What is CloudEx?

Traditionally when executed on fixed clusters, tasks need to be tailored to fit the available computing resources (memory, CPU, disk size, etc...). With cloud computing the computing resources can be tailored to fit the tasks instead. CloudEx is a framework for executing jobs on cloud virtual machines. You can use the CloudEx framework to dynamically provision ephemeral computing resources to fit the tasks in hand.

Imagine you have a computational job which can be broken down into a sequence of tasks, some of which are memory intensive, others are CPU intensive or both. Other tasks are neither memory nor CPU intensive, but are used for forking and joining work. CloudEx executes such a job on the cloud by acquiring various worker VMs — called processors — with different specification to execute the tasks and deletes them once the job is done. You can statically declare the VM specification to execute each task or drive it dynamically during the job execution. The following two cloud features makes it possible for CloudEx to dynamically acquire heterogeneous and ephemeral cloud-based clusters:

In order to use CloudEx, you need to:

CloudEx architecture

CloudEx uses a coordinator component to facilitate the execution of jobs in the cloud. The coordinator can be run locally, on a VM or a remote server. The coordinator component acquires processors (VMs) to execute a job. Each processor can interact with other cloud services like storage and databases to retrieve its input data. The coordinator uses the cloud provider's metadata to instruct the processors to execute particular tasks. The processors do not communicate with each other, but they update their metadata to indicate when the current task is completed, which is then read by the coordinator. Once the job is done the coordinator deletes these processors. The high level architecture is shown below: Jobs are defined as a sequence of embarrassingly parallel tasks. Each task can be executed by the coordinator or multiple (1 to n) processors. CloudEx provides an implementation of the Bin Packing algorithm that users can use to distribute the workload for processor tasks. Each processor task can define the specification (disk, memory and CPU cores) of the VM on which it should be executed. The number and the specification of the processors that execute each task can either be defined statically in the job JSON definition or driven dynamically during the job execution.

Show me an example

Imagine you have a job that processes a number of video files to extract some data then builds a catalogue in memory before saving it to a disk. The task to process the videos is CPU intensive and can be distributed. On the other hand the task to build the catalogue is memory intensive and needs to be processed on a single VM. Assuming we are using the Google Cloud Platform, a CloudEx job can be defined as follows:

We will explain each of the major parts of the job definition. More details are provided in the documentation: Finally, once the job is done the coordinator will delete all the processors.

Getting Started

Checkout the Getting Started section on GitHub.


To find out more about CloudEx, check out the documentation.


See the CONTRIBUTING Guidelines.


Apache 2.0 - See LICENSE for more information.