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Exam Code: MLS-C01
Exam Name: AWS Certified Machine Learning - Specialty
Vendor: Amazon

60 Questions & Answers
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NEW QUESTION: 1
On an XtremIO system, how many unit spaces are required for one X-Brick, including reserved space(s)?
A. 6U
B. 7U
C. 9U
D. 8U
Answer: B

NEW QUESTION: 2
You are evaluating expense management capabilities in Dynamics 365 Finance.
Instructions: For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:



NEW QUESTION: 3
애플리케이션은 여러 가용 영역의 Amazon EC2 인스턴스에서 실행됩니다. 인스턴스는 Application Load Balancer 뒤의 Amazon EC2 Auto Scaling 그룹에서 실행됩니다. EC2 인스턴스의 CPU 사용률이 40 % 이상인 경우 애플리케이션이 가장 잘 수행됩니다. 그룹 내 모든 인스턴스에서 원하는 성능을 유지하려면?
A. 대상 추적 정책을 사용하여 Auto Scaling 그룹을 동적으로 조정
B. 간단한 조정 정책을 사용하여 Auto Scaling 그룹을 동적으로 조정
C. 예약 된 스케일링 작업을 사용하여 Auto Scaling 그룹의 스케일 업 및 스케일 다운
D. AWS Lambda 함수를 사용하여 원하는 Auto Scaling 그룹 용량을 업데이트하십시오.
Answer: A
Explanation:
Reference:
"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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