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NEW QUESTION: 1
Amazon Cognito에서 모바일 앱은 제공자의 SDK를 사용하여 자격 증명 제공자 (IdP)로 인증합니다.
최종 사용자가 IdP로 인증되면 IdP에서 반환 된 OAuth 또는 OpenID Connect 토큰이 앱에서 Amazon Cognito로 전달되어 사용자에 대한 새 _____ 및 임시 제한된 권한 AWS 자격 증명 세트를 반환합니다.
A. Cognito SDK
B. Cognito API
C. 인식 키 페어
D. 인식 ID
Answer: D
Explanation:
설명
모바일 앱은 제공자의 SDK를 사용하여 ID 제공자 (IdP)로 인증합니다. 최종 사용자가 IdP로 인증되면 IdP에서 반환 된 OAuth 또는 OpenID Connect 토큰이 앱에서 Amazon Cognito로 전달되어 사용자의 새 Cognito ID와 임시 제한된 권한 AWS 자격 증명이 반환됩니다.
http://aws.amazon.com/cognito/faqs/

NEW QUESTION: 2
CORRECT TEXT
You create a table named Sales.Orders by running the following Transact-SQL statement:

You need to write a query that removes orders from the table that have a Status of Canceled.
Construct the query using the following guidelines:

Part of the correct Transact-SQL has been provided in the answer area below. Enter the code in the answer area that resolves the problem and meets the stated goals or requirements. You can add code within the code that has been provided as well as below it.

Use the Check Syntax button to verify your work. Any syntax or spelling errors will be reported by line and character position.
Answer:
Explanation:
1. DELETE from sales.orders where status='Canceled'
Note: On line 1 change calceled to Canceled
Example: Using the WHERE clause to delete a set of rows
The following example deletes all rows from the ProductCostHistory table in the AdventureWorks2012 database in which the value in the StandardCost column is more than 1000.00.
DELETE FROM Production.ProductCostHistory
WHERE StandardCost > 1000.00;
References: https://docs.microsoft.com/en-us/sql/t-sql/statements/delete-transact-sql

NEW QUESTION: 3
Over the period of 2 to 3 weeks, a cluster displays the following:
* Periods where Warning Alerts of memory usage over 75% are asserted
* Periods where Critical Warnings of memory usage over 90% are asserted
* Periods of slow of frozen VDI desktops have caused work stoppage or slowdown
* VDI clones have periodically not powered up when called, causing work stoppage Which steps should be used to prioritize the administrator's troubleshooting efforts?
A. * Check Analysis page for CPU demand
* Verify VDI workload property for memory subscription
* Review the Hardware page to determine if the cluster has sufficient RAM
B. * Review Analysis Page for memory use pattern
* Alert with VDI workload demand
* Analyze current and future workload in the Capacity Runaway tab for sufficient resources
C. * Assess resource health on Hardware page
* Review the Analysis page for memory usage demand
* Determine the VDI workload-to-host affinity across the cluster
D. * Analyze Alert Pages for a root cause of memory problem
* Analyze VM table page to access the VM functionality
* Analyze the VDI Clone properties for possible VDI Workload stress
Answer: B

NEW QUESTION: 4
GRE / IPトンネルでの断片化のリスクを最小限に抑えるために調整されているTCP設定はどれですか。
A. MSS
B. MRU
C. Window size
D. MTU
Answer: A
Explanation:
The TCP Maximum Segment Size (TCP MSS) defines the maximum amount of data that a host
is willing to accept in a single TCP/IP datagram. This TCP/IP datagram might be fragmented at the
IP layer. The MSS value is sent as a TCP header option only in TCP SYN segments. Each side of a
TCP connection reports its MSS value to the other side. Contrary to popular belief, the MSS value
is not negotiated between hosts. The sending host is required to limit the size of data in a single
TCP segment to a value less than or equal to the MSS reported by the receiving host.
TCP MSS takes care of fragmentation at the two endpoints of a TCP connection, but it does not
handle the case where there is a smaller MTU link in the middle between these two endpoints.
PMTUD was developed in order to avoid fragmentation in the path between the endpoints. It is
used to dynamically determine the lowest MTU along the path from a packet's source to its
destination.
Reference:
25885-pmtud-ipfrag.html (there is some examples of how TCP MSS avoids IP Fragmentation
in this link but it is too long so if you want to read please visit this link)
Note: IP fragmentation involves breaking a datagram into a number of pieces that can be
reassembled later.

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