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A tool for launching and running commands on multiple EC2 instances

Project description


Simple library and CLI to work with clusters of EC2 instances. Multi-purpose, but created to make deep learning distributed training infrastructure easier.

ec2-cluster is designed for simple distributed tasks where Kubernetes is overkill or where fast cluster spin up/down is crucial. It provides the ability to launch a cluster, to retrieve IP addresses for all nodes in the cluster, to delete the cluster and to execute commands on some or all of the instances.

Other benefits:

  • Resilient to EC2 capacity limits. If instances are not available, ec2-cluster will retry until the all nodes in the cluster are created or until the user-set timeout is reached.
  • Easy to quickly launch duplicate clusters for parallel training runs.
  • Can write orchestration logic that needs to be run when launching a cluster, e.g. enabling passwordless ssh between all instances for Horovod-based training





  • Provide the minimal set of features to run distributed deep learning training jobs on EC2 instances.
  • Provide libraries, not a framework or platform.
  • Make cluster environments reproducible to allow for parallelization of experiments
  • Make cluster launches fast
  • Be resilient to EC2 capacity limitations
  • Encourage ephemeral infrastructure design
  • Focus on iterative, not disruptive, improvements on the common methodology of manually launching EC2 instances, ssh-ing to them, configuring environments by hand and running scripts


ec2-cluster can be consumed in two ways:

  • A CLI for launching, describing and deleting clusters.
  • A python library for scripting.

This library has three main components:L

  • infra: creating cluster infrastructure
  • orch: orchestrating simple runtime cluster configuration (e.g. generate a hostfile with runtime IPs)
  • control: running commands on the cluster

CLI Quick Start

Library Quick Start

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