AWSClusterManagers

Julia cluster managers which run within the AWS infrastructure.

Installation

Pkg.add("AWSClusterManagers")

Testing

Testing AWSClusterManagers can be performed on your local system using:

Pkg.test("AWSClusterManagers")

Adjustments can be made to the tests with the environmental variables ONLINE and STACK_NAME:

• ONLINE: Should contain a comma separated list which contain elements from the set "docker" and/or "batch". Including "docker" will run the online Docker tests (requires Docker to be installed) and "batch" will run AWS Batch tests (see STACK_NAME for details).
• STACK_NAME: Set the AWS Batch tests to use the stack specified. It is expected that the stack already exists in the current AWS profile. Note that STACK_NAME is only used if ONLINE contains "batch".

Online Docker tests

To run the online Docker tests you'll need to have Docker installed. Additionally you'll also need access to pull down the image "468665244580.dkr.ecr.us-east-1.amazonaws.com/julia-baked" using your current AWS profile. If your current profile doesn't have access then ask @sudo in #techsupport to "Please grant account ID <ACCOUNT_ID> permissions to the julia-baked repo". Make sure to replace <ACCOUNT_ID> with the results of aws sts get-caller-identity --query Account.

Online AWS Batch tests

To run the online AWS Batch tests you need all of the requirements as specified in Online Docker tests, the current AWS profile should have an aws-batch-manager-test stack running and STACK_NAME needs to be set.

To make an aws-batch-manager-test compatible stack you can use the included CloudFormation template batch.yml. Alternatively you should be able to use your own custom stack but it will be required to have, at a minimum, the named outputs as shown in the included template.

Sample Project Architecture

The details of how the AWSECSManager & AWSBatchManager will be described in more detail shortly, but we'll briefly summarizes a real world application archtecture using the AWSBatchManager.

The client machines on the left (e.g., your laptop) begin by pushing a docker image to ECR, registering a job definition, and submitting a cluster manager batch job. The cluster manager job (JobID: 9086737) begins executing julia demo.jl which immediately submits 4 more batch jobs (JobIDs: 4636723, 3957289, 8650218 and 7931648) to function as its workers. The manager then waits for the worker jobs to become available and register themselves with the manager. Once the workers are available the remainder of the script sees them as ordinary julia worker processes (identified by the integer pid values shown in parentheses). Finally, the batch manager exits, releasing all batch resources, and writing all STDOUT & STDERR to CloudWatch logs for the clients to view or download and saving an program results to S3. The clients may then choose to view or download the logs/results at a later time.