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A Sysops administrator creates an Amazon Elastic Kubernetes Service (Amazon EKS) cluster that uses AWS Fargate. The cluster is deployed successfully. The Sysops administrator needs to manage the cluster by using the kubect1 command line tool.
Which of the following must be configured on the Sysops administrator's machine so that kubect1 can communicate with the cluster API server?
See the explanation below.
The kubeconfig file is a configuration file used to store cluster authentication information, which is required to make requests to the Amazon EKS cluster API server. The kubeconfig file will need to be configured on the SysOps administrator's machine in order for kubectl to be able to communicate with the cluster API server.
A Sysops administrator needs to configure automatic rotation for Amazon RDS database credentials. The credentials must rotate every 30 days. The solution must integrate with Amazon RDS.
Which solution will meet these requirements with the LEAST operational overhead?
See the explanation below.
Storing the credentials in AWS Secrets Manager and configuring automatic rotation with a rotation interval of 30 days is the most efficient way to meet the requirements with the least operational overhead. AWS Secrets Manager automatically rotates the credentials at the specified interval, so there is no need for an additional AWS Lambda function or manual rotation. Additionally, Secrets Manager is integrated with Amazon RDS, so the credentials can be easily used with the RDS database.
A company has an application that runs only on Amazon EC2 Spot Instances. The instances run in an Amazon EC2 Auto Scaling group with scheduled scaling actions.
However, the capacity does not always increase at the scheduled times, and instances terminate many times a day. A Sysops administrator must ensure that the instances launch on time and have fewer interruptions.
Which action will meet these requirements?
See the explanation below.
Specifying the capacity-optimized allocation strategy for Spot Instances and adding more instance types to the Auto Scaling group is the best action to meet the requirements. Increasing the size of the instances in the Auto Scaling group will not necessarily help with the launch time or reduce interruptions, as the Spot Instances could still be interrupted even with larger instance sizes.
A company stores its data in an Amazon S3 bucket. The company is required to classify the data and find any sensitive personal information in its S3 files.
Which solution will meet these requirements?
See the explanation below.
Amazon Macie is a security service designed to help organizations find, classify, and protect sensitive data stored in Amazon S3. Amazon Macie uses machine learning to automatically discover, classify, and protect sensitive data in Amazon S3. Creating a discovery job with the managed data identifier will allow Macie to identify sensitive personal information in the S3 files and classify it accordingly. Enabling AWS Config and Amazon GuardDuty will not help with this requirement as they are not designed to automatically classify and protect data.
A company has an application that customers use to search for records on a website. The application's data is stored in an Amazon Aurora DB cluster. The application's usage varies by season and by day of the week.
The website's popularity is increasing, and the website is experiencing slower performance because of increased load on the DB cluster during periods of peak activity. The application logs show that the performance issues occur when users are searching for information. The same search is rarely performed multiple times.
A SysOps administrator must improve the performance of the platform by using a solution that maximizes resource efficiency.
Which solution will meet these requirements?
See the explanation below.
https://docs.amazonaws.cn/en_us/AmazonRDS/latest/AuroraUserGuide/aurora-replicas-adding.html
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