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Amazon DVA-C02 Exam Syllabus Topics:

Section	Weight	Objectives
Troubleshooting and Optimization	18%	- Instrument code for observability 1. Amazon CloudWatch alarms 2. Amazon CloudWatch metrics 3. Structured logging 4. AWS X-Ray 5. Custom metrics - Assist in a root cause analysis 1. AWS CloudTrail 2. Amazon CloudWatch Logs 3. Application logging 4. AWS X-Ray 5. Error handling and retries - Optimize applications by using AWS services and features 1. Memory and compute optimization 2. Data storage optimization 3. Concurrency and throttling 4. Caching strategies (ElastiCache, CloudFront) 5. Cost optimization
Security	26%	- Manage sensitive data in application code 1. Encryption of data at rest and in transit 2. AWS Systems Manager Parameter Store 3. AWS Secrets Manager 4. Environment variables - Implement encryption by using AWS services 1. AWS CloudHSM 2. Amazon S3 encryption 3. AWS Certificate Manager 4. AWS KMS 5. AWS Secrets Manager - Implement authentication and/or authorization for applications and AWS services 1. Identity federation (SAML, OpenID Connect, Amazon Cognito) 2. User pools and identity pools in Amazon Cognito 3. Role-based access control (RBAC) 4. Bearer tokens (JWT, OAuth, AWS STS) 5. Resource-based policies, service policies, and principal policies
Deployment	24%	- Automate deployment testing 1. AWS CodeCommit 2. AWS CodeDeploy 3. AWS CodeBuild 4. AWS CodePipeline - Prepare application artifacts to be deployed to AWS 1. Lambda deployment packages 2. AWS CDK 3. Docker containers 4. AWS SAM 5. AWS CloudFormation - Test applications in development environments 1. AWS SAM local 2. Mocking AWS services 3. Local testing of Lambda functions - Deploy code by using AWS CI/CD services 1. Canary deployments 2. Blue/green deployments 3. Rolling deployments 4. AWS CodeCommit 5. AWS CodeDeploy 6. AWS CodeBuild 7. AWS CodePipeline 8. GitHub integration
Development with AWS Services	32%	- Develop code for applications hosted on AWS 1. Amazon Cognito 2. Amazon SNS 3. Amazon DynamoDB 4. Amazon SQS 5. Amazon S3 6. AWS CLI 7. Amazon API Gateway 8. AWS Lambda 9. AWS CloudFormation 10. AWS SDKs - Use data stores in application development 1. Amazon ElastiCache 2. Amazon DynamoDB 3. Amazon EFS 4. Amazon RDS 5. Amazon S3 - Develop code for AWS serverless applications 1. AWS AppSync 2. Amazon EventBridge 3. Amazon API Gateway 4. AWS Step Functions

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Amazon AWS Certified Developer - Associate Sample Questions (Q201-Q206):

NEW QUESTION # 201
A company has a web application that runs on Amazon EC2 instances with a custom Amazon Machine Image (AMI). The company uses AWS CloudFormation to provision the application. The application runs in the us-east-1 Region, and the company needs to deploy the application to the us-west-1 Region.
An attempt to create the AWS CloudFormation stack in us-west-1 fails. An error message states that the AMI ID does not exist. A developer must resolve this error with a solution that uses the least amount of operational overhead.
Which solution meets these requirements?

A. Manually deploy the application outside AWS CloudFormation in us-west-1.
B. Copy the custom AMI from us-east-1 to us-west-1. Update the AWS CloudFormation template for us-west-1 to refer to AMI ID for the copied AMI. Relaunch the stack.
C. Build the custom AMI in us-west-1. Create a new AWS CloudFormation template to launch the stack in us-west-1 with the new AMI ID.
D. Change the AWS CloudFormation templates for us-east-1 and us-west-1 to use an AWS AMI.
Relaunch the stack for both Regions.

Answer: B

Explanation:
AMI IDs are Region-specific, so the custom AMI from us-east-1 cannot be referenced directly in us-west-1. Copying the AMI to us-west-1 and updating the CloudFormation template with the copied AMI ID allows the stack to launch successfully with minimal operational overhead.

NEW QUESTION # 202
A company has installed smart motes in all Its customer locations. The smart meter's measure power usage at
1minute intervals and send the usage readings to a remote endpoint tot collection. The company needs to create an endpoint that will receive the smart meter readings and store the readings in a database. The company wants to store the location ID and timestamp information.
The company wants to give Is customers low-latency access to their current usage and historical usage on demand The company expects demand to increase significantly. The solution must not impact performance or include downtime write seeing.
When solution will meet these requirements MOST cost-effectively?

A. Store the smart meter readings in Amazon EastCache for Reds Create a Sorted set key y using the location ID and timestamp columns. Use the columns to filter on the customers' data.
B. Store the smart meter readings in an Amazon RDS database. Create an index on the location ID and timestamp columns Use the columns to filter on the customers 'data.
C. Store the smart meter readings m Amazon S3 Parton the data by using the location ID and timestamp columns. Use Amazon Athena lo tiler on me customers' data.
D. Store the smart motor readings m an Amazon DynamoDB table Croato a composite Key oy using the location ID and timestamp columns. Use the columns to filter on the customers' data.

Answer: D

Explanation:
The solution that will meet the requirements most cost-effectively is to store the smart meter readings in an Amazon DynamoDB table. Create a composite key by using the location ID and timestamp columns. Use the columns to filter on the customers' data. This way, the company can leverage the scalability, performance, and low latency of DynamoDB to store and retrieve the smart meter readings. The company can also use the composite key to query the data by location ID and timestamp efficiently. The other options either involve more expensive or less scalable services, or do not provide low-latency access to the current usage.

NEW QUESTION # 203
An application development team decides to use AWS X-Ray to monitor application code to analyze performance and perform root cause analysis.
What does the team need to do to begin using X-Ray? (Select TWO.)

A. Instrument application code using the AWS SDK.
B. Create an Amazon DynamoDB table to store the trace logs.
C. Install the X-Ray agent on the application servers.
D. Use a visualization tool to view application traces.
E. Log instrumentation output into an Amazon SQS queue.

Answer: A,C

Explanation:
To begin using AWS X-Ray, the team must (1) instrument the application to emit trace segments
/subsegments and (2) ensure there is a component that can send trace data to the X-Ray service.
Instrumenting code is typically done with the AWS X-Ray SDK (language-specific). This adds tracing to inbound requests and downstream calls, creates segments/subsegments, and attaches annotations/metadata.
That corresponds to Option C.
For many compute environments (especially EC2, ECS on EC2, and on-prem servers), the application sends trace data via the X-Ray daemon/agent running locally. The daemon batches segments and forwards them to the X-Ray service endpoint. That corresponds to Option D.
Option B is helpful after traces exist (using the X-Ray console or CloudWatch ServiceLens), but it is not a prerequisite to "begin using" X-Ray.
Option A is unrelated. X-Ray does not require SQS for instrumentation output.
Option E is incorrect because X-Ray stores trace data in its managed backend; you do not create a DynamoDB table for trace logs.
Therefore, the team needs to instrument the code with the X-Ray SDK and install/run the X-Ray agent
/daemon on the servers where the application runs.

NEW QUESTION # 204
A developer is creating an Amazon DynamoDB table by using the AWS CLI. The DynamoDB table must use server-side encryption with an AWS owned encryption key.
How should the developer create the DynamoDB table to meet these requirements?

A. Create an AWS Key Management Service (AWS KMS) AWS managed key. Provide the key's Amazon Resource Name (ARN) in the KMSMasterKeyId parameter during creation of the DynamoDB table.
B. Create the DynamoDB table with the default encryption options.
C. Create an AWS owned key. Provide the key's Amazon Resource Name (ARN) in the KMSMasterKeyId parameter during creation of the DynamoDB table.
D. Create an AWS Key Management Service (AWS KMS) customer managed key. Provide the key's Amazon Resource Name (ARN) in the KMSMasterKeyId parameter during creation of the DynamoDB table.

Answer: B

NEW QUESTION # 205
A developer has created an AWS Lambda function that is written in Python. The Lambda function reads data from objects in Amazon S3 and writes data to an Amazon DynamoDB table. The function is successfully invoked from an S3 event notification when an object is created. However, the function fails when it attempts to write to the DynamoDB table.
What is the MOST likely cause of this issue?

A. The Lambda function's concurrency limit has been exceeded.
B. DynamoDB table requires a global secondary index (GSI) to support writes.
C. The DynamoDB table is not running in the same Availability Zone as the Lambda function.
D. The Lambda function does not have IAM permissions to write to DynamoDB.

Answer: C

NEW QUESTION # 206
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