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NEW QUESTION: 1
Which of the following is a critical success factor for business process modeling?
A. Streamline for resource availability.
B. Eliminate exception execution of processes.
C. Reduce unique handling requirements.
D. Follow defined standards and naming conventions.
Answer: D

NEW QUESTION: 2
A customer recently provisioned a new server on the IaaS. The IP address assigned from the pool resolves to another hostname. Some user traffic is being dumped or is causing slowness because of this issue. Which of the following maintenance activities does the provider need to perform to prevent this issue?
A. Run a script to remove stale DNS entries.
B. Use cloud provider tools to remove orphaned resources.
C. Initiate resource reclamation.
D. Update outdated security firewall configurations.
Answer: A

NEW QUESTION: 3
An organization hosts 10 microservices, each in an Auto Scaling group behind individual Classic Load Balancers. Each EC2 instance is running at optimal load. Which of the following actions would allow the organization to reduce costs without impacting performance?
A. Change instance types in the Auto Scaling group launch configuration
B. Replace the Classic Load Balancers with a single Application Load Balancer
C. Change the maximum size but leave the desired capacity of the Auto Scaling groups
D. Reduce the number of EC2 instances behind each Classic Load Balancer
Answer: B
Explanation:
Explanation
https://www.sumologic.com/insight/aws-elastic-load-balancers-classic-vs-application/
https://docs.aws.amazon.com/elasticloadbalancing/latest/application/tutorial-target-ecs-containers.html An application load balancer can take the place of multiple individual classic load balancers to load balance microservices (e.g. running on AWS ECS) saving costs.

NEW QUESTION: 4
完成したバイナリ分類機械学習モデルを評価しています。
評価指標として精度を使用する必要があります。
どの視覚化を使用する必要がありますか？
A. Binary classification confusion matrix
B. Gradient descent
C. box plot
D. coefficient of determination
Answer: A
Explanation:
説明
参照：
https://machinelearningknowledge.ai/confusion-matrix-and-performance-metrics-machine-learning/