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NEW QUESTION: 1
A developer wants to use WebServiceContext in the web service endpoint. Which of the following is the correct way to get WebServiceContext object ? (Choose one)
A. @WebService
public class MyService {
@Resource
WebServiceContext ctxt;
public String echo(String str) {
...
}
B. @WebService
public class MyService {
@Inject
WebServiceContext ctxt;
public String echo(String str) {
...
}
C. @WebService
public class MyService {
WebServiceContext ctxt;
public String echo(String str) { ctxt = jndi.lookup("java:com/env/WebServiceContext"); }
D. @WebService
public class MyService {
@WebServiceContext
WebServiceContext ctxt;
public String echo(String str) {
...
}
Answer: A

NEW QUESTION: 2
AWS에서 웹 사이트를 운영하는 회사는 높은 수준의 확장 성, 가용성 및 성능이 필요합니다. 이 회사는 Amazon EC2에서 Ruby on Rails 애플리케이션을 실행하고 있습니다. 16TB의 Amazon EBS 스토리지를 사용하는 Amazon EC2의 MySQL 5.6에 데이터 계층이 있습니다. Amazon CloudFront는 애플리케이션 콘텐츠를 캐시하는 데 사용됩니다. 운영 팀은 MySQL 데이터베이스에 할당 된 EBS 볼륨의 지속적이고 예기치 않은 증가를 보고합니다. Solutions Architect는 확장 성이 뛰어나고 가용성이 높으며 성능이 뛰어난 솔루션을 설계해야 합니다.
가장 비용 효율적인 솔루션은 무엇입니까?
A. EC2 인스턴스의 크기가 Elastic Load Balancing로드 밸런서 뒤에 있는지 확인하십시오.
EC2 인스턴스로 Auto Scaling을 구현하십시오. 예약 된 인스턴스를 고정 용량으로 구매하고 Auto Scaling 인스턴스를 요청시 실행해야합니다. Amazon Aurora MySQL 다중 AZ 클러스터로 마이그레이션합니다. 다중 AZ 아키텍처가 구현되었는지 확인하십시오.
B. EC2 인스턴스의 크기가 적절하고 Elastic Load Balancer 뒤에 있는지 확인하십시오. EC2 인스턴스로 Auto Scaling을 구현하십시오. 예약 된 인스턴스를 고정 용량으로 구매하고 Auto Scaling 인스턴스를 요청시 실행해야 합니다. Amazon Aurora MySQL 다중 AZ 클러스터로 마이그레이션합니다. 필요에 따라 Aurora MySQL 스토리지를 늘리기 위해 Aurora MySQL 스토리지 활용 및 AWS Lambda 기능에 대한 스토리지 검사를 구현합니다. 다중 AZ 아키텍처가 구현되었는지 확인하십시오.
C. Amazon ECS를 사용하여 애플리케이션에 대한 Docker 기반 컨테이너화 된 솔루션을 설계하고 구현하십시오.
Amazon Aurora MySQL 다중 AZ 클러스터로 마이그레이션합니다. 필요에 따라 Aurora MySQL 스토리지 사용 및 AWS Lambda 기능에 대한 스토리지 검사를 구현하여 Aurora MySQL 스토리지를 확장합니다.
다중 AZ 아키텍처가 구현되었는지 확인하십시오.
D. 현재 구성의 모든 EC2 인스턴스에 대해 다중 AZ 및 Auto Scaling을 구현하십시오. 모든 EC2 인스턴스가 예약 인스턴스로 구매되었는지 확인하십시오. 데이터 계층을 위한 새로운 탄력적 Amazon EBS 볼륨을 구현합니다.
Answer: A
Explanation:
A: Not scalable.
B\D: Aurora will auto grow and does not need Lambda.
The minimum storage is 10GB. Based on your database usage, your Amazon Aurora storage will automatically grow, up to 64 TB, in 10GB increments with no impact to database performance.
There is no need to provision storage in advance.

NEW QUESTION: 3
A prediction process requires access to a trained model that is stored in an Amazon S3 bucket. The process takes a few seconds to process an image and make a prediction. The process is not overly resource-intensive, does not require any specialized hardware, and takes less than 512 MB of memory to run.
What would be the MOST effective compute solution for this use case?
A. Amazon EC2 Spot instances
B. AWS Lambda functions
C. AWS Elastic Beanstalk
D. Amazon ECS
Answer: B
Explanation:
Explanation
https://docs.aws.amazon.com/lambda/latest/dg/limits.html