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NEW QUESTION: 1
HOTSPOT
Answer:
Explanation:
NEW QUESTION: 2
Which of the following should an IS auditor review to gain an understanding of the effectiveness of controls over the management of multiple projects?
A. Policy documents
B. Project database
C. Program organization
D. Project portfolio database
Answer: D
Explanation:
Explanation/Reference:
Explanation:
A project portfolio database is the basis for project portfolio management. It includes project data, such as owner, schedules, objectives, project type, status and cost. Project portfolio management requires specific project portfolio reports. A project database may contain the above for one specific project and updates to various parameters pertaining to the current status of that single project. Policy documents on project management set direction for the design, development, implementation and monitoring of the project.
Program organization is the team required (steering committee, quality assurance, systems personnel, analyst, programmer, hardware support, etc.) to meet the delivery objective of the project.
NEW QUESTION: 3
アプリケーションは、複数のアベイラビリティーゾーンにまたがるAmazon EC2インスタンスで実行されます。インスタンスは、アプリケーションロードバランサーの背後にあるAmazon EC2 Auto Scalingグループで実行されます。アプリケーションは、EC2インスタンスのCPU使用率が40％以下のときに最高のパフォーマンスを発揮します。グループ内のすべてのインスタンスで望ましいパフォーマンスを維持しますか？
A. ターゲットトラッキングポリシーを使用して、Auto Scalingグループを動的にスケーリングします
B. 単純なスケーリングポリシーを使用してAuto Scalingグループを動的にスケーリングします
C. AWS Lambda関数を使用して、目的のAuto Scalingグループ容量を更新します
D. スケジュールされたスケーリングアクションを使用して、Auto Scalingグループを拡大および縮小します
Answer: A
Explanation:
Reference:
https://docs.aws.amazon.com/autoscaling/ec2/userguide/as-scaling-target-tracking.html
"With target tracking scaling policies, you select a scaling metric and set a target value. Amazon EC2 Auto Scaling creates and manages the CloudWatch alarms that trigger the scaling policy and calculates the scaling adjustment based on the metric and the target value. The scaling policy adds or removes capacity as required to keep the metric at, or close to, the specified target value. In addition to keeping the metric close to the target value, a target tracking scaling policy also adjusts to changes in the metric due to a changing load pattern. For example, you can use target tracking scaling to: Configure a target tracking scaling policy to keep the average aggregate CPU utilization of your Auto Scaling group at 40 percent. Configure a target tracking scaling policy to keep the request count per target of your Application Load Balancer target group at 1000 for your Auto Scaling group."
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