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NEW QUESTION: 1
運用チームと開発チームは、オペレーティングシステムとアプリケーションログの両方を1か所で表示できるようにしたいと考えています。
AWSサービスを使用してこれをどのように実装する必要がありますか？ 2つの答えを選んでください
A. AWS CloudFormationを使用して、CloudWatch Logs LogGroupを作成します。
Cloudwatch Logエージェントはすべてのオペレーティングシステムログを自動的に送信するため、マシン外に送信するためのアプリケーションログを構成するだけで済みます。
B. AWS CloudFormationと構成管理を使用して、UDPパケット経由でCloudTrailにイベントを送信するようにリモートロギングを設定します。
C. AWS CloudFormationを使用して、CloudWatch Logs LogGroupを作成し、CloudWatch Logsエージェントを使用して、対象のオペレーティングシステムとアプリケーションログを送信します。
D. 構成管理を使用して、リモートロギングをセットアップし、イベントをAmazon Kinesisに送信して、利用可能な分析ツールに応じて、これらをAmazon CloudSearchまたはAmazon Redshiftに挿入します。
E. AWS CloudFormationを使用して、アプリケーションログをオペレーティングシステムのログとマージし、IAMロールを使用して、両方のチームがAmazon EC2からのコンソール出力を表示できるようにします。
Answer: C,D

NEW QUESTION: 2
What is the default method to back up an IBM Spectrum Protect V8.1 client's file system data?
A. Image
B. Full
C. Differential
D. Incremental
Answer: D
Explanation:
IBM Spectrum Protect uses the progressive incrementalbackup method. For this backup method, a first full backup of all data objects is created and in subsequent backup operations only changed data is moved to storage.
References: IBM Spectrum Protect Version 8.1.0, Introduction to Data Protection, p 5

NEW QUESTION: 3
SQL Server 2012を展開することを計画しています。Table 1とTable 2という名前の2つのテーブルを作成する必要があります。これらのテーブルには、次の仕様があります。
* Table1にはColumn1という名前の日付列が含まれ、これには時間の約80パーセントのNULL値が含まれます。
* Table2には、Table2の他の2つの列の積であるColumn2という名前の列が含まれます。
Table1とTable2の両方に100万を超える行が含まれます。
どのオプションを列に定義する必要があるかを推奨する必要があります。 解決策は、テーブルの記憶域要件を最小限に抑える必要があります。
どのオプションをお勧めしますか？ 回答するには、適切なオプションを回答領域の正しい列にドラッグします。

Answer:
Explanation:

Explanation
Column1 - Sparse;
Column2 - Computed
- Sparse columns are ordinary columns that have an optimized storage for null values. Sparse columns reduce the space requirements for null values at the cost of more overhead to retrieve nonnull values. Consider using sparse columns when the space saved is at least 20 percent to 40 percent.
- A Persisted column would be faster to retrieve.
- A computed column is computed from an expression that can use other columns in the same table. The expression can be a noncomputed column name, constant, function, and any combination of these connected by one or more operators. Unless otherwise specified, computed columns are virtual columns that are not physically stored in the table. Their values are recalculated every time they are referenced in a query. The Database Engine uses the PERSISTED keyword in the CREATE TABLE and ALTER TABLE statements to physically store computed columns in the table. Their values are updated when any columns that are part of their calculation change.
References:
http://msdn.microsoft.com/en-us/library/cc280604.aspx
http://msdn.microsoft.com/en-us/library/ms186241.aspx

NEW QUESTION: 4
A development team has created a series of AWS CloudFormation templates to help deploy services. They created a template for a network/virtual private (VPC) stack, a database stack, a bastion host stack, and a web application-specific stack. Each service requires the deployment of at least:
A network/VPC stack
* A bastion host stack
* A web application stack
* Each template has multiple input parameters that make it difficult to deploy the services individually from the AWS CloudFormation console. The input parameters from one stack are typically outputs from other stacks. For example, the VPC ID, subnet IDs, and security groups from the network stack may need to be used in the application stack or database stack.
Which actions will help reduce the operational burden and the number of parameters passed into a service deployment? (Choose two.)
A. Create a new AWS CloudFormation template for each service. After the existing templates to use cross-stack references to eliminate passing many parameters to each template. Call each required stack for the application as a nested stack from the new stack. Call the newly created service stack from the AWS CloudFormation console to deploy the specific service with a subset of the parameters previously required.
B. Set up an AWS CodePipeline workflow for each service. For each existing template, choose AWS CloudFormation as a deployment action. Add the AWS CloudFormation template to the deployment action. Ensure that the deployment actions are processed to make sure that dependences are obeyed.
Use configuration files and scripts to share parameters between the stacks. To launch the service, execute the specific template by choosing the name of the service and releasing a change.
C. Create a new portfolio in AWS Service Catalog for each service. Create a product for each existing AWS CloudFormation template required to build the service. Add the products to the portfolio that represents that service in AWS Service Catalog. To deploy the service, select the specific service portfolio and launch the portfolio with the necessary parameters to deploy all templates.
D. Use AWS Step Functions to define a new service. Create a new AWS CloudFormation template for each service. After the existing templates to use cross-stack references to eliminate passing many parameters to each template. Call each required stack for the application as a nested stack from the new service template. Configure AWS Step Functions to call the service template directly.
In the AWS Step Functions console, execute the step.
E. Create a new portfolio for the Services in AWS Service Catalog. Create a new AWS CloudFormation template for each service. After the existing templates to use cross-stack references to eliminate passing many parameters to each template. Call each required stack for the application as a nested stack from the new stack. Create a product for each application. Add the service template to the product. Add each new product to the portfolio. Deploy the product from the portfolio to deploy the service with the necessary parameters only to start the deployment.
Answer: B,D