A healthcare organization is looking to store highly confidential patient records in an Amazon S3 bucket. The storage solution must comply with regulatory standards that require not only encryption of data at rest but also stringent control and auditing over who can access the encryption keys. Since their IT team lacks the resources to manage encryption processes manually, they need an encryption method that is both secure and manageable within their AWS environment.

What encryption method should they use for their S3 bucket to ensure compliance with these standards?

A digital media company processes large volumes of image and video files daily. These files are stored in an Amazon S3 bucket. The company needs to analyze metadata extracted from these files (such as file size, type, creation date) and store this information for quick retrieval and analysis. The solution should automatically handle new files as they are uploaded and be scalable to handle increasing data volumes.

Which AWS service should the company implement to extract, store, and manage the metadata efficiently?

A retail company uses Amazon Aurora to manage inventory data. The company's Aurora DB cluster resides in a private subnet. A team member has created an AWS Lambda function to manage inventory levels within the Aurora DB cluster. To maintain data security, the company wants to ensure that this Lambda function can access the Aurora DB cluster only through the private network.

What steps should be taken to enable private connectivity from the Lambda function to the Aurora DB cluster with minimal administrative effort? (Select TWO.)

A healthcare application hosted on AWS uses Amazon EC2 instances to manage sensitive patient data that must comply with regulatory security standards. The data is stored on EBS volumes attached to the EC2 instances. The company's security policy mandates that all data at rest be encrypted to protect against unauthorized access.

Which action should the IT department take to secure the EBS volumes in accordance with the company's security policy?

Your company's Cloud Data Engineering team is using Amazon Kinesis Data Streams to process real-time streaming data from IoT devices. The stream is configured with 4 shards. Lately, the team observes that during peak operational hours, there are intermittent delays in data processing and some records appear to be dropped. The team is using a custom Kinesis consumer application for data processing.

What initial step should the team take to begin troubleshooting these performance issues?