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Amazon DVA-C02 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|
| Troubleshooting and Optimization | 18% | - Performance optimization
- 1. Fault tolerance and resilience patterns
- 2. Application performance tuning
- Monitoring and logging
- 1. Amazon CloudWatch metrics and logs
|
| Development with AWS Services | 32% | - Application development and integration
- 1. API Gateway and REST APIs
- 2. Event-driven architectures with SNS/SQS
- AWS core services development
- 1. Amazon S3 usage in applications
- 2. AWS Lambda functions development
- 3. Amazon DynamoDB integration patterns
|
| Security | 26% | - Data security
- 1. Encryption using AWS KMS
- 2. Secure API access patterns
- Application authentication and authorization
- 1. Cognito user authentication
- 2. IAM roles and policies
|
| Deployment | 24% | - CI/CD and deployment strategies
- 1. AWS CodePipeline workflows
- 2. AWS CodeBuild and CodeDeploy usage
- Infrastructure as code
- 1. AWS CloudFormation templates
|
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Amazon AWS Certified Developer - Associate 認定 DVA-C02 試験問題 (Q376-Q381):
質問 # 376
A developer is optimizing an AWS Lambda function and wants to test the changes in production on a small percentage of all traffic. The Lambda function serves requests to a REST API in Amazon API Gateway. The developer needs to deploy their changes and perform a test in production without changing the API Gateway URL.
Which solution will meet these requirements?
- A. Define a function version for the currently deployed production Lambda function. Update the API Gateway endpoint to reference the new Lambda function version. Upload and publish the optimized Lambda function code. Update the API Gateway endpoint to use the $LATEST version of the Lambda function.
Deploy a new API Gateway stage. - B. Define a function version for the currently deployed production Lambda function. Update the API Gateway endpoint to reference the new Lambda function Deploy the API to the production API Gateway stage.
- C. Define a function version for the currently deployed production Lambda function. Update the API Gateway endpoint to reference the new Lambda function version. Upload and publish the optimized Lambda function code. On the production API Gateway stage, define a canary release and set the percentage of traffic to direct to the canary release. Update the API Gateway endpoint to use the $LATEST version of the Lambda function. Publish the API to the canary stage.
- D. Define an alias on the $LATEST version of the Lambda function. Update the API Gateway endpoint to reference the new Lambda function alias. Upload and publish the optimized Lambda function code. On the production API Gateway stage, define a canary release and set the percentage of traffic to direct to the canary release. Update the API Gateway endpoint to use the SLAT EST version of the Lambda function. Publish to the canary stage.
正解:D
解説:
A Lambda alias is a pointer to a specific Lambda function version or another alias1. A Lambda alias allows you to invoke different versions of a function using the same name1. You can also split traffic between two aliases by assigning weights to them1.
In this scenario, the developer needs to test their changes in production on a small percentage of all traffic without changing the API Gateway URL. To achieve this, the developer can follow these steps:
Define an alias on the $LATEST version of the Lambda function. This will create a new alias that points to the latest code of the function.
Update the API Gateway endpoint to reference the new Lambda function alias. This will make the API Gateway invoke the alias instead of a specific version of the function.
Upload and publish the optimized Lambda function code. This will update the $LATEST version of the function with the new code.
On the production API Gateway stage, define a canary release and set the percentage of traffic to direct to the canary release. This will enable API Gateway to perform a canary deployment on a new API2. A canary deployment is a software development strategy in which a new version of an API is deployed for testing purposes, and the base version remains deployed as a production release for normal operations on the same stage2. The canary release receives a small percentage of API traffic and the production release takes up the rest2.
Update the API Gateway endpoint to use the $LATEST version of the Lambda function. This will make the canary release invoke the latest code of the function, which contains the optimized changes.
Publish to the canary stage. This will deploy the changes to a subset of users for testing.
By using this solution, the developer can test their changes in production on a small percentage of all traffic without changing the API Gateway URL. The developer can also monitor and compare metrics between the canary and production releases, and promote or disable the canary as needed2.
質問 # 377
An application is processing clickstream data using Amazon Kinesis. The clickstream data feed into Kinesis experiences periodic spikes. The PutRecords API call occasionally fails and the logs show that the failed call returns the response shown below:

Which techniques will help mitigate this exception? (Choose two.)
- A. Use Amazon SNS instead of Kinesis.
- B. Reduce the frequency and/or size of the requests.
- C. Use a PutRecord API instead of PutRecords.
- D. Implement retries with exponential backoff.
- E. Reduce the number of KCL consumers.
正解:B、D
解説:
Explanation
The response from the API call indicates that the ProvisionedThroughputExceededException exception has occurred. This exception means that the rate of incoming requests exceeds the throughput limit for one or more shards in a stream. To mitigate this exception, the developer can use one or more of the following techniques:
Implement retries with exponential backoff. This will introduce randomness in the retry intervals and avoid overwhelming the shards with retries.
Reduce the frequency and/or size of the requests. This will reduce the load on the shards and avoid throttling errors.
Increase the number of shards in the stream. This will increase the throughput capacity of the stream and accommodate higher request rates.
Use a PutRecord API instead of PutRecords. This will reduce the number of records per request and avoid exceeding the payload limit.
References:
[ProvisionedThroughputExceededException - Amazon Kinesis Data Streams Service API Reference]
[Best Practices for Handling Kinesis Data Streams Errors]
質問 # 378
A web application is using Amazon Kinesis Data Streams for clickstream data that may not be consumed for up to 12 hours.
How can the developer implement encryption at rest for data within the Kinesis Data Streams?
- A. Use Amazon Kinesis Consumer Library.
- B. Enable SSL connections to Kinesis.
- C. Encrypt the data once it is at rest with a Lambda function.
- D. Enable server-side encryption in Kinesis Data Streams.
正解:D
解説:
Amazon Kinesis Data Streams is designed for real-time data streaming and allows multiple consumers to process data concurrently and in real-time. It can handle millions of events and provides a scalable and cost-effective solution for handling high-throughput data streams.
質問 # 379
A developer is storing sensitive data generated by an application in Amazon S3. The developer wants to encrypt the data at rest. A company policy requires an audit trail of when the AWS Key Management Service (AWS KMS) key was used and by whom.
Which encryption option will meet these requirements?
- A. Server-side encryption with Amazon S3 managed keys (SSE-S3)
- B. Server-side encryption with self-managed keys
- C. Server-side encryption with AWS KMS managed keys (SSE-KMS)
- D. Server-side encryption with customer-provided keys (SSE-C)
正解:C
解説:
KMS provides audit functionalities.
質問 # 380
A developer is building a serverless application by using the AWS Serverless Application Model (AWS SAM). The developer is currently testing the application in a development environment.
When the application is nearly finished, the developer will need to set up additional testing and staging environments for a quality assurance team.
The developer wants to use a feature of the AWS SAM to set up deployments to multiple environments.
Which solution will meet these requirements with the LEAST development effort?
- A. Create additional AWS SAM templates for each testing and staging environment. Write a custom shell script that uses the sam deploy command and the --template-file flag to deploy updates to the environments.
- B. Use the existing AWS SAM template. Add additional parameters to configure specific attributes for the serverless function and database table resources that are in each environment. Deploy updates to the testing and staging environments by using the sam deploy command.
- C. Create one AWS SAM configuration file that has default parameters. Perform updates to the testing and staging environments by using the --parameter-overrides flag in the AWS SAM CLI and the parameters that the updates will override.
- D. Add a configuration file in TOML format to group configuration entries to every environment. Add a table for each testing and staging environment. Deploy updates to the environments by using the sam deploy command and the --config-env flag that corresponds to each environment.
正解:D
質問 # 381
......
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