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NEW QUESTION: 1
A company has two applications it wants to migrate to AWS. Both applications process a large set of files by accessing the same files at the same time. Both applications need to read the files with low latency. Which architecture should a solutions architect recommend for this situation?
A. Configure one memory optimized Amazon EC2 instance to run both applications simultaneously. Create an Amazon Elastic Block Store (Amazon EBS) volume with Provisioned IOPS to store the data.
B. Configure two AWS Lambda functions to run the applications. Create an Amazon EC2 instance with an instance store volume to store the data.
C. Configure two Amazon EC2 instances to run both applications. Configure Amazon Elastic File System (Amazon EFS) with General Purpose performance mode and Bursting Throughput mode to store the data.
D. Configure two AWS Lambda functions to run the applications. Create an Amazon EC2 instance with an Amazon Elastic Block Store (Amazon EBS) volume to store the data.
Answer: C
NEW QUESTION: 2
What are two of the characteristics of using online prediction rather than batch prediction?
A. It is optimized to handle a high volume of data instances in a job and to run more complex models.
B. Predictions are written to output files in a Cloud Storage location that you specify.
C. It is optimized to minimize the latency of serving predictions.
D. Predictions are returned in the response message.
Answer: C,D
Explanation:
Online prediction
.Optimized to minimize the latency of serving predictions.
.Predictions returned in the response message.
Batch prediction
.Optimized to handle a high volume of instances in a job and to run more complex models. .Predictions written to output files in a Cloud Storage location that you specify.
Reference: https://cloud.google.com/ml-engine/docs/prediction-
overview#online_prediction_versus_batch_prediction
NEW QUESTION: 3
한 회사가 Amazon Aurora에서 데이터베이스를 실행하고 있습니다. 데이터베이스가 매일 저녁 유휴 상태입니다. 데이터베이스에서 광범위한 읽기를 수행하는 애플리케이션은 사용자 트래픽이 급증하는 오전 시간에 성능 문제를 경험합니다. 이러한 피크 기간 동안 애플리케이션은 데이터베이스에서 읽을 때 시간 초과 오류를 수신합니다. 회사에는 전담 운영 팀이 없으며 성능 문제를 해결하기 위해 자동화 된 솔루션이 필요함 솔루션 설계자가 데이터베이스의 증가 된 읽기로드에 자동으로 조정하기 위해 취해야 하는 조치는 무엇입니까? (2 개 선택)
A. MySQL 다중 AZ 배포 용 Amazon RDS로 데이터베이스 마이그레이션
B. Aurora 복제본으로 Aurora Auto Scaling 구성
C. Aurora 데이터베이스의 인스턴스 크기 늘리기
D. 데이터베이스를 Aurora 다중 마스터 클러스터로 마이그레이션
E. 데이터베이스를 Aurora Serverless로 마이그레이션하십시오.
Answer: B,E