Running in AWS

Toil jobs can be run on a variety of cloud platforms. Of these, Amazon Web Services (AWS) is currently the best-supported solution. Toil provides the Cluster Utilities to conveniently create AWS clusters, connect to the leader of the cluster, and then launch a workflow. The leader handles distributing the jobs over the worker nodes and autoscaling to optimize costs.

The Running a Workflow with Autoscaling section details how to create a cluster and run a workflow that will dynamically scale depending on the workflow’s needs.

The Static Provisioning section explains how a static cluster (one that won’t automatically change in size) can be created and provisioned (grown, shrunk, destroyed, etc.).

Preparing your AWS environment

To use Amazon Web Services (AWS) to run Toil or to just use S3 to host the files during the computation of a workflow, first set up and configure an account with AWS.

  1. If necessary, create and activate an AWS account

  2. Only needed once, but AWS requires that users “subscribe” to use the Container Linux by CoreOS AMI. You will encounter errors if this is not done.

  3. Next, generate a key pair for AWS with the command (do NOT generate your key pair with the Amazon browser):

    $ ssh-keygen -t rsa
    
  4. This should prompt you to save your key. Please save it in:

    ~/.ssh/id_rsa
    
  5. Now move this to where Ubuntu can see it as an authorized key:

    $ cat ~/.ssh/id_rsa.pub >> ~/.ssh/authorized_keys
    $ eval `ssh-agent -s`
    $ ssh-add
    
  6. You’ll also need to chmod your private key (good practice but also enforced by AWS):

    $ chmod 400 id_rsa
    
  7. Now you’ll need to add the key to AWS via the browser. For example, on us-west1, this address would accessible at:

    https://us-west-1.console.aws.amazon.com/ec2/v2/home?region=us-west-1#KeyPairs:sort=keyName
    
  8. Now click on the “Import Key Pair” button to add your key.

Adding an Amazon Key Pair
  1. Next, you need to create an AWS access key. First go to the IAM dashboard, again, for “us-west1”, the example link would be here:

    https://console.aws.amazon.com/iam/home?region=us-west-1#/home
    
  2. The directions (transcribed from: https://docs.aws.amazon.com/general/latest/gr/managing-aws-access-keys.html ) are now:

    1. On the IAM Dashboard page, choose your account name in the navigation bar, and then choose My Security Credentials.
    2. Expand the Access keys (access key ID and secret access key) section.
    3. Choose Create New Access Key. Then choose Download Key File to save the access key ID and secret access key to a file on your computer. <strong><em>After you close the dialog box, you can’t retrieve this secret access key again.
  3. Now you should have a newly generated “AWS Access Key ID” and “AWS Secret Access Key”. We can now install the AWS CLI and make sure that it has the proper credentials:

    $ pip install awscli --upgrade --user
    
  4. Now configure your AWS credentials with:

    $ aws configure
    
  5. Add your “AWS Access Key ID” and “AWS Secret Access Key” from earlier and your region and output format:

    " AWS Access Key ID [****************Q65Q]: "
    " AWS Secret Access Key [****************G0ys]: "
    " Default region name [us-west-1]: "
    " Default output format [json]: "
    
  6. Toil also relies on boto, and you’ll need to create a boto file containing your credentials as well. To do this, run:

    $ nano ~/.boto
    
  7. Paste in the following (with your actual “AWS Access Key ID” and “AWS Secret Access Key”):

    [Credentials]
    aws_access_key_id = ****************Q65Q
    aws_secret_access_key = ****************G0ys
    
  8. If not done already, install toil (example uses version 3.12.0, but we recommend the latest release):

    $ virtualenv venv
    $ source venv/bin/activate
    $ pip install toil[all]==3.12.0
    
  9. Now that toil is installed and you are running a virtualenv, an example of launching a toil leader node would be (again, note that we set TOIL_APPLIANCE_SELF to toil version 3.12.0 in this example, but please set the version to the installed version that you are using if you’re using a different version):

    $ TOIL_APPLIANCE_SELF=quay.io/ucsc_cgl/toil:3.12.0 toil launch-cluster clustername --leaderNodeType t2.medium --zone us-west-1a --keyPairName id_rsa
    

To further break down each of these commands:

TOIL_APPLIANCE_SELF=quay.io/ucsc_cgl/toil:latest - This is optional. It specifies a mesos docker image that we maintain with the latest version of toil installed on it. If you want to use a different version of toil, please specify the image tag you need from: https://quay.io/repository/ucsc_cgl/toil?tag=latest&tab=tags

toil launch-cluster - Base command in toil to launch a cluster.

clustername - Just choose a name for your cluster.

–leaderNodeType t2.medium - Specify the leader node type. Make a t2.medium (2CPU; 4Gb RAM; $0.0464/Hour). List of available AWS instances: https://aws.amazon.com/ec2/pricing/on-demand/

–zone us-west-1a - Specify the AWS zone you want to launch the instance in. Must have the same prefix as the zone in your awscli credentials (which, in the example of this tutorial is: “us-west-1”).

–keyPairName id_rsa - The name of your key pair, which should be “id_rsa” if you’ve followed this tutorial.

AWS Job Store

Using the AWS job store is straightforward after you’ve finished Preparing your AWS environment, all you need to do is specify the prefix for the job store name.

To run the sort example sort example with the AWS job store you would type

$ python sort.py aws:us-west-2:my-aws-sort-jobstore

Toil Provisioner

The Toil provisioner is included in Toil alongside the [aws] extra and allows us to spin up a cluster.

Getting started with the provisioner is simple:

  1. Make sure you have Toil installed with the AWS extras. For detailed instructions see Installing Toil with Extra Features.
  2. You will need an AWS account and you will need to save your AWS credentials on your local machine. For help setting up an AWS account see here. For setting up your aws credentials follow instructions here.

The Toil provisioner is built around the Toil Appliance, a Docker image that bundles Toil and all its requirements (e.g. Mesos). This makes deployment simple across platforms, and you can even simulate a cluster locally (see Developing with Docker for details).

Choosing Toil Appliance Image

When using the Toil provisioner, the appliance image will be automatically chosen based on the pip installed version of Toil on your system. That choice can be overriden by setting the environment variables TOIL_DOCKER_REGISTRY and TOIL_DOCKER_NAME or TOIL_APPLIANCE_SELF. See Environment Variables for more information on these variables. If you are developing with autoscaling and want to test and build your own appliance have a look at Developing with Docker.

For information on using the Toil Provisioner have a look at Running a Workflow with Autoscaling.

Details about Launching a Cluster in AWS

Using the provisioner to launch a Toil leader instance is simple using the launch-cluster command. For example, to launch a cluster named “my-cluster” with a t2.medium leader in the us-west-2a zone, run:

(venv) $ toil launch-cluster my-cluster --leaderNodeType t2.medium --zone us-west-2a --keyPairName <your-AWS-key-pair-name>

The cluster name is used to uniquely identify your cluster and will be used to populate the instance’s Name tag. In addition, the Toil provisioner will automatically tag your cluster with an Owner tag that corresponds to your keypair name to facilitate cost tracking.

The leaderNodeType is an EC2 instance type. This only affects the leader node.

The --zone parameter specifies which EC2 availability zone to launch the cluster in. Alternatively, you can specify this option via the TOIL_AWS_ZONE environment variable. Note: the zone is different from an EC2 region. A region corresponds to a geographical area like us-west-2 (Oregon), and availability zones are partitions of this area like us-west-2a.

For more information on options try:

(venv) $ toil launch-cluster --help

Static Provisioning

Toil can be used to manage a cluster in the cloud by using the Cluster Utilities. The cluster utilities also make it easy to run a toil workflow directly on this cluster. We call this static provisioning because the size of the cluster does not change. This is in contrast with Running a Workflow with Autoscaling.

To launch worker nodes alongside the leader we use the -w option.:

(venv) $ 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

This will spin up a leader node of type t2.small with five additional workers - one m3.large instance and four t2.micro.

Currently static provisioning is only possible during the cluster’s creation. The ability to add new nodes and remove existing nodes via the native provisioner is in development. Of course the cluster can always be deleted with the destroy-cluster Command utility.

Uploading Workflows

Now that our cluster is launched, we use the Rsync-Cluster Command utility to copy the workflow to the leader. For a simple workflow in a single file this might look like:

(venv) $ toil rsync-cluster -z us-west-2a my-cluster toil-workflow.py :/

Note

If your toil workflow has dependencies have a look at the Auto-Deployment section for a detailed explanation on how to include them.

Running a Workflow with Autoscaling

Autoscaling is a feature of running Toil in a cloud whereby additional cloud instances are launched to run the workflow. Autoscaling leverages Mesos containers to provide an execution environment for these workflows.

Note

Make sure you’ve done the AWS setup in Preparing your AWS environment.

  1. Download sort.py.

  2. Launch the leader node in AWS using the Launch-Cluster Command command:

    (venv) $ toil launch-cluster <cluster-name> --keyPairName <AWS-key-pair-name> --leaderNodeType t2.medium --zone us-west-2a
    
  3. Copy the sort.py script up to the leader node:

    (venv) $ toil rsync-cluster <cluster-name> sort.py :/root
    
  4. Login to the leader node:

    (venv) $ toil ssh-cluster <cluster-name>
    
  5. Run the script as an autoscaling workflow:

    $ python /root/sort.py aws:us-west-2:<my-jobstore-name> --provisioner aws --nodeTypes c3.large --maxNodes 2 --batchSystem mesos
    

Note

In this example, the autoscaling Toil code creates up to two instances of type c3.large and launches Mesos slave containers inside them. The containers are then available to run jobs defined by the sort.py script. Toil also creates a bucket in S3 called aws:us-west-2:autoscaling-sort-jobstore to store intermediate job results. The Toil autoscaler can also provision multiple different node types, which is useful for workflows that have jobs with varying resource requirements. For example, one could execute the script with --nodeTypes c3.large,r3.xlarge --maxNodes 5,1, which would allow the provisioner to create up to five c3.large nodes and one r3.xlarge node for memory-intensive jobs. In this situation, the autoscaler would avoid creating the more expensive r3.xlarge node until needed, running most jobs on the c3.large nodes.

  1. View the generated file to sort.

    $ head fileToSort.txt
    
  2. View the sorted file.

    $ head sortedFile.txt
    

For more information on other autoscaling (and other) options have a look at Commandline Options and/or run:

$ python my-toil-script.py --help

Important

Some important caveats about starting a toil run through an ssh session are explained in the Ssh-Cluster Command section.

Preemptability

Toil can run on a heterogeneous cluster of both preemptable and non-preemptable nodes. Being preemptable node simply means that the node may be shut down at any time, while jobs are running. These jobs can then be restarted later somewhere else.

A node type can be specified as preemptable by adding a spot bid to its entry in the list of node types provided with the --nodeTypes flag. If spot instance prices rise above your bid, the preemptable node whill be shut down.

While individual jobs can each explicitly specify whether or not they should be run on preemptable nodes via the boolean preemptable resource requirement, the --defaultPreemptable flag will allow jobs without a preemptable requirement to run on preemptable machines.

Specify Preemptability Carefully

Ensure that your choices for --nodeTypes and --maxNodes <> make sense for your workflow and won’t cause it to hang. You should make sure the provisioner is able to create nodes large enough to run the largest job in the workflow, and that non-preemptable node types are allowed if there are non-preemptable jobs in the workflow.

Finally, the --preemptableCompensation flag can be used to handle cases where preemptable nodes may not be available but are required for your workflow. With this flag enabled, the autoscaler will attempt to compensate for a shortage of preemptable nodes of a certain type by creating non-preemptable nodes of that type, if non-preemptable nodes of that type were specified in --nodeTypes.

Dashboard

Toil provides a dashboard for viewing the RAM and CPU usage of each node, the number of issued jobs of each type, the number of failed jobs, and the size of the jobs queue. To launch this dashboard for a toil workflow, include the --metrics flag in the toil script command. The dashboard can then be viewed in your browser at localhost:3000 while connected to the leader node through toil ssh-cluster. On AWS, the dashboard keeps track of every node in the cluster to monitor CPU and RAM usage, but it can also be used while running a workflow on a single machine. The dashboard uses Grafana as the front end for displaying real-time plots, and Prometheus for tracking metrics exported by toil. In order to use the dashboard for a non-released toil version, you will have to build the containers locally with make docker, since the prometheus, grafana, and mtail containers used in the dashboard are tied to a specific toil version.