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NEW QUESTION: 1
The problem just described is beast approved by use of which quantitative method?
A. Queuing theory.
B. Integrated autoregressive-moving average ARIMA) modeling.
C. Exponential smoothing, multiple parameters.
D. Linear programming.
Answer: A
Explanation:
Two basic casts are involved in queuing waiting-line) models: 1) the cast of providing service including facility casts and operating casts), and 2) the cast of idle resources waiting in line. The latter may be a direct cast if paid employees are waiting, or an opportunity cast in the case of waiting customers. The objective of the queuing theory is to minimize the total cast of the system, including bath service and waiting casts, far a given rate of arrivals. This minimization occurs at the paint where the cast of waiting is balanced by the cast of providing service. A bank has two drive-in lanes to serve customers: one attached to the bank itself and one on an island. One teller serves bath stations. The bank is interested in determining the average waiting times of customers and has developed a model based on random numbers. The two key factors are the time between successive car arrivals and the time customers wait in line. Assume that the analysis begins with cars just arriving at bath service windows. bath requiring 3 minutes of service time. Car 1 is the attached window attached to the bank unless that window has more cars waiting than the island window. The lone teller will always serve the car that arrived first. If two cars arrive simultaneously, the one at the attached window will be served before the one at the island.
NEW QUESTION: 2
다음 중 24x7 거래를 처리하는 글로벌 금융 기관의 보안 운영 센터의 효율성에 가장 큰 위험을 나타내는 것은 무엇입니까?
A. 인시던트 대응 기능이 제 3 자 제공 업체에 아웃소싱 됩니다.
B. 사고 대응은 정상 업무 시간 동안 단일 위치에서 수행됩니다.
C. 이벤트 상관 관계에서 사전 프로덕션 시스템의 로그는 제외됩니다.
D. 사고 대응 보고는 오픈 소스 소프트웨어를 기반으로 합니다.
Answer: B
NEW QUESTION: 3
You design a solution for the web tier of WebApp1 as shown in the exhibit.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
Answer:
Explanation:
Explanation
Box 1: Yes
Any new deployments to Azure must be redundant in case an Azure region fails.
Traffic Manager uses DNS to direct client requests to the most appropriate service endpoint based on a traffic-routing method and the health of the endpoints. An endpoint is any Internet-facing service hosted inside or outside of Azure. Traffic Manager provides a range of traffic-routing methods and endpoint monitoring options to suit different application needs and automatic failover models. Traffic Manager is resilient to failure, including the failure of an entire Azure region.
Box 2: Yes
Recent changes in Azure brought some significant changes in autoscaling options for Azure Web Apps (i.e.
Azure App Service to be precise as scaling happens on App Service plan level and has effect on all Web Apps running in that App Service plan).
Box 3: No
Traffic Manager provides a range of traffic-routing methods and endpoint monitoring options to suit different application needs and automatic failover models. Traffic Manager is resilient to failure, including the failure of an entire Azure region.
Reference:
https://docs.microsoft.com/en-us/azure/traffic-manager/traffic-manager-overview
https://blogs.msdn.microsoft.com/hsirtl/2017/07/03/autoscaling-azure-web-apps/
