to any S3 action on any object in the “DOC-EXAMPLE-BUCKET” bucket when the request is made over HTTPS (the value of aws:SecureTransport is true). The second statement denies access to the s3:GetObject and s3:PutObject actions on any object in the “DOC-EXAMPLE-BUCKET/secrets” prefix when the request is made over HTTP (the value of aws:SecureTransport is false). Therefore, the policy allows access on all objects in the “DOC-EXAMPLE-BUCKET” bucket except on objects that start with “secrets”. Reference: Using IAM policies forAmazon S3

Step-by-Step Breakdown:

Requirement Summary:

Get notified when EC2CPU Utilization > 80%

Option A: CloudWatch Alarm with SNS

✅Correct and standard AWS practice

CloudWatch automatically collectsEC2 metrics, including CPUUtilization.

You can set aCloudWatch Alarmwith a threshold (80% in this case).

Then,trigger an SNS notificationto email, SMS, Lambda, etc.

Option B: AWS CloudTrail alarm

❌Incorrect: CloudTrail logsAPI 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

Requirement Summary:

Multi-tier app on EC2 + Aurora PostgreSQL

Must comply withleast privilegeandsecurity policies

Need to managecredentials and API keys securely

Must supportkey rotation on demand

Evaluate Options:

✅A. Secrets Manager + AWS managed KMS keys

✅Best practice for secure secret storage

✅Supportsauto rotation

✅Uses AWS SDK to fetch at runtime (secure, avoids hardcoding)

AWS managed keys arerotated automaticallyandeasier to manage

B. Secrets Manager + customer managed keys

⚠️Also valid, butadds complexity

Since the question asks forLEAST development effort, AWS-managed keys are preferred

C. Store secrets in code

❌Violates all security best practices

D. Use SSM Parameter Store + AWS managed keys

⚠️Possible, butSecrets Manageris preferred when rotation is needed

Parameter Store doesnot natively rotate secrets

Secrets Manager:https://docs.aws.amazon.com/secretsmanager/latest/userguide/intro.html

Automatic key rotation:https://docs.aws.amazon.com/kms/latest/developerguide/rotate-keys.html

Best practices for secret management:https://docs.aws.amazon.com/secretsmanager/latest/userguide/best-practices.html

S3Bucket and S3Key: These properties in a CloudFormation AWS::Lambda::Function resource specify the location of the function's code in S3.

Least Development Effort: This solution minimizes code changes, relying on CloudFormation to reference the existing S3 deployment package.

Comprehensive Detailed and Lengthy Step-by-Step Explanation with All AWS Developer References:

1. Understanding the Use Case:

The API needs to:

Generate responses without backend integrations:This indicates the use of mock responses for testing.

Be used by multiple internal teams during development.

Minimize operational overhead.

2. Key Features of Amazon API Gateway:

REST APIs:Fully managed API Gateway option that supports advanced capabilities like mock integrations, request/response transformation, and more.

HTTP APIs:Lightweight option for building APIs quickly. It supports fewer features but has lower operational complexity and cost.

Mock Integration:Allows API Gateway to return pre-defined responses without requiring backend integration.

3. Explanation of the Options:

Option A:"Create an Amazon API Gateway REST API. Set up a proxy resource that has the HTTP proxy integration type."A proxy integration requires a backend service for handling requests. This does not meet the requirement of "no backend integrations."

Option B:"Create an Amazon API Gateway HTTP API. Provision a VPC link, and set up a private integration on the API to connect to a VPC."This requires setting up a VPC and provisioning resources, which increases operational overhead and is unnecessary for this use case.

Option C:"Create an Amazon API Gateway HTTP API. Enable mock integration on the method of the APIresource."While HTTP APIs can enable mock integrations, they have limited support for advanced features compared to REST APIs, such as detailed request/response customization. REST APIs are better suited for development environments requiring mock responses.

Option D:"Create an Amazon API Gateway REST API. Enable mock integration on the method of the API resource."This is the correct answer. REST APIs with mock integration allow defining pre-configured responses directly within API Gateway, making them ideal for scenarios where backend services are unavailable. It provides flexibility for testing while minimizing operational overhead.

4. Implementation Steps:

To enable mock integration with REST API:

Create a REST API in API Gateway:

Open theAPI Gateway Console.

ChooseCreate API>REST API.

Define the API Resource and Methods:

Add a resource and method (e.g., GET or POST).

Set Up Mock Integration:

Select the method, and in theIntegration Type, chooseMock Integration.

Configure the Mock Response:

Define a200 OK responsewith the desired response body and headers.

Deploy the API:

Deploy the API to a stage (e.g., dev) to make it accessible.

5. Why REST API Over HTTP API?

REST APIs support detailed request/response transformations and robust mock integration features, which are ideal for development and testing scenarios.

While HTTP APIs offer lower cost and simplicity, they lack some advanced features required for fine-tuned mock integrations.

The correct policy condition ensures that:

The LeadingKeys condition restricts operations to the authenticated user's user_id.

The Attributes condition limits the updatable attributes to user_name.

Explanation of Choices:

Option A:Correctly enforces both the key restriction (dynamodb:LeadingKeys) and ensures only the user_name attribute can be updated.

Option B, C, D:Use incorrect conditions, such as referencing user_name in the LeadingKeys or including other attributes like user_id in updatable fields.

The requirement here is to ensure that Lambda functions are executed in a specific order. AWS Step Functions is a low-code workflow orchestration service that enables you to sequence AWS services, such as AWS Lambda, into workflows. It is purpose-built for situations like this, where different steps need to be executed in a strict sequence.

AWS Step Functions: Step Functions allows developers to design workflows as state machines, where each state corresponds to a particular function. In this case, the developer can create a Step Functions state machine where each step (order processing, inventory management, etc.) is represented by a Lambda function.

Operational Overhead: Step Functions have very low operational overhead because it natively handles retries, error handling, and function sequencing.

Alternatives:

Amazon SQS (Option A): While SQS can manage message ordering, it requires more manual handling of each step and the logic to sequentially invoke the Lambda functions.

Amazon SNS (Option B): SNS is a pub/sub service and is not designed to handle sequences of Lambda executions.

EventBridge (Option D): EventBridge Scheduler allows you to invoke Lambda functions based on scheduled times, but it doesn’t directly support sequencing based on workflow logic.Therefore,AWS Step Functionsis the most appropriate solution due to its native orchestration capabilities and minimal operational complexity.