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NEW QUESTION: 1
Refer to the exhibit.
Based on the Access Tracker output for the user shown, which statement describes the status?
A. A NAP agent was used to obtain the posture token for the user.
B. A Healthy Posture Token was sent to the Policy Manager.
C. The authentication method used is EAP-PEAP.
D. The Aruba Terminate Session enforcement profile as applied because the posture check failed.
E. A RADIUS-Access-Accept message is sent back to the Network Access Device.
Answer: B
Explanation:
Explanation
We see System Posture Status: HEALTHY(0)
End systems that pass all SHV tests receive a Healthy Posture Token, if they fail a single test they receive a Quarantine Posture Token.
References: CLEARPASS ONGUARD CONFIGURATION GUIDE (July 2015), page 13
https://community.arubanetworks.com/aruba/attachments/aruba/aaa-nac-guest-access-byod/21122/1/OnGuard%2
NEW QUESTION: 2
A Dell EMC NetWorker backup administrator is configuring backups for a Microsoft Windows client with several large save sets. The administrator is considering using the parallel save streams feature.
What is a characteristic of the parallel save streams feature?
A. Parallel save streams can be enabled on the backup action
B. Save set entry on the client is specified at the file system level.
C. "Target sessions" on the client controls the number of save streams
D. Synthetic full backups are supported for only Linux
Answer: B
Explanation:
References:
NEW QUESTION: 3
경매 웹 사이트를 통해 사용자는 수집품에 입찰 할 수 있습니다. 경매 규칙에 따라 각 입찰은 접수 된 순서대로 한 번만 처리되어야 합니다. 현재 구현은 Amazon Kinesis Data Streams에 입찰 레코드를 쓰는 Amazon EC2 웹 서버 집합을 기반으로 합니다. 단일 t2.large 인스턴스에는 Kinesis Data Streams에서 수신되는 입찰을 읽고 각 입찰을 처리하는 입찰 프로세서를 실행하는 크론 작업이 있습니다. 경매 사이트의 인기가 높아지고 있지만 사용자는 일부 입찰이 등록되지 않는다고 불평하고 있습니다.
문제 해결은 최대 수요 시간 동안 입찰 프로세서가 너무 느리고 처리하는 동안 충돌이 발생하며 처리중인 레코드를 추적하지 못하는 경우가 있음을 나타냅니다.
입찰 처리의 안정성을 높이려면 어떻게 해야 합니까?
A. Kinesis Data Streams에 입찰을 게시 할 때 Amazon Kinesis Producer Library (KPL)를 사용하도록 웹 애플리케이션을 리팩터링합니다. 입찰 프로세서를 리팩터링하여 Kinesis Data Streams의 각 레코드를 읽지 않음, 처리 및 처리됨으로 플래그 지정합니다. 각 입찰 처리 실행을 시작할 때 처리되지 않은 레코드에 대해 Kinesis Data Streams를 스캔합니다.
B. EC2 인스턴스 유형을 t2.large에서 더 큰 일반 컴퓨팅 인스턴스 유형으로 전환합니다. Kinesis Data Streams의 IncomingRecords 지표를 기반으로 입찰 프로세서를 실행하는 EC2 인스턴스의 수를 확장하는 Auto Scaling 그룹에 입찰 프로세서 EC2 인스턴스를 배치합니다.
이 경우 FIFO는 입찰 순서를 보장하므로 Kinesis에 비해 더 좋습니다. 최소 최대 1은 인스턴스가 실패한 경우 다시 돌아올 때까지 SQS가 대기열을 보유하므로 괜찮습니다.
C. 웹 애플리케이션을 리팩터링하여 수신되는 각 입찰을 Kinesis Data Streams 대신 Amazon SNS 주제에 게시합니다. 사용자가 제출하는 즉시 각 입찰을 처리하는 AWS Lambda 함수를 트리거하도록 SNS 주제를 구성합니다.
D. Kinesis Data Streams 대신 Amazon SQS FIFO 대기열에 들어오는 각 입찰을 게시하도록 웹 애플리케이션을 리팩터링합니다. 입찰 프로세서를 지속적으로 SQS 대기열로 리팩터링합니다. 입찰 처리 EC2 인스턴스를 최소 및 최대 크기가 1 인 Auto Scaling 그룹에 배치합니다.
Answer: D