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Connecting to LTS

LTS is not available as a mounted filesystem on local computers or Cheaha. You must use an interface to transfer data between LTS and whichever machine you are using. There a variety of interfaces with the following recommendations.


Globus is a general file transfer system that operates through a web browser and is recommended for most file transfer needs. UAB has an S3 connector for Globus that can transfer data to and from LTS as long as the user has access to the desired buckets.

To connect to the LTS endpoint in Globus, search UAB Research Computing LTS in the search bar and enter your access and secret keys given to you by Research Computing staff. You will be able to see the buckets owned by the account associated with the keys you entered.


If your LTS account was given permission to access a bucket owned by another account, it will not automatically appear in the Globus file browser. You can access buckets you have s3:ListBucket permissions on by typing /<bucket-name>/ in the Path field under the LTS endpoint.

!Access a shared bucket in Globus

Globus is very useful for single transfers of data either to or from LTS and is available on any computer with an internet connection. However, it is currently not capable of managing buckets. This must be done through a command line interface.

Managing LTS Credentials on Globus

See our Globus - Adding LTS Allocation Credentials section for more information.

Command Line

While globus is the recommended tool for most data transfers, command line tools are necessary for planned, regular transfers as well as managing permissions on buckets. We recommend the following two tools for different purposes:

  1. s3cmd is a Python tool that we suggest using for managing bucket permissions as well as small transfers.
  2. s5cmd is a Go package that transfers data much more quickly than s3cmd, especially as the file size and/or quanitity increases. It does not have full bucket management capabilities.

You do not need to install both tools if they aren't necessary. Both are available to install into Anaconda environments. It's suggested to create a single environment named s3 and install both s3cmd and s5cmd into it for easy access to both tools. Specific install and usage commands for each are given in their respective sections. You can create the general environment using the following commands:

module load Anaconda3
conda create -n s3 -c conda-forge pip s5cmd
conda activate s3
pip install s3cmd


We manually install pip into the conda environment so that pip will install s3cmd into the conda environment as opposed to $HOME/.local. This way, you do not need to add the .local folder to your path whenever you want to use s3cmd.


s3cmd is our suggested tool for managing bucket permissions and small, periodic file transfers. See the preceding section for instructions on how to install both it and s5cmd into an Anaconda environment. Once you have s3cmd installed and the environment active, you can start the configuration process like so:

s3cmd --configure [-c $HOME/profile_name]

You can run the configuration either with or without the [-c] option. If you use it, a file named profile_name will be created in your home directory with your login credentials and other information. If you omit the -c option, a file called $HOME/.s3cfg will be created by default. This can be helpful if you have multiple S3 profiles you are using. If you use UAB LTS as your only S3 storage platform and are only managing a single account, it's suggested to omit the -c option. If you are a PI or data manager and are managing both a personal and lab/core LTS account, you will need to make a separate profile for each account.


After configuration, the s3cmd command will default to using the .s3cfg file for credentials if it exists. If you create a separate named profile file, you will need to add that to the s3cmd call each time you run it.

During configuration, you will be asked to enter some information. You can follow the example below, inputting your user-specific information where required. Lines requiring user input are highlighted.

Access key and Secret key are your identifiers for Amazon S3. Leave them empty for using the env variables.
Access Key: <access key>
Secret Key: <secret key>
Default Region [US]: <leave blank>

Use "" for S3 Endpoint and not modify it to the target Amazon S3.
S3 Endpoint []:

Use "%(bucket)" to the target Amazon S3. "%(bucket)s" and "%(location)s" vars can be used if the target S3 system supports dns based buckets.
DNS-style bucket+hostname:port template for accessing a bucket [%(bucket)]: %(bucket)

Encryption password is used to protect your files from reading by unauthorized persons while in transfer to S3
Encryption password: <leave blank or enter password>
Path to GPG program [/usr/bin/gpg]: <leave blank>

When using secure HTTPS protocol all communication with Amazon S3 servers is protected from 3rd party eavesdropping. This method is slower than plain HTTP, and can only be proxied with Python 2.7 or newer
Use HTTPS protocol [Yes]: <leave blank>

On some networks all internet access must go through a HTTP proxy. Try setting it here if you can't connect to S3 directly
HTTP Proxy server name: <leave blank>

New settings:
  Access Key: <access key>
  Secret Key: <secret key>
  Default Region: US
  S3 Endpoint:
  DNS-style bucket+hostname:port template for accessing a bucket: %(bucket)
  Encryption password:
  Path to GPG program: $HOME/bin/gpg
  Use HTTPS protocol: True
  HTTP Proxy server name:
  HTTP Proxy server port: 0

Test access with supplied credentials? [Y/n] n

Save settings? [y/N] y


If you choose to test access using your credentials, the test may fail. Do not rely on the automatic test results, test access yourself by either creating a bucket or listing files from a existing bucket using the commands listed below.

s3cmd Commands

# General command structure for s3cmd
s3cmd [-c profile_file] <command> [options] [-n --dry-run]

The [-c profile_file] is only required if you are using credentials NOT saved in the $HOME/.s3cfg file. Otherwise, you can omit it.

To see a list of all available commands, use s3cmd --help. Additionally, if you want to test an action without actually running it (i.e. it prints all actions that would be performed), you can add the -n or --dry-run option. A list of selected commands are provided below for reference

# Create a bucket
s3cmd mb s3://<bucket>

# List a bucket/path within the bucket
s3cmd ls [-r, --recursive] s3://<bucket/path>

# Check bucket or folder size
s3cmd du -H s3://<bucket/path/>

# transfer a file or folder from local to a bucket
s3cmd put <source> s3://<bucket/path/destination/>

# transfer a file or folder from a bucket to a local drive
s3cmd get s3://<bucket/path/source/> <destination>

# transfer between two S3 locations
s3cmd cp s3://<bucket/path/> s3://<bucket/path/>

# sync an S3 location with a local source. The S3 destination will be made exactly the same as the source including file deletions.
# The source is unaltered. The S3 bucket/folder can be either the source or the destination
s3cmd sync <source> s3://<bucket/path/destination>

# remove a single object or all objects within a given path
s3cmd rm s3://<bucket/path/file> [--recursive]

# remove an entire bucket
s3cmd rb s3://<bucket>

# get info about the bucket
s3cmd info s3://<bucket>


Be extremely cautious using sync. If there are files in the destination that are not in the source, it will delete those files in addition to adding files to the destination. If data is deleted from LTS, it is not recoverable.


When using ls to list buckets, it will only show the buckets you own, not buckets you have been given permissions on. This is a limitation of the S3 system. You can still interact with any buckets you have been given relevant permissions on, but you will need to remember the names of the buckets you don't own.


s5cmd is a parallel transfer tool suggested for period transfers of large and/or many files at a time. It has options for customizing how many processors are available for transferring data as well as how many chunks files can be broken into during transfer to minimize transfer time. See the preceding section for instructions on how to install both it and s3cmd into an Anaconda environment

Configuring s5cmd

s5cmd does not use the same authentication file as s3cmd. Instead, it uses official AWS SDK to access S3 including LTS. The default credentials file for AWS CLI would found at ${HOME}/.aws/credentials. This file is then populated with different profiles and their access and secret keys. You can create the necessary file with the following commands.

mkdir ${HOME}/.aws
touch ${HOME}/.aws/credentials

Open the credentials file with your favorite editor (i.e. vim, nano, gedit, etc.) and create a default profile by adding the following lines.

aws_access_key_id = <access_key>
aws_secret_access_key = <secret_key>


Do not include the <> symbols in the credentials file when saving your keys

One of the benefits of this credential method is that multiple sets of credentials can be kept in the same file. For instance, if you have both a lab/core LTS account and a personal account, you could set your personal account as the default profile and then add your lab credentials under a named profile like so:

aws_access_key_id = <personal_access_key>
aws_secret_access_key = <personal_secret_key>

aws_access_key_id = <lab_access_key>
aws_secret_access_key = <lab_secret_key>

s5cmd Commands

s5cmd has the following general form.

s5cmd --endpoint-url [global_options] command [command options] [arguments]

Here, global options must be kept separate from command specific options. For instance, the --endpoint-url option is a global option that specifies the URL for the S3 server. This must be included with every s5cmd command to communicate with UAB LTS, otherwise it will default to accessing AWS servers. Other global options include --numworkers and --profile, the number of available CPUs and which account to use in the credentials file, respectively. You can see a list of global options and the list of available commands by running s5cmd --help. A selection of commands are listed below.

# copy all files from a local directory to a bucket using a single CPU
s5cmd --endpoint-url cp /path/to/directory/* s3://bucket/

# copy all files from a local directory to a bucket using 10 CPUs  and allowing the files to be broken into 5 parts during transfer
s5cmd --endpoint-url --numworkers 10 cp --concurrency 5 /path/to/directory/* s3://bucket/

# sync an S3 bucket (destination) to a local directory (source)
s5cmd --endpoint-url sync /path/to/directory/ s3://bucket/

# remove all objects with a given prefix from a bucket
s5cmd --endpoint-url rm s3://bucket/prefix/*

As with s3cmd, be very careful using the sync and rm commands as these can/will delete files either locally or on LTS. There are many more commands s5cmd can use as well as a number of command options that can be used to customize how an operation is performed. Please see the help documentation for a full list.

It's important to note that the main functionality of s5cmd over s3cmd is the parallelization options given by the --numworkers global option and the --concurrency local option for cp and sync commands. Choosing not to use these options will result in unoptimized performance.


When setting the value for --numworkers, do not select a value beyond the number of CPUs you have requested for your job! This can cause high context switching (meaning individual CPUs are switching between multiple running processes) which can affect job performance for all jobs on a node.


There are other tools for interfacing with LTS such as rclone. Please see our rclone documentation for more details.