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NEW QUESTION: 1
AWS CloudFormationの循環依存関係とは何ですか？
A. リソースがDependOnループを形成する場合。
B. ネストされたスタックが互いに依存している場合。
C. テンプレートが元のテンプレートを参照する領域を参照する場合。
D. テンプレートがそれ自体の以前のバージョンを参照する場合。
Answer: A
Explanation:
依存関係エラーを解決するには、テンプレート内の他のリソースに依存するリソースにDependsOn属性を追加します。場合によっては、AWS CloudFormationが正しい順序でリソースを作成または削除できるように、依存関係を明示的に宣言する必要があります。たとえば、同じスタックにインターネットゲートウェイを持つElastic IPとVPCを作成する場合、Elastic IPはインターネットゲートウェイの接続に依存する必要があります。追加情報については、DependsOn属性を参照してください。
http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/troubleshooting.html#trouble shooting-errors-dependency-error

NEW QUESTION: 2
You are building a model to make clothing recommendations. You know a user's fashion preference is likely to change over time, so you build a data pipeline to stream new data back to the model as it becomes available.
How should you use this data to train the model?
A. Continuously retrain the model on just the new data.
B. Train on the existing data while using the new data as your test set.
C. Continuously retrain the model on a combination of existing data and the new data.
D. Train on the new data while using the existing data as your test set.
Answer: D

NEW QUESTION: 3
A 3-Ber e-commerce web application is currently deployed on-premises, and will be migrated to AWS for greater scalability and elasticity. The web tier currently shares read-only data using a network distributed file system. The app server tier uses a clustering mechanism for discovery and shared session state that depends on IP multicast. The database tier uses shared-storage clustering to provide database failover capability, and uses several read slaves for scaling. Data on all servers and the distributed file system directory is backed up weekly to off-site tapes.
Which AWS storage and database architecture meets the requirements of the application?
A. Web servers: store read-only data in S3, and copy from S3 to root volume at boot time.
App servers: share state using a combination of DynamoDB and IP unicast.
Database: use RDS with multi-AZ deployment.
Backup: web and app servers backed up weekly via AMIs, database backed up via DB snapshots.
B. Web servers: store read-only data in an EC2 NFS server, mount to each web server at boot time.
App servers: share state using a combination of DynamoDB and IP multicast.
Database: use RDS with multi- AZ deployment and one or more Read Replicas.
Backup: web and app servers backed up weekly via AMIs, database backed up via DB snapshots.
C. Web servers: store read-only data in S3, and copy from S3 to root volume at boot time.
App servers: share state using a combination of DynamoDB and IP unicast.
Database: use RDS with multi-AZ deployment and one or more read replicas.
Backup: web servers, app servers, and database backed up weekly to Glacier using snapshots.
D. Web servers: store read-only data in S3, and copy from S3 to root volume at boot time.
App servers: share state using a combination of DynamoDB and IP unicast.
Database: use RDS with multi-AZ deployment and one or more Read Replicas.
Backup: web and app servers backed up weekly via AMIs, database backed up via DB snapshots.
Answer: D
Explanation:
Amazon RDS Multi-AZ deployments provide enhanced availability and durability for Database (DB) Instances, making them a natural fit for production database workloads. When you provision a Multi-AZ DB Instance, Amazon RDS automatically creates a primary DB Instance and synchronously replicates the data to a standby instance in a different Availability Zone (AZ). Each AZ runs on its own physically distinct, independent infrastructure, and is engineered to be highly reliable. In case of an infrastructure failure (for example, instance hardware failure, storage failure, or network disruption), Amazon RDS performs an automatic failover to the standby, so that you can resume database operations as soon as the failover is complete. Since the endpoint for your DB Instance remains the same after a failover, your application can resume database operation without the need for manual administrative intervention.