Amazon Web Services
As with all aspects of AWS, performance will vary depending on the resources you allocate. AWS bandwidth is a shared resource. Larger instance sizes will more often receive a larger share of AWS bandwidth. On average, you can expect the following speeds, assuming your local bandwidth is sufficient.
|c4.large||100 to 400 megabits per second|
|c4.xlarge||200 to 600 megabits per second|
|c4.2xlarge||400 to 1000 megabits per second|
|c4.4xlarge||700 to 2000 megabits per second|
c4.2xlarge will provide good performance most of the time.
To achieve maximum performance more often, choose the
c4.4xlarge instance type.
If you have a slower internet connection or do not require as much consistency, you may choose
c4.large for reduced cost.
Folders do not exist in S3 buckets.
For the purpose of listing remote files, pseudo-folders are displayed by grouping together objects sharing common name prefixes ending in "
While pseudo-folders allow you to browse the contents of a bucket as though it were organized into folders, some folder related functions will not work with S3.
Listing a bucket containing many objects may take a long time, even if they are grouped into pseudo-folders.
Data cannot move faster than your underlying network and storage hardware.
The EC2 instance hosting the CloudDat must be in the same availability region as the S3 bucket. Accessing a bucket in a different region than the gateway instance would severely limit performance.
Because each transaction must establish communication between the EC2 instance and S3, it may take several seconds for each action to start. If you are storing large numbers of files in S3, consider packaging related files as a ZIP or TAR archive, rather than storing each file as a separate object. Remember that S3 "objects" are not quite the same thing as "files", even though CloudDat will do its best to make them look like files.
Clients display the progress of uploading data to the CloudDat instance. It may take several seconds more for the data to then finish being written into S3. There may be times when S3 takes up to a minute to confirm receipt of the data.