Running pyfora on AWS

If you have an Amazon Web Services account you can get pyfora running at scale within minutes. The pyfora package includes an auxiliary script called pyfora_aws, which helps get you started on AWS.

What You Need to Get Started

AWS Account

You’ll need an AWS account with an access key that has permission to launch EC2 instances. If you don’t yet have an access key, follow these instructions to create one.


The pyfora_aws tool uses boto to communicate with AWS:

pip install boto

Launch the Backend


pyfora_aws uses boto to interact with EC2 on your behalf. If you already have a Boto configuration file with your credentials then no additional configuration in needed. Otherwise, you can set your credentials using the environment variables AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY.

To set the envrionment variables, open a terminal window and type:

export AWS_ACCESS_KEY_ID=<your aws access key id>
export AWS_SECRET_ACCESS_KEY=<your aws secret key>

SSH Key-Pair

While not strictly required, it is strongly recommended that you register an SSH key-pair with EC2 and use it when launching instances. Otherwise, you will not be able to log in to the launched instances for diagnostics and troubleshooting. See Amazon EC2 Key Pairs for more information.


This tutorial assumes that you are providing an SSH key and uses SSH to tunnel traffic to/from launched instances. If you do not wish to use an SSH key, or tunnel HTTP traffic over SSH, please the the reference documentation for pyfora_aws.

Start a Backend Instance

You are now ready to start some instances using pyfora_aws. The following command will launch and configure a single c3.8xlarge on-demand instance in the us-east-1 region. It takes about 5-6 minutes to complete:

    $ pyfora_aws start --ssh-keyname <name_of_your_SSH_keypair>

    Launching manager instance:
    Mon Mar  7 10:24:42 2016 -- i-4aef5b89: pending /

    Manager instance started:

        i-4aef5b89 | | running | manager

    To tunnel the pyfora HTTP port (30000) over ssh, run the following command:
        ssh -i <ssh_key_file> -L 30000:localhost:30000 ubuntu@

    Waiting for services:

    Mon Mar  7 10:26:20 2016 -- Instance:i-4aef5b89: installing dependencies -
    Mon Mar  7 10:29:10 2016 -- Instance:i-4aef5b89: installing docker 1.9 -
    Mon Mar  7 10:30:28 2016 -- Instance:i-4aef5b89: pulling docker image -
    Mon Mar  7 10:30:51 2016 -- Instance:i-4aef5b89: launching service -
    Mon Mar  7 10:30:52 2016 -- Instance:i-4aef5b89: ready

Where <name_of_your_SSH_keypair> is the name you gave your SSH key-pair in EC2.

SSH Tunnelling

By default, to keep things secure, pyfora_aws keeps all ports on launched instances inaccessible to incoming connections, with the exception of port 22 for SSH connections. The easiest secure way to connect to the launched instance from your machine is by tunnelling pyfora’s HTTP port - 30000 - over SSH. This means that all traffic between your machine and the instance is secured by SSH.

To establish a tunnel, open a new terminal window (it will need to stay open for the duration of your session) and run:

$ ssh -i <ssh_key_file> -L 30000:localhost:30000 ubuntu@<manager_ip_address>

Where <ssh_key_file> is the path to the private key file of the SSH key-pair you specified when launching the instance, and <manager_ip_address> is the public IP address of the manager machine ( in the example above).

The -L option tells SSH to map port 30000 on your local machine to localhost:30000 on the remote.

Connect to the Backend

Now that the SSH tunnel is open you can connect to the backend using localhost:30000. To verify your connection, copy the code below to a new file:

import pyfora
executor = pyfora.connect('http://localhost:30000')

with executor.remotely.downloadAll():
    x = sum(xrange(10**9))

print x

And run it in your terminal:

$ python

Adding Instances

If you need more compute power you can easily increase the size of your cluster by launching additional instances. The following command add two more c3.8xlarge instances to your running backend:

$ pyfora_aws add -n 2
Tue Mar  7 10:52:57 2016 -- pending (2) /
Tue Mar  7 10:53:04 2016 -- running (1), pending (1) \

Workers started:
    i-3c9324ff | | running | worker
    i-149225d7 | | running | worker

Waiting for services:

Tue Mar  7 10:54:20 2016 -- installing dependencies (2) -
Tue Mar  7 10:54:37 2016 -- installing dependencies (1), installing docker 1.9 (1) \
Tue Mar  7 10:57:09 2016 -- installing docker 1.9 (2) \
Tue Mar  7 10:58:04 2016 -- installing docker 1.9 (1), pulling docker image (1) /
Tue Mar  7 10:58:37 2016 -- pulling docker image (2) -
Tue Mar  7 10:58:41 2016 -- launching service (1), pulling docker image (1) /
Tue Mar  7 11:00:01 2016 -- ready (1), pulling docker image (1) -
Tue Mar  7 11:00:17 2016 -- ready (1), launching service (1) |
Tue Mar  7 11:00:18 2016 -- ready (2)

Stopping Instances

To terminate all instances in your cluster run:

$ pyfora_aws stop --terminate
Terminating 3 instances:
    i-3c9324ff | | running | worker
    i-799423ba | | running | manager
    i-149225d7 | | running | worker