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NEW QUESTION: 1
The implementation group has been using the test bed to do an IPv6 'proof-of-concept1. After several changes to the network addressing and routing schemes, a trouble ticket has been
opened indicating that the loopback address on R1 (2026::111:1) is not able to ping the loopback address on DSW2 (2026::102:1).
The fault condition is related to which technology?
A. IPv4 OSPF Routing
B. IPV4 and IPV6 Interoperability
C. IPv6 OSPF Routing
D. NTP
E. IPv4 layer 3 security
Answer: B
Explanation:
As explained earlier, the problem is with route misconfigured tunnel modes on R3. R3 is using tunnel mode ipv6, while R4 is using the default of GRE.

NEW QUESTION: 2
CORRECT TEXT
What is the maximum RT CORBA priority value?
Answer:
Explanation:
32767

NEW QUESTION: 3
Your network contains an Active Directory domain named contoso.com. The domain contains multiple servers that run Windows Server 2012. All client computers run Windows 7.
The network contains two data centers.
You plan to deploy one file server to each data center.
You need to recommend a solution to provide redundancy for shared folders if a single data center fails.
What should you recommend?
More than one answer choice may achieve the goal. Select the BEST answer.
A. The clustered File Server role of the File Server scale-out application data type
B. Cluster Shared Volumes (CSVs)
C. The clustered File Server role of the File Server for general use type
D. A Distributed File System (DFS) namespace and DFS Replication
Answer: D

NEW QUESTION: 4
고객은 하나의 단일 시스템에서 로그 스트림 (액세스 로그, 응용 프로그램 로그, 보안 로그 등)을 통합하려고 합니다. 통합 된 고객은 휴리스틱을 기반으로 이러한 로그를 실시간으로 분석하려고 합니다. 고객은 때때로 휴리스틱의 유효성을 검사해야 하며, 지난 12 시간 동안 추출 된 데이터 샘플로 돌아가야 합니다.
고객의 요구 사항을 충족시키는 가장 좋은 방법은 무엇입니까?
A. 사용자 지정 로그를 받도록 Amazon CloudTrail 구성, EMR을 사용하여 휴리스틱을 로그에 적용
B. 모든 로그 이벤트를 Amazon Kinesis에 전송하고 로그에 휴리스틱을 적용하는 클라이언트 프로세스를 개발하십시오.
C. 모든 로그 이벤트를 Amazon SQS로 보내고 EC2 서버의 Auto Scaling 그룹을 설정하여 로그를 소비하고 휴리스틱을 적용합니다.
D. EC2 syslogd 서버의 Auto Scaling 그룹 설정, S3에 로그 저장, EMR을 사용하여 로그에 휴리스틱 적용
Answer: B
Explanation:
Explanation
The throughput of an Amazon Kinesis stream is designed to scale without limits via increasing the number of shards within a stream. However, there are certain limits you should keep in mind while using Amazon Kinesis Streams:
By default, Records of a stream are accessible for up to 24 hours from the time they are added to the stream.
You can raise this limit to up to 7 days by enabling extended data retention.
The maximum size of a data blob (the data payload before Base64-encoding) within one record is 1 megabyte (MB).
Each shard can support up to 1000 PUT records per second.
For more information about other API level limits, see Amazon Kinesis Streams Limits.