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  • Exam Number/Code : Associate-Developer-Apache-Spark-3.5
  • Exam Name : Databricks Certified Associate Developer for Apache Spark 3.5 - Python
  • Questions and Answers : 260 Q&As
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NEW QUESTION: 1
When you create a Provisioning Policy, which two are required? (Choose two.)
A. level of storage availability required
B. Storage type: NAS or SAN
C. name of the policy
D. provisioning script
E. resource label
Answer: B,C

NEW QUESTION: 2
Which three services can be provided by Cisco ISR G2 access routers? (Choose three.)?
A. Cisco WAAS engine
B. NX-OS-based services
C. integrated video conferences
D. IP telephony with SIP trunking
E. zone-based firewalling
F. video control unit services
Answer: C,D,E
Explanation:
Explanation/Reference:
Explanation:

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、Application Load Balancer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にわたって望ましいパフォーマンスを維持するには?
A. 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
B. 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グループをスケールアップおよびスケールダウンします
C. 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
D. 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
Answer: D
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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Databricks Reliable Associate-Developer-Apache-Spark-3.5 Exam Online & Associate-Developer-Apache-Spark-3.5 Practical Information - Real Associate-Developer-Apache-Spark-3.5 Exam - Cads-Group


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