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NEW QUESTION: 1
What theme provides the justification for the project?
A. Plans
B. Progress
C. Business Case
D. Quality
Answer: C

NEW QUESTION: 2
Refer to the exhibit. Some 2950 series switches are connected to the conference area of the corporate headquarters network. The switches provide two to three jacks per conference room to host laptop connections for employees who visit the headquarters office. When large groups of employees come from other locations, the network administrator often finds that hubs have been connected to wall jacks in the conference area although the ports on the access layer switches were not intended to support multiple workstations.
What action could the network administrator take to prevent access by multiple laptops through a single switch port and still leave the switch functional for its intended use?

A. Implement Port Security on all interfaces and use the port-security maximum 1 command to limit port access to a single MAC address.
B. Implement Port Security on all interfaces and use the port-security mac-address sticky command to limit access to a single MAC address.
C. Configure static entries in the switch MAC address table to include the range of addresses used by visiting employees.
D. Use the mac-address-table 1 global configuration command to limit each port to one source MAC address.
E. Configure an ACL to allow only a single MAC address to connect to the switch at one time.
F. Implement Port Security at global configuration mode and use the port-security maximum 1 command to allow each switch only one attached hub.
Answer: A

NEW QUESTION: 3
부서에서 회사의 로그 파일로부터 정기적 인 분석 보고서를 생성합니다. 모든 로그 데이터는 Amazon S3에서 수집되며 Amazon Redshift 데이터웨어 하우스 용 일일 PDF 보고서 및 집계 테이블을 CSV 형식으로 생성하는 일일 Amazon Elastic MapReduce (EMR) 작업에 의해 처리됩니다.
CFO는 귀하가이 시스템의 비용 구조를 최적화하도록 요청합니다.
다음 중 원시 데이터에 대한 시스템의 평균 성능 또는 데이터 무결성을 손상시키지 않으면서 비용을 절감할수 있는 대안은 무엇입니까?
A. S3의 모든 데이터에 대해 축소 중복 저장 (RRS)을 사용합니다. Amazon EMR 작업을 위해 스팟 인스턴스와 예약 인스턴스의 조합을 사용하십시오. Amazon Redshift를 위해 예약 인스턴스를 사용하십시오.
B. S3의 PDF 및 .csv 데이터에 RRS (Redundancy Redundancy Storage)를 사용합니다. Spot 인스턴스를 EMR 작업에 추가합니다. Amazon Redshift에 스팟 인스턴스 사용.
C. Amazon S3의 모든 데이터에 축소 중복 저장 장치 (RRS)를 사용하십시오. Spot 인스턴스를 Amazon EMR 작업에 추가하십시오. Amazon Redshift를 위해 예약 인스턴스를 사용하십시오.
D. Amazon S3에서 PDF 및 .csv 데이터에 대해 Redundancy Redundancy Storage (RRS)를 사용합니다. Spot 인스턴스를 Amazon EMR 작업에 추가하십시오. Amazon Redshift를 위해 예약 인스턴스를 사용하십시오.
Answer: D
Explanation:
설명:
Redundancy Redundancy 사용 StorageAmazon S3은 스토리지 클래스에 따라 객체를 저장합니다. 스토리지 클래스가 Amazon S3에 기록 될 때 객체에 저장 클래스를 할당합니다. 객체를 Amazon S3 버킷에 쓰거나 Amazon S3에 이미 저장된 객체를 복사 할 때만 객체에 특정 저장 클래스 (표준 또는 축소 중복)를 할당 할 수 있습니다. 표준이 기본 저장소 클래스입니다. 저장소 클래스에 대한 자세한 내용은 개체 키 및 메타 데이터를 참조하십시오.
스토리지 비용을 줄이기 위해 Amazon S3가 표준 스토리지를 제공하는 것보다 낮은 수준의 중복성으로 중요하지 않은 재현 가능 데이터에 대해 축소 중복 스토리지를 사용할 수 있습니다. 리던던시가 낮 으면 내구성과 가용성이 떨어지지 만 대부분의 경우 비용이 낮을수록 리던던시 스토리지를 수용 가능한 스토리지 솔루션으로 줄일 수 있습니다. 예를 들어, 다른 곳에 영구적으로 저장된 미디어 콘텐츠를 공유하는 비용 효율적인 솔루션이 될 수 있습니다. 원본 이미지에서 쉽게 재현 할 수있는 축소판 및 기타 크기 조정 된 이미지를 저장하는 경우에도 의미가 있습니다.
Redundancy Redundancy Storage는 주어진 해 동안 객체의 99.99 % 내구성을 제공하도록 설계되었습니다. 이 내구성 수준은 개체의 평균 예상 손실 0.01 %에 해당합니다. 예를 들어, RRS 옵션을 사용하여 10,000 개의 객체를 저장하면 평균적으로 1 년에 1 개의 객체가 손실 될 것으로 예상 할 수 있습니다 (10,000 개의 객체의 0.01 %).
노트
이 연간 손실은 예상 평균을 나타내며 주어진 해에 0.01 % 미만의 개체 손실을 보장하지 않습니다.
Redundancy Redundancy Storage는 여러 장치에 여러 장치에 개체를 저장하여 일반 디스크 드라이브의 내구성을 400 배나 향상 시키지만 Amazon S3 표준 저장소만큼 개체를 복제하지는 않습니다. 또한 중복 된 스토리지를 줄이면 단일 시설에서 데이터 손실을 방지 할 수 있습니다.
축소 된 중복 저장 영역의 객체가 손실 된 경우 Amazon S3는 해당 객체에 대한 요청에 대해 405 오류를 반환합니다. Amazon S3는 중복 스토리지 개체 ​​손실 감소에 대한 알림도 제공합니다. Amazon S3가 RRS 개체 손실을 감지하면 Amazon SNS (Amazon Simple Notification Service)를 통해 알림이 전송되도록 버킷을 구성 할 수 있습니다. 그런 다음 잃어버린 객체를 바꿀 수 있습니다. 알림을 사용하려면 Amazon S3 콘솔을 사용하여 버킷의 알림 등록 정보를 설정할 수 있습니다.

RFRSNotif 설정

NEW QUESTION: 4
Which AWS service provides a simple and scalable shared file storage solution for use with Linux-based AWS and on-premises servers?
A. Amazon Glacier
B. Amazon S3
C. Amazon EFS
D. Amazon EBS
Answer: C
Explanation:
Explanation
Amazon Elastic File System (Amazon EFS) provides a simple, scalable, fully managed elastic NFS file system for use with AWS Cloud services and on-premises resources. It is built to scale on demand to petabytes without disrupting applications, growing and shrinking automatically as you add and remove files, eliminating the need to provision and manage capacity to accommodate growth.
Amazon EFS is designed to provide the throughput, IOPS, and low latency needed for Linux workloads. Throughput and IOPS scale as a file system grows and can burst to higher throughput levels for short periods of time to support the unpredictable performance needs of file workloads. For the most demanding workloads, Amazon EFS can support performance over 10 GB/sec and up to 500,000 IOPS.