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NEW QUESTION: 1
Sie haben ein Azure Migrate-Projekt mit den folgenden Bewertungseigenschaften:
* Zielort: Osten der USA
* Speicherredundanz: Lokal redundant
* Wohlfühlfaktor: 2,0
* Leistungsverlauf: 1 Monat
* Perzentilauslastung: 95
* Preisstufe: Standard
* Angebot: Bezahlen Sie, während Sie gehen
Sie entdecken die folgenden zwei virtuellen Maschinen:
* Eine virtuelle Maschine mit dem Namen VM1, auf der Windows Server 2016 ausgeführt wird und die 10 CPU-Kerne bei 20 Prozent Auslastung aufweist
* Eine virtuelle Maschine mit dem Namen VM2, auf der Windows Server 2012 ausgeführt wird und die vier CPU-Kerne mit einer Auslastung von 50 Prozent aufweist. Wie viele CPU-Kerne empfiehlt Azure Migrate für jede virtuelle Maschine? Wählen Sie zum Beantworten die entsprechenden Optionen im Antwortbereich aus.
HINWEIS: Jede richtige Auswahl ist einen Punkt wert.
Answer:
Explanation:
Explanation
The equation is: 'core usage x comfort factor'. The comfort factor is 2.0.
So VM 1 is 10 cores at 20% utilization which equals 2 cores. Multiply that the comfort factor and you get 4 cores.
VM 2 is 4 cores at 50% utilization which equals 2 cores. Multiply that the comfort factor and you get 4 cores.
NEW QUESTION: 2
You are designing a SQL Server Integration Services (SSIS) data flow to load sales transactions from a source system into a data warehouse hosted on Windows Azure SQL Database. One of the columns in the data source is named ProductCode.
Some of the data to be loaded will reference products that need special processing logic in the data flow.
You need to enable separate processing streams for a subset of rows based on the source product code.
Which Data Flow transformation should you use?
A. Conditional Split
B. Script Task
C. Multicast
D. Data Conversion
Answer: B
NEW QUESTION: 3
During a review of a customer master file, an IS auditor discovered numerous customer name duplications arising from variations in customer first names. To determine the extent of the duplication, the IS auditor would use:
A. generalized audit software to search for account field duplications.
B. test data to validate data input.
C. generalized audit software to search for address field duplications.
D. test data to determine system sort capabilities.
Answer: C
Explanation:
Explanation/Reference:
Explanation:
Since the name is not the same {due to name variations), one method to detect duplications would be to compare other common fields, such as addresses. A subsequent review to determine common customer names at these addresses could then be conducted. Searching for duplicate account numbers would not likely find duplications, since customers would most likely have different account numbers for each variation. Test data would not be useful to detect the extent of any data characteristic, but simply to determine how the data were processed.
NEW QUESTION: 4
A company's main intranet page has experienced degraded response times as its user base has increased although there are no reports of users seeing error pages. The application uses Amazon DynamoDB in read-only mode.
Amazon DynamoDB latency metrics for successful requests have been in a steady state even during times when users have reported degradation The Development team has correlated the issue to ProvisionedThrough put Exceeded exceptions in the application logs when doing Scan and read operations The team also identified an access pattern of steady spikes of read activity on a distributed set of individual data items The Chief Technology Officer wants to improve the user experience Which solutions will meet these requirements with the LEAST amount of changes to the application? (Select TWO )
A. Change the data model of the DynamoDB tables to ensure that all Scan and read operations meet DynamoDB best practices of uniform data access, reaching the full request throughput provisioned for the DynamoDB tables
B. Provision Amazon ElastiCache for Redis with cluster mode enabled The cluster should be provisioned with enough shards to spread the application load and provision at least one read replica node for each shard
C. Implement the DynamoDB Accelerator (DAX) client and provision a DAX cluster with the appropriate node types to sustain the application load. Tune the item and query cache configuration for an optimal user experience
D. Enable DynamoDB auto scaling to manage the throughput capacity as table traffic increases Set the upper and lower limits to control costs and set a target utilization given the peak usage and how quickly the traffic changes.
E. Remove error retries and exponential backoffs in the application code to handle throttling errors
Answer: A,E
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