Which approach has the least risk and the highest likelihood of a successful data transfer?
Set up a VPN tunnel for encrypting data over the network from the data center to AWS. Leverage AWS SCT and apply the converted schema to Amazon Redshift. Once complete, start an AWS DMS task to move the data from the source to Amazon S3. Use AWS Glue to load the data from Amazon S3 to Amazon Redshift.
Leverage AWS SCT and apply the converted schema to Amazon Redshift. Start an AWS DMS task with two AWS Snowball Edge devices to copy data from on-premises to Amazon S3 with AWS KMS encryption. Use AWS DMS to finish copying data to Amazon Redshift.
Leverage AWS SCT and apply the converted schema to Amazon Redshift. Once complete, use a fleet of 10 TB dedicated encrypted drives using the AWS Import/Export feature to copy data from on-premises to Amazon S3 with AWS KMS encryption. Use AWS Glue to load the data to Amazon redshift.
Set up a VPN tunnel for encrypting data over the network from the data center to AWS. Leverage a native database export feature to export the data and compress the files. Use the aws S3 cp multi-port upload command to upload these files to Amazon S3 with AWS KMS encryption. Once complete, load the data to Amazon Redshift using AWS Glue.
Explanations:
While setting up a VPN for secure data transfer is a good practice, the approach relies solely on AWS DMS to transfer data, which may not efficiently handle the large volume of data (100 TB) over a 500 Mbps connection within the 2-week window. This could lead to prolonged downtime and increased risk of data loss.
This approach effectively uses AWS Snowball Edge devices to securely transfer the large amount of data to Amazon S3 with KMS encryption, which is suitable for a 100 TB dataset. The use of AWS DMS to complete the data transfer to Redshift after Snowball ensures minimal risk and efficient handling of the migration, keeping encryption intact.
Using a fleet of 10 TB dedicated encrypted drives with the AWS Import/Export feature can be complex and less efficient for a 100 TB dataset. The logistics of managing multiple drives and potential delays in shipping can introduce risks, making it less ideal compared to the Snowball approach. Additionally, the use of AWS Glue may not be as seamless as using DMS for moving data directly to Redshift.
This option relies on a VPN for encryption, which is good, but it uses a native export and manual file upload method that may not be efficient for a 100 TB dataset. The S3 cp multi-port upload command might not provide the same efficiency as AWS DMS or Snowball for such a large volume of data, risking delays and potential failures in transferring all data within the limited timeframe.
I conclude that the answer is:
Leverage AWS SCT and apply the converted schema to Amazon Redshift. Start an AWS DMS task with two AWS Snowball Edge devices to copy data from on-premises to Amazon S3 with AWS KMS encryption. Use AWS DMS to finish copying data to Amazon Redshift.