Cluster Utilities

There are several utilities used for starting and managing a Toil cluster using the AWS provisioner. They are installed via the [aws] or [google] extra. For installation details see Toil Provisioner. The cluster utilities are used for Running in AWS and are comprised of toil launch-cluster, toil rsync-cluster, toil ssh-cluster, and toil destroy-cluster entry points.

Cluster commands specific to toil are:

status — Reports runtime and resource usage for all jobs in a specified jobstore (workflow must have originally been run using the --stats option).

stats — Inspects a job store to see which jobs have failed, run successfully, etc.

destroy-cluster — For autoscaling. Terminates the specified cluster and associated resources.

launch-cluster — For autoscaling. This is used to launch a toil leader instance with the specified provisioner.

rsync-cluster — For autoscaling. Used to transfer files to a cluster launched with toil launch-cluster.

ssh-cluster — SSHs into the toil appliance container running on the leader of the cluster.

clean — Delete the job store used by a previous Toil workflow invocation.

kill — Kills any running jobs in a rogue toil.

For information on a specific utility run:

toil launch-cluster --help

for a full list of its options and functionality.

The cluster utilities can be used for Running in Google Compute Engine (GCE) and Running in AWS.


By default, all of the cluster utilities expect to be running on AWS. To run with Google you will need to specify the --provisioner gce option for each utility.


Boto must be configured with AWS credentials before using cluster utilities.

Running in Google Compute Engine (GCE) contains instructions for

Stats Command

To use the stats command, a workflow must first be run using the --stats option. Using this command makes certain that toil does not delete the job store, no matter what other options are specified (i.e. normally the option --clean=always would delete the job, but --stats will override this).

An example of this would be running the following:

python file:my-jobstore --stats

Where is the following:

import os
import subprocess

from toil.common import Toil
from toil.job import Job

class discoverFiles(Job):
    """Views files at a specified path using ls."""

    def __init__(self, path, *args, **kwargs):
        self.path = path
        super().__init__(*args, **kwargs)

    def run(self, fileStore):
        if os.path.exists(self.path):
            subprocess.check_call(["ls", self.path])

def main():
    options = Job.Runner.getDefaultArgumentParser().parse_args()
    options.clean = "always"

    job1 = discoverFiles(path="/sys/", displayName='sysFiles')
    job2 = discoverFiles(path=os.path.expanduser("~"), displayName='userFiles')
    job3 = discoverFiles(path="/tmp/")


    with Toil(options) as toil:
        if not toil.options.restart:

if __name__ == '__main__':

Notice the displayName key, which can rename a job, giving it an alias when it is finally displayed in stats. Running this workflow file should record three job names: sysFiles (job1), userFiles (job2), and discoverFiles (job3). To see the runtime and resources used for each job when it was run, type

toil stats file:my-jobstore

This should output the following:

Batch System: singleMachine
Default Cores: 1  Default Memory: 2097152K
Max Cores: 9.22337e+18
Total Clock: 0.56  Total Runtime: 1.01
    Count |                                    Time* |                                    Clock |                                     Wait |                                   Memory
        n |      min    med*     ave     max   total |      min     med     ave     max   total |      min     med     ave     max   total |      min     med     ave     max   total
        1 |     0.14    0.14    0.14    0.14    0.14 |     0.13    0.13    0.13    0.13    0.13 |     0.01    0.01    0.01    0.01    0.01 |      76K     76K     76K     76K     76K
 Worker Jobs  |     min    med    ave    max
              |       3      3      3      3
    Count |                                    Time* |                                    Clock |                                     Wait |                                   Memory
        n |      min    med*     ave     max   total |      min     med     ave     max   total |      min     med     ave     max   total |      min     med     ave     max   total
        3 |     0.01    0.06    0.05    0.07    0.14 |     0.00    0.06    0.04    0.07    0.12 |     0.00    0.01    0.00    0.01    0.01 |      76K     76K     76K     76K    229K
    Count |                                    Time* |                                    Clock |                                     Wait |                                   Memory
        n |      min    med*     ave     max   total |      min     med     ave     max   total |      min     med     ave     max   total |      min     med     ave     max   total
        1 |     0.01    0.01    0.01    0.01    0.01 |     0.00    0.00    0.00    0.00    0.00 |     0.01    0.01    0.01    0.01    0.01 |      76K     76K     76K     76K     76K
    Count |                                    Time* |                                    Clock |                                     Wait |                                   Memory
        n |      min    med*     ave     max   total |      min     med     ave     max   total |      min     med     ave     max   total |      min     med     ave     max   total
        1 |     0.06    0.06    0.06    0.06    0.06 |     0.06    0.06    0.06    0.06    0.06 |     0.01    0.01    0.01    0.01    0.01 |      76K     76K     76K     76K     76K
    Count |                                    Time* |                                    Clock |                                     Wait |                                   Memory
        n |      min    med*     ave     max   total |      min     med     ave     max   total |      min     med     ave     max   total |      min     med     ave     max   total
        1 |     0.07    0.07    0.07    0.07    0.07 |     0.07    0.07    0.07    0.07    0.07 |     0.00    0.00    0.00    0.00    0.00 |      76K     76K     76K     76K     76K

Once we’re done, we can clean up the job store by running

toil clean file:my-jobstore

Status Command

Continuing the example from the stats section above, if we ran our workflow with the command

python file:my-jobstore --stats

We could interrogate our jobstore with the status command, for example:

toil status file:my-jobstore

If the run was successful, this would not return much valuable information, something like

2018-01-11 19:31:29,739 - toil.lib.bioio - INFO - Root logger is at level 'INFO', 'toil' logger at level 'INFO'.
2018-01-11 19:31:29,740 - toil.utils.toilStatus - INFO - Parsed arguments
2018-01-11 19:31:29,740 - toil.utils.toilStatus - INFO - Checking if we have files for Toil
The root job of the job store is absent, the workflow completed successfully.

Otherwise, the status command should return the following:

There are x unfinished jobs, y parent jobs with children, z jobs with services, a services, and b totally failed jobs currently in c.

Clean Command

If a Toil pipeline didn’t finish successfully, or was run using --clean=always or --stats, the job store will exist until it is deleted. toil clean <jobStore> ensures that all artifacts associated with a job store are removed. This is particularly useful for deleting AWS job stores, which reserves an SDB domain as well as an S3 bucket.

The deletion of the job store can be modified by the --clean argument, and may be set to always, onError, never, or onSuccess (default).

Temporary directories where jobs are running can also be saved from deletion using the --cleanWorkDir, which has the same options as --clean. This option should only be run when debugging, as intermediate jobs will fill up disk space.

Launch-Cluster Command

Running toil launch-cluster starts up a leader for a cluster. Workers can be added to the initial cluster by specifying the -w option. An example would be

$ toil launch-cluster my-cluster \
      --leaderNodeType t2.small -z us-west-2a \
      --keyPairName your-AWS-key-pair-name \
      --nodeTypes m3.large,t2.micro -w 1,4

Options are listed below. These can also be displayed by running

$ toil launch-cluster --help

launch-cluster’s main positional argument is the clusterName. This is simply the name of your cluster. If it does not exist yet, Toil will create it for you.

Launch-Cluster Options

--help -h also accepted. Displays this help menu.
 Path to the temporary directory where all temp files are created, by default uses the current working directory as the base.
--version Display version.
--provisioner CLOUDPROVIDER
 -p CLOUDPROVIDER also accepted. The provisioner for cluster auto-scaling. Both AWS and GCE are currently supported.
--zone ZONE -z ZONE also accepted. The availability zone of the leader. This parameter can also be set via the TOIL_AWS_ZONE or TOIL_GCE_ZONE environment variables, or by the ec2_region_name parameter in your .boto file if using AWS, or derived from the instance metadata if using this utility on an existing EC2 instance.
 Non-preemptable node type to use for the cluster leader.
 The name of the AWS or ssh key pair to include on the instance.
--owner OWNER The owner tag for all instances. If not given, the value in TOIL_OWNER_TAG will be used, or else the value of –keyPairName.
 The path to the boto credentials directory. This is transferred to all nodes in order to access the AWS jobStore from non-AWS instances.
--tag KEYVALUE KEYVALUE is specified as KEY=VALUE. -t KEY=VALUE also accepted. Tags are added to the AWS cluster for this node and all of its children. Tags are of the form: -t key1=value1 –tag key2=value2. Multiple tags are allowed and each tag needs its own flag. By default the cluster is tagged with: { “Name”: clusterName, “Owner”: IAM username }.
--vpcSubnet VPCSUBNET
 VPC subnet ID to launch cluster leader in. Uses default subnet if not specified. This subnet needs to have auto assign IPs turned on.
--nodeTypes NODETYPES
 Comma-separated list of node types to create while launching the leader. The syntax for each node type depends on the provisioner used. For the AWS provisioner this is the name of an EC2 instance type followed by a colon and the price in dollars to bid for a spot instance, for example ‘c3.8xlarge:0.42’. Must also provide the –workers argument to specify how many workers of each node type to create.
--workers WORKERS
 -w WORKERS also accepted. Comma-separated list of the number of workers of each node type to launch alongside the leader when the cluster is created. This can be useful if running toil without auto-scaling but with need of more hardware support.
--leaderStorage LEADERSTORAGE
 Specify the size (in gigabytes) of the root volume for the leader instance. This is an EBS volume.
--nodeStorage NODESTORAGE
 Specify the size (in gigabytes) of the root volume for any worker instances created when using the -w flag. This is an EBS volume.
 Comma-separated list of nodeType:nodeStorage that are used to override the default value from –nodeStorage for the specified nodeType(s). This is useful for heterogeneous jobs where some tasks require much more disk than others.

Logging Options

--logOff Same as --logCritical.
--logCritical Turn on logging at level CRITICAL and above. (default is INFO)
--logError Turn on logging at level ERROR and above. (default is INFO)
--logWarning Turn on logging at level WARNING and above. (default is INFO)
--logInfo Turn on logging at level INFO and above. (default is INFO)
--logDebug Turn on logging at level DEBUG and above. (default is INFO)
--logLevel LOGLEVEL
 Log at given level (may be either OFF (or CRITICAL), ERROR, WARN (or WARNING), INFO or DEBUG). (default is INFO)
--logFile LOGFILE
 File to log in.
 Turn on rotating logging, which prevents log files getting too big.

Ssh-Cluster Command

Toil provides the ability to ssh into the leader of the cluster. This can be done as follows:

$ toil ssh-cluster CLUSTER-NAME-HERE

This will open a shell on the Toil leader and is used to start an Running a Workflow with Autoscaling run. Issues with docker prevent using screen and tmux when sshing the cluster (The shell doesn’t know that it is a TTY which prevents it from allocating a new screen session). This can be worked around via

$ script
$ screen

Simply running screen within script will get things working properly again.

Finally, you can execute remote commands with the following syntax:

$ toil ssh-cluster CLUSTER-NAME-HERE remoteCommand

It is not advised that you run your Toil workflow using remote execution like this unless a tool like nohup is used to ensure the process does not die if the SSH connection is interrupted.

For an example usage, see Running a Workflow with Autoscaling.

Rsync-Cluster Command

The most frequent use case for the rsync-cluster utility is deploying your Toil script to the Toil leader. Note that the syntax is the same as traditional rsync with the exception of the hostname before the colon. This is not needed in toil rsync-cluster since the hostname is automatically determined by Toil.

Here is an example of its usage:

$ toil rsync-cluster CLUSTER-NAME-HERE \
   ~/localFile :/remoteDestination

Destroy-Cluster Command

The destroy-cluster command is the advised way to get rid of any Toil cluster launched using the Launch-Cluster Command command. It ensures that all attached nodes, volumes, security groups, etc. are deleted. If a node or cluster is shut down using Amazon’s online portal residual resources may still be in use in the background. To delete a cluster run

$ toil destroy-cluster CLUSTER-NAME-HERE

Kill Command

To kill all currently running jobs for a given jobstore, use the command

toil kill file:my-jobstore