Which solution will meet these requirements?
Create an S3 bucket. Create an IAM role that has permissions to write to the S3 bucket. Use the AWS CLI to copy all files locally to the S3 bucket.
Create an AWS Snowball Edge job. Receive a Snowball Edge device on premises. Use the Snowball Edge client to transfer data to the device. Return the device so that AWS can import the data into Amazon S3.
Deploy an S3 File Gateway on premises. Create a public service endpoint to connect to the S3 File Gateway. Create an S3 bucket. Create a new NFS file share on the S3 File Gateway. Point the new file share to the S3 bucket. Transfer the data from the existing NFS file share to the S3 File Gateway.
Set up an AWS Direct Connect connection between the on-premises network and AWS. Deploy an S3 File Gateway on premises. Create a public virtual interface (VIF) to connect to the S3 File Gateway. Create an S3 bucket. Create a new NFS file share on the S3 File Gateway. Point the new file share to the S3 bucket. Transfer the data from the existing NFS file share to the S3 File Gateway.
Explanations:
This method relies on the AWS CLI to transfer files over the network, which may consume a significant amount of bandwidth given the large size of files.
Using AWS Snowball Edge allows the company to physically transfer data without using network bandwidth, making it ideal for large data migrations.
While deploying an S3 File Gateway provides a way to transfer data, it still requires network bandwidth, which is not optimal given the need for low usage.
Setting up AWS Direct Connect could improve bandwidth efficiency, but it still involves transferring data over the network, which contradicts the requirements.
I measure that the answer is:
Create an AWS Snowball Edge job. Receive a Snowball Edge device on premises. Use the Snowball Edge client to transfer data to the device. Return the device so that AWS can import the data into Amazon S3.