SAP-C02入門知識、SAP-C02認定テキスト
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Amazon AWS Certified Solutions Architect - Professional (SAP-C02) 認定 SAP-C02 試験問題 (Q456-Q461):
質問 # 456
A live-events company is designing a scaling solution for its ticket application on AWS. The application has high peaks of utilization during sale events. Each sale event is a one-time event that is scheduled.
The application runs on Amazon EC2 instances that are in an Auto Scaling group. The application uses PostgreSOL for the database layer.
The company needs a scaling solution to maximize availability during the sale events.
Which solution will meet these requirements?
- A. Use a scheduled scaling policy for the EC2 instances. Host the database on an Amazcyl ROS for PostgreSQL Multi-AZ DB instance with automatically scaling read replicas. Create an Amazon EventBridge rule that invokes an AWS Lambda function to create a larger read replica before a sale event. Fail over to the larger read replic a. Create another EventBridge rule that invokes another Lambda function to scale down the read replica after the sale event.
- B. Use a scheduled scaling policy for the EC2 instances. Host the database on an Amazon Aurora PostgreSQL Multi-AZ DB duster. Create an Amazon EventBridge rule that invokes an AWS Lambda function to create a larger Aurora Replica before a sale event. Fail over to the larger Aurora Replica. Create another EventBridge rule that invokes another Lambda function to scale down the Aurora Replica after the sale event.
- C. Use a predictive scaling policy for the EC2 instances. Host the database on an Amazon Aurora PostgreSOL Serverless v2 Multi-AZ DB instance with automatically scaling read replicas. Create an AWS Step Functions state machine to run parallel AWS Lambda functions to pre-warm the database before a sale event. Create an Amazon EventBridge rule to invoke the state machine.
- D. Use a predictive scaling policy for the EC2 instances. Host the database on an Amazon RDS for PostgreSOL Multi-AZ DB instance with automatically scaling read replica. Create an AWS Step Functions state machine to run parallel AWS Lambda functions to pre-warm the database before a sale event. Create an Amazon EventBridge rule to invoke the state machine.
正解:B
解説:
The correct answer is D. Use a scheduled scaling policy for the EC2 instances. Host the database on an Amazon Aurora PostgreSQL Multi-AZ DB cluster. Create an Amazon EventBridge rule that invokes an AWS Lambda function to create a larger Aurora Replica before a sale event. Fail over to the larger Aurora Replica. Create another EventBridge rule that invokes another Lambda function to scale down the Aurora Replica after the sale event.
This solution will meet the requirements of maximizing availability during the sale events. A scheduled scaling policy for the EC2 instances will allow the application to scale up and down according to the predefined schedule of the sale events. Hosting the database on an Amazon Aurora PostgreSQL Multi-AZ DB cluster will provide high availability and durability, as well as compatibility with PostgreSQL. Creating an Amazon EventBridge rule that invokes an AWS Lambda function to create a larger Aurora Replica before a sale event will ensure that the database can handle the increased read traffic during the peak periods. Failing over to the larger Aurora Replica will make it the primary instance, which will also improve the write performance of the database. Creating another EventBridge rule that invokes another Lambda function to scale down the Aurora Replica after the sale event will reduce the cost and resources of the database.
質問 # 457
A company is running a serverless application that consists of several AWS Lambda functions and Amazon DynamoDB tables.
The company has created new functionality that requires the Lambda functions to access an Amazon Neptune DB cluster.
The Neptune DB cluster is located in three subnets in a VPC.
Which of the possible solutions will allow the Lambda functions to access the Neptune DB cluster and DynamoDB tables? (Choose two.)
- A. Create three public subnets in the Neptune VPC and route traffic through an interne: gateway Host the Lambda functions m the three new public subnets
- B. Create three private subnets in the Neptune VPC. Host the Lambda functions m the three new isolated subnets. Create a VPC endpoint for DynamoDB. and route DynamoDB traffic to the VPC endpoint
- C. Create three private subnets in the Neptune VPC and route internet traffic through a NAT gateway Host the Lambda functions In the three new private subnets.
- D. Host the Lambda functions outside the VPC. Update the Neptune security group to allow access from the IP ranges of the Lambda functions.
- E. Host the Lambda functions outside the VPC. Create a VPC endpoint for the Neptune database, and have the Lambda functions access Neptune over the VPC endpoint
正解:B、C
解説:
https://docs.aws.amazon.com/neptune/latest/userguide/security-vpc.html
質問 # 458
A company is planning a one-time migration of an on-premises MySQL database to Amazon Aurora MySQL in the us-east-I Region. The company's current internet connection has limited bandwidth. The on-premises MySQL database is 60 TB in size. The company estimates that it will take a month to transfer the data to AWS over the current internet connection.
The company needs a migration solution that will migrate the database more quickly.
Which solution will migrate the database in the LEAST amount of time?
- A. Request a 1 Gbps AWS Direct Connect connection between the on-premises data center and AWS. Use AWS Database Migration Service (AWS DMS) to migrate the on-premises MySQL database to Aurora MySQL.
- B. Order an AWS Snowball Edge device. Load the data into an Amazon S3 bucket by using the S3 interface. Use AWS Database Migration Service (AWS DMS) to migrate the data from Amazon S3 to Aurora MySQL
- C. Use AWS DataSync with the current internet connection to accelerate the data transfer between the on-premises data center and AWS. Use AWS Application Migration Service to migrate the on-premises MySQL database to Aurora MySQL.
- D. Order AWS Snowball device. Load the data into an Amazon S3 bucket by using the S3 Adapter for Snowball. Use AWS Application Migration Service to migrate the data from Amazon S3 to Aurora MySQL
正解:B
解説:
Explanation
Ordering an AWS Snowball Edge device will enable transferring large amounts of data to AWS without using the internet1. AWS Snowball Edge is a type of Snowball device with on-board storage and compute power for select AWS capabilities2. Loading the data into an Amazon S3 bucket by using the S3 interface will enable storing the data on the device2. Using AWS Database Migration Service (AWS DMS) to migrate the data from Amazon S3 to Aurora MySQL will enable migrating the on-premises MySQL database to Aurora MySQL3. AWS DMS can use Amazon S3 as a source for a database migration3.
質問 # 459
A company runs a workload in the AWS Cloud. The company stores data for the application in an older version of Amazon DocumentDB. Several backend services read and write data to the database continuously throughout all hours of the day. All services connect to the database by using the Amazon DocumentDB cluster endpoint, which is registered as a DNS record in Amazon Route 53.
The company needs to upgrade the database to the latest version of Amazon DocumentDB without losing any data. The company must be able to test and verify the upgrade before the company allows backend services to use the upgraded version. The company has already enabled change streams and set a retention period of 24 hours.
Which solution will meet these requirements?
- A. Create a new Amazon DocumentDB cluster that runs the latest version. Deploy the AWS DataSync agent to an Amazon EC2 instance and activate the agent. Create a new AWS DataSync task in enhanced mode. Start the transfer task to copy data to the new cluster. Test and verify the new cluster.Update the Route 53 record to point to the new cluster.
- B. Create a new Amazon DocumentDB cluster that runs the latest version. Install MongoDB command line interface (CLI) database tools on an Amazon EC2 instance. Use the MongoDB CLI to create a binary export, and import the data to the new Amazon DocumentDB cluster. Test and verify the new cluster. Update the Route 53 record to point to the new cluster.
- C. Create a snapshot of the existing Amazon DocumentDB cluster. Perform an in-place major version upgrade. Modify the existing cluster to the latest version and the latest cluster parameter group. Apply modifications immediately. Test and verify the upgrade.
- D. Create a new Amazon DocumentDB cluster that runs the latest version. Use the Amazon DocumentDB Index Tool to export existing indexes and import them to the new cluster. Create a new AWS DMS instance and a source and target endpoint. Create a DMS task to migrate the data by using the Migrate and replicate migration type. Test and verify the new cluster. Update the Route 53 record to point to the new cluster.
正解:D
解説:
The company needs to upgrade DocumentDB to the latest version with no data loss while allowing continuous reads and writes. The company also must be able to test and verify the upgrade before switching production traffic. This is a classic requirement for performing an upgrade using a blue/green approach: build a new target environment on the new version, keep it in sync with the source, validate it, and then cut over by changing the endpoint (here, Route 53 DNS).
Option A implements this pattern using a new DocumentDB cluster running the latest version and AWS DMS to continuously migrate and replicate changes from the old cluster to the new cluster. Because the workload is continuously changing, a one-time export/import is insufficient; continuous replication is needed to keep the target cluster current during the test period. AWS DMS supports a "migrate and replicate" style of task that performs a full load and then applies ongoing changes (CDC) so the target stays synchronized. The question also states that change streams are enabled with a 24-hour retention period, which supports capturing and applying changes during migration/validation and helps ensure the replication stream can be maintained while testing.
Option A also addresses indexes by using the DocumentDB Index Tool to export and import indexes, which is important because indexes can affect query performance and behavior. After the company validates the new cluster, the cutover is done by updating the Route 53 record to point to the new cluster endpoint, switching all backend services without changing application configuration beyond DNS resolution.
Option B uses MongoDB CLI tools to export/import. This is not suitable for continuous write workloads because export/import is a point-in-time operation and would require downtime or risk data divergence during the test period. It also adds more operational overhead and does not provide continuous replication for the duration of validation.
Option C performs an in-place major version upgrade. That does not satisfy the requirement to test and verify the upgrade before backend services use the upgraded version because the upgrade happens directly on the production cluster. Even though a snapshot exists for rollback, production is still exposed to the upgrade immediately, which violates the requirement for pre-cutover verification.
Option D is incorrect because AWS DataSync transfers files between storage systems such as NFS/SMB and AWS storage services. It is not a database migration or replication service and cannot copy a DocumentDB database in a way that preserves database semantics and supports continuous replication.
Therefore, creating a new DocumentDB cluster, keeping it synchronized using AWS DMS (supported by change stream retention), validating it, and then cutting over via Route 53 DNS update (option A) meets all requirements.
References:
AWS documentation on blue/green style database upgrades by migrating to a new cluster and cutting over via DNS.
AWS documentation on AWS DMS full load plus ongoing replication (CDC) patterns for minimizing downtime and maintaining target synchronization during validation.
AWS documentation on Amazon DocumentDB change streams and retention considerations for capturing ongoing changes during migration windows.
質問 # 460
A company is serving files to its customers through an SFTP server that is accessible over the internet The SFTP server is running on a single Amazon EC2 instance with an Elastic IP address attached Customers connect to the SFTP server through its Elastic IP address and use SSH for authentication The EC2 instance also has an attached security group that allows access from all customer IP addresses.
A solutions architect must implement a solution to improve availability minimize the complexity of infrastructure management and minimize the disruption to customers who access files. The solution must not change the way customers connect Which solution will meet these requirements?
- A. Disassociate the Elastic IP address from the EC2 instance. Create a new Amazon Elastic File System (Amazon EFS) file system to be used for SFTP file hosting. Create an AWS Fargate task definition to run an SFTP server Specify the EFS file system as a mount in the task definition Create a Fargate service by using the task definition, and place a Network Load Balancer (NLB) in front of the service.
When configuring the service, attach the security group with customer IP addresses to the tasks that run the SFTP server Associate the Elastic IP address with the NLB Sync all files from the SFTP server to the S3 bucket. - B. Disassociate the Elastic IP address from the EC2 instance. Create a multi-attach Amazon Elastic Block Store (Amazon EBS) volume to be used for SFTP file hosting. Create a Network Load Balancer (NLB) with the Elastic IP address attached. Create an Auto Scaling group with EC2 instances that run an SFTP server. Define in the Auto Scaling group that instances that are launched should attach the new multi-attach EBS volume Configure the Auto Scaling group to automatically add instances behind the NLB. configure the Auto Scaling group to use the security group that allows customer IP addresses for the EC2 instances that the Auto Scaling group launches Sync all files from the SFTP server to the new multi-attach EBS volume.
- C. Disassociate the Elastic IP address from the EC2 instance Create an Amazon S3 bucket to be used for SFTP file hosting Create an AWS Transfer Family Server Configure the Transfer Family server with a VPC-hosted, internet-facing endpoint Associate the SFTP Elastic IP address with the new endpoint Attach the security group with customer IP addresses to the new endpoint Point the Transfer Family server to the S3 bucket. Sync all files from the SFTP server to the S3 bucket.
- D. Disassociate the Elastic IP address from the EC2 instance Create an Amazon S3 bucket to be used for SFTP file hosting Create an AWS Transfer Family server. Configure the Transfer Family server with a publicly accessible endpoint Associate the SFTP Elastic IP address with the new endpoint. Point the Transfer Family server to the S3 bucket Sync all files from the SFTP server to the S3 bucket.
正解:C
解説:
Explanation
https://aws.amazon.com/premiumsupport/knowledge-center/aws-sftp-endpoint-type/
質問 # 461
......
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