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NEW QUESTION: 1
A company is creating a software solution that executes a specific parallel-processing mechanism. The software can scale to tens of servers in some special scenarios. This solution uses a proprietary library that is license-based, requiring that each individual server have a single, dedicated license installed. The company has 200 licenses and is planning to run 200 server nodes concurrently at most. The company has requested the following features: " A mechanism to automate the use of the licenses at scale. " Creation of a dashboard to use in the future to verify which licenses are available at any moment. What is the MOST effective way to accomplish these requirements?
A. Upload the licenses to a private Amazon S3 bucket. Populate an Amazon SQS queue with the list of licenses stored in S3. Create an AWS CloudFormation template that uses an Auto Scaling group to launch the servers. In the user data script acquire an available license from SQS. Create an Auto Scaling lifecycle hook, then use it to put the license back in SQS after the instance is terminated.
B. Upload the licenses to an Amazon DynamoDB table. Create an AWS CloudFormation template that uses an Auto Scaling group to launch the servers. In the user data script, acquire an available license from the DynamoDB table. Create an Auto Scaling lifecycle hook, then use it to update the mapping after the instance is terminated.
C. Upload the licenses to an Amazon DynamoDB table. Create an AWS CLI script to launch the servers by using the parameter --count, with min:max instances to launch. In the user data script, acquire an available license from the DynamoDB table. Monitor each instance and, in case of failure, replace the instance, then manually update the DynamoDB table.
D. Upload the licenses to a private Amazon S3 bucket. Create an AWS CloudFormation template with a Mappings section for the licenses. In the template, create an Auto Scaling group to launch the servers. In the user data script, acquire an available license from the Mappings section. Create an Auto Scaling lifecycle hook, then use it to update the mapping after the instance is terminated.
Answer: C

NEW QUESTION: 2
Which two pieces of information can you determine from the output of the show ntp status command? (Choose two)
A. the configured NTP servers
B. the IP address of the peer to which the clock is synchronized
C. whether the clock is synchronized
D. the NTP version number of the peer
E. whether the NTP peer is statically configured
Answer: B,C
Explanation:
Below is the output of the "show ntp status" command. From this output we learn that R1 has a stratum of 10 and it is getting clock from 10.1.2.1.

NEW QUESTION: 3
You need to recommend the appropriate technology to provide the predictive analytics for passenger pickup.
What should you do?
A. Use Power BI to analyze the traffic data and PowerPivot to categorize the results.
B. Use Machine Learning Studio to create a predictive model and publish the results as a web service.
C. Use Hadoop on-premises to analyze the traffic and produce a report that shows high traffic zones.
D. Use HDInsight to analyze the traffic data and write a .NET program to categorize the results.
Answer: B
Explanation:
* Scenario: Predictive Routing:
/ An Azure solution must be used for prediction systems.
/ Predictive analytics must be published as a web service and accessible by using the
REST API.
* Microsoft Azure Machine Learning Studio is a collaborative visual development environment that enables you to build, test, and deploy predictive analytics solutions that operate on your data. The Machine Learning service and development environment is cloud-based, provides compute resource and memory flexibility, and eliminates setup and installation concerns because you work through your web browser.
References: https://azure.microsoft.com/en-us/documentation/articles/machine-learning- what-is-ml-studio/