CLF-C02 Exam Dumps - AWS Certified Cloud Practitioner

Amazon RDS supports six database engines: Amazon Aurora, MySQL, MariaDB, PostgreSQL, Oracle, and SQL Server. Apache Cassandra, MongoDB, and Neo4j are not compatible with Amazon RDS. Therefore, the correct answer is D. You can learn more about Amazon RDS and its supported database engines

 AWS manages the encryption of the database clusters and database snapshots for Amazon Aurora, as well as the encryption keys. This is part of the AWS shared responsibility model, where AWS is responsible for the security of the cloud, and the customer is responsible for the security in the cloud. Encryption is one of the security features that AWS provides to protect the data at rest and in transit. For more information, see Amazon Aurora FAQs and AWS Shared Responsibility Model.

Amazon S3 is the AWS service that provides highly durable object storage. Amazon S3 is designed to provide 99.999999999% durability of objects over a given year. This means that you can store your data with high confidence that it will not be lost. Amazon S3 also provides high availability, scalability, security, and performance for your data. You can use Amazon S3 to store and retrieve any amount of data, at any time, from anywhere on the web5.

AWS Compute Optimizer is the AWS service or tool that provides recommendations to help users get rightsized Amazon EC2 instances based on historical workload usage data. AWS Compute Optimizer analyzes the configuration and performance characteristics of the EC2 instances and delivers recommendations for optimal instance types, sizes, and configurations. AWS Compute Optimizer helps users improve performance, reduce costs, and eliminate underutilized resources

The design principles for reliability in the AWS Cloud are:

Test recovery procedures. The best way to ensure that systems can recover from failures is to regularly test them using simulated scenarios. This can help identify gaps and improve the recovery process.

Automatically recover from failure. By using automation, systems can detect and correct failures without human intervention. This can reduce the impact and duration of failures and improve the availability of the system.

Scale horizontally to increase aggregate system availability. By adding more redundant resources to the system, the impact of individual resource failures can be reduced. This can also improve the performance and scalability of the system.

Stop guessing capacity. By using monitoring and automation, systems can adjust the capacity based on the demand and performance metrics. This can prevent failures due to insufficient or excessive capacity and optimize the cost and efficiency of the system.

Manage change in automation. By using automation, changes to the system can be applied in a consistent and controlled manner. This can reduce the risk of human errors and configuration drifts that can cause failures. AWS Well-Architected Framework