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Exam Code: Databricks-Generative-AI-Engineer-Associate Dumps

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NEW QUESTION: 1

A. InnoDB
B. MyISAM
Answer: A

NEW QUESTION: 2
Your system is giving error while booting on Runlevel 5 . Make successfully boot your system in runlevel 5.
A. While you load the X Window System, you will get the problem. To troubleshoot follow the following steps:
Check the /tmp is full ?
Check your quota, hard limit is already crossed ?
Check xfs service is running ?
Configure the Video card, Resolution, monitor type using: system-configdisplay (Most Probably in Redhat exam)
Edit the /etc/inittab to set default runlevel 4. id:6:initdefault:
B. While you load the X Window System, you will get the problem. To troubleshoot follow the following steps:
Check the /tmp is full ?
Check your quota, hard limit is already crossed ?
Check xfs service is running ?
Configure the Video card, Resolution, monitor type using: system-configdisplay (Most Probably in Redhat exam)
Edit the /etc/inittab to set default runlevel 5. id:5:initdefault:
Answer: B

NEW QUESTION: 3
Your company releases new features with high frequency while demanding high application availability. As part of the application's A/B testing, logs from each updated Amazon EC2 instance of the application need to be analyzed in near real-time, to ensure that the application is working flawlessly after each deployment. If the logs show any anomalous behavior, then the application version of the instance is changed to a more stable one. Which of the following methods should you use for shipping and analyzing the logs in a highly available manner?
A. Ship the logs to Amazon CloudWatch Logs and use Amazon EMR to analyze the logs in a batch manner each hour.
B. Ship the logs to a large Amazon EC2 instance and analyze the logs in a live manner.
C. Ship the logs to an Amazon Kinesis stream and have the consumers analyze the logs in a live manner.
D. Ship the logs to Amazon S3 for durability and use Amazon EMR to analyze the logs in a batch manner each hour.
Answer: C
Explanation:
Explanation
Answer - C
You can use Kinesis Streams for rapid and continuous data intake and aggregation. The type of data used includes IT infrastructure log data, application logs, social media, market data feeds, and web clickstream data. Because the response time for the data intake and processing is in real time, the processing is typically lightweight.
The following are typical scenarios for using Kinesis Streams:
* Accelerated log and data feed intake and processing - You can have producers push data directly into a stream. For example, push system and application logs and they'll be available for processing in seconds. This prevents the log data from being lost if the front end or application server fails. Kinesis Streams provides accelerated data feed intake because you don't batch the data on the servers before you submit it for intake.
* Real-time metrics and reporting - You can use data collected into Kinesis Streams for simple data analysis and reporting in real time. For example, your data-processing application can work on metrics and reporting for system and application logs as the data is streaming in, rather than wait to receive batches of data.
For more information on Amazon Kinesis and SNS please refer to the below link:
* http://docs.aws.a
mazon.com/streams/latest/dev/introduction.html


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