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[General] Reliable Amazon Reliable DVA-C02 Test Practice With Interarctive Test Engine &am

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【General】 Reliable Amazon Reliable DVA-C02 Test Practice With Interarctive Test Engine &am

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Amazon AWS Certified Developer - Associate Sample Questions (Q62-Q67):NEW QUESTION # 62
A developer needs to export the contents of several Amazon DynamoDB tables into Amazon S3 buckets to comply with company data regulations. The developer uses the AWS CLI to run commands to export from each table to the proper S3 bucket. The developer sets up AWS credentials correctly and grants resources appropriate permissions. However, the exports of some tables fail.
What should the developer do to resolve this issue?
  • A. Ensure that DynamoDB streaming is enabled for the tables.
  • B. Ensure that the target S3 bucket is in the same AWS Region as the DynamoDB table.
  • C. Ensure that point-in-time recovery is enabled on the DynamoDB tables.
  • D. Ensure that DynamoDB Accelerator (DAX) is enabled.
Answer: B
Explanation:
Comprehensive Detailed and Lengthy Step-by-Step Explanation with All AWS Developer Reference:
1. Understanding the Use Case:
The developer needs to export DynamoDB table data into Amazon S3 buckets using the AWS CLI, and some exports are failing. Proper credentials and permissions have already been configured.
2. Key Conditions to Check:
Region Consistency:
DynamoDB exports require that the target S3 bucket and the DynamoDB table reside in the same AWS Region. If they are not in the same Region, the export process will fail.
Point-in-Time Recovery (PITR):
PITR is not required for exporting data from DynamoDB to S3. Enabling PITR allows recovery of table states at specific points in time but does not directly influence export functionality.
DynamoDB Streams:
Streams allow real-time capture of data modifications but are unrelated to the bulk export feature.
DAX (DynamoDB Accelerator):
DAX is a caching service that speeds up read operations for DynamoDB but does not affect the export functionality.
3. Explanation of the Options:
Option A:
"Ensure that point-in-time recovery is enabled on the DynamoDB tables." While PITR is useful for disaster recovery and restoring table states, it is not required for exporting data to S3. This option does not address the export failure.
Option B:
"Ensure that the target S3 bucket is in the same AWS Region as the DynamoDB table." This is the correct answer. DynamoDB export functionality requires the target S3 bucket to reside in the same AWS Region as the DynamoDB table. If the S3 bucket is in a different Region, the export will fail.
Option C:
"Ensure that DynamoDB streaming is enabled for the tables."
Streams are useful for capturing real-time changes in DynamoDB tables but are unrelated to the export functionality. This option does not resolve the issue.
Option D:
"Ensure that DynamoDB Accelerator (DAX) is enabled."
DAX accelerates read operations but does not influence the export functionality. This option is irrelevant to the issue.
4. Resolution Steps:
To ensure successful exports:
Verify the Region of the DynamoDB tables:
Check the Region where each table is located.
Verify the Region of the target S3 buckets:
Confirm that the target S3 bucket for each export is in the same Region as the corresponding DynamoDB table.
If necessary, create new S3 buckets in the appropriate Regions.
Run the export command again with the correct setup:
aws dynamodb export-table-to-point-in-time
--table-name <TableName>
--s3-bucket <BucketName>
--s3-prefix <refix>
--export-time <ExportTime>
--region <Region>
Reference:
Exporting DynamoDB Data to Amazon S3
S3 Bucket Region Requirements for DynamoDB Exports
AWS CLI Reference for DynamoDB Export

NEW QUESTION # 63
A company wants to use AWS AppConfig to gradually deploy a new feature to 15% of users to test the feature before a full deployment.
Which solution will meet this requirement with theLEAST operational overhead?
  • A. Create an AWS AppConfig feature flag. Define a variant for the new feature, and create a rule to target
    15% of users.
  • B. Set up a custom script within the application to randomly select 15% of users. Assign a flag for the new feature to the selected users.
  • C. Create separate AWS AppConfig feature flags for both groups of users. Configure the flags to target
    15% of users.
  • D. Use AWS AppConfig to create a feature flag without variants. Implement a custom traffic splitting mechanism in the application code.
Answer: A
Explanation:
Comprehensive Detailed and Lengthy Step-by-Step Explanation with All AWS Developer References:
1. Understanding the Use Case:
The company wants to gradually release a new feature to 15% of users to perform testing. AWS AppConfig is designed to manage and deploy configurations, including feature flags, allowing controlled rollouts.
2. Key AWS AppConfig Features:
* Feature Flags:Enable or disable features dynamically without redeploying code.
* Variantsefine different configurations for subsets of users.
* Targeting Rules:Specify rules for which users receive a particular variant.
3. Explanation of the Options:
* Option A:"Set up a custom script within the application to randomly select 15% of users. Assign a flag for the new feature to the selected users."While possible, this approach requires significant operational effort to manage user selection and ensure randomness. It does not leverage AWS AppConfig's built-in capabilities, which increases overhead.
* Option B:"Create separate AWS AppConfig feature flags for both groups of users. Configure the flags to target 15% of users."Creating multiple feature flags for different user groups complicates configuration management and does not optimize the use of AWS AppConfig.
* Option C:"Create an AWS AppConfig feature flag. Define a variant for the new feature, and create a rule to target 15% of users."This is the correct solution. Using AWS AppConfig feature flags with variants and targeting rules is the most efficient approach. It minimizes operational overhead by leveraging AWS AppConfig's built-in targeting and rollout capabilities.
* Option D:"Use AWS AppConfig to create a feature flag without variants. Implement a custom traffic splitting mechanism in the application code."This approach requires custom implementation within the application code, increasing complexity and operational effort.
4. Implementation Steps for Option C:
* Set Up AWS AppConfig:
* Open theAWS Systems Manager Console.
* Navigate toAppConfig.
* Create a Feature Flag:
* Define a new configuration for the feature flag.
* Add variants (e.g., "enabled" for the new feature and "disabled" for no change).
* Define a Targeting Rule:
* Usepercentage-based targetingto define a rule that applies the "enabled" variant to 15% of users.
* Targeting rules can use attributes like user IDs or geographic locations.
* Deploy the Configuration:
* Deploy the configuration using a controlled rollout to ensure gradual exposure.

NEW QUESTION # 64
A developer is troubleshooting an Amazon API Gateway API Clients are receiving HTTP 400 response errors when the clients try to access an endpoint of the API.
How can the developer determine the cause of these errors?
  • A. Turn on execution logging and access logging in Amazon CloudWatch Logs for the API stage. Create a CloudWatch Logs log group. Specify the Amazon Resource Name (ARN) of the log group for the API stage.
  • B. Create an Amazon Kinesis Data Firehose delivery stream to receive API call logs from API Gateway. Configure Amazon CloudWatch Logs as the delivery stream's destination.
  • C. Turn on AWS X-Ray for the API stage Create an Amazon CtoudWalch Logs log group Specify the Amazon Resource Name (ARN) of the log group for the API stage.
  • D. Turn on AWS CloudTrail Insights and create a trail Specify the Amazon Resource Name (ARN) of the trail for the stage of the API.
Answer: A
Explanation:
This solution will meet the requirements by using Amazon CloudWatch Logs to capture and analyze the logs from API Gateway. Amazon CloudWatch Logs is a service that monitors, stores, and accesses log files from AWS resources. The developer can turn on execution logging and access logging in Amazon CloudWatch Logs for the API stage, which enables logging information about API execution and client access to the API. The developer can create a CloudWatch Logs log group, which is a collection of log streams that share the same retention, monitoring, and access control settings. The developer can specify the Amazon Resource Name (ARN) of the log group for the API stage, which instructs API Gateway to send the logs to the specified log group. The developer can then examine the logs to determine the cause of the HTTP 400 response errors. Option A is not optimal because it will create an Amazon Kinesis Data Firehose delivery stream to receive API call logs from API Gateway, which may introduce additional costs and complexity for delivering and processing streaming data. Option B is not optimal because it will turn on AWS CloudTrail Insights and create a trail, which is a feature that helps identify and troubleshoot unusual API activity or operational issues, not HTTP response errors. Option C is not optimal because it will turn on AWS X-Ray for the API stage, which is a service that helps analyze and debug distributed applications, not HTTP response errors.

NEW QUESTION # 65
A company's application includes an Amazon DynamoDB table for product orders. The table has a primary partition key of orderId and has no sort key. The company is adding a new feature that requires the application to query the table by using the customerId attribute.
Which solution will provide this query functionality?
  • A. Create a new local secondary index (LSI) on the table with a partition key of orderId and a sort key of customerId.
  • B. Create a new global secondary index (GSI) on the table with a partition key of customerId.
  • C. Create a new local secondary index (LSI) on the table with a partition key of customerId.
  • D. Change the existing primary key by setting customerId as the sort key.
Answer: B

NEW QUESTION # 66
A company has multiple Amazon VPC endpoints in the same VPC. A developer needs configure an Amazon S3 bucket policy so users can access an S3 bucket only by using these VPC endpoints.
Which solution will meet these requirements?
  • A. Create a single S3 bucket policy that the multiple aws SourceVpce value and in the SringNotEquals condton to use vpce.
  • B. Create a single S3 bucket policy that has multiple aws sourceVpce value in the StingNotEquale condition. Repeat for all the VPC endpoint IDs.
  • C. Create multiple S3 bucket polices by using each VPC endpoint ID that have the aws SourceVpce value in the StringNotEquals condition.
  • D. Create a single S3 bucket policy that has the aws SourceVpc value and in the StingNotEquals condition to use VPC ID.
Answer: B
Explanation:
This solution will meet the requirements by creating a single S3 bucket policy that denies access to the S3 bucket unless the request comes from one of the specified VPC endpoints. The aws:SourceVpce condition key is used to match the ID of the VPC endpoint that is used to access the S3 bucket. The StringNotEquals condition operator is used to negate the condition, so that only requests from the listed VPC endpoints are allowed. Option A is not optimal because it will create multiple S3 bucket policies, which is not possible as only one bucket policy can be attached to an S3 bucket. Option B is not optimal because it will use the aws:
SourceVpc condition key, which matches the ID of the VPC that is used to access the S3 bucket, not the VPC endpoint. Option C is not optimal because it will use the StringNotEquals condition operator with a single value, which will deny access to the S3 bucket from all VPC endpoints except one.

NEW QUESTION # 67
......
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