Execution Orchestrator for MLsploit

ENVIRONMENT SETUP

The primary configuration settings of the execution module are stored inside the .env file, which you'll need to modify according to your needs.

The first thing you should update is the MLSPLOIT_API_ADMIN_TOKEN, which is necessary for accessing the data API for MLsploit.

RUN WITH DOCKER

We use docker-compose to orchestrate the setup and execution of the service. You only need to setup docker on your system and then run the following command:

$ bash docker-start-master.sh

This starts the execution service in MASTER mode. The MASTER mode of the execution service runs the scheduling, networking, monitoring and execution of the jobs. The WORKER mode, which only handles the execution of the jobs, can be run in parallel on another system using the following command:

$ bash docker-start-worker.sh

For the WORKER mode, you will need to update the host environment variables in the .env file to point to the MASTER node.

MANUAL SETUP

Install the dependencies

$ pip install -r requirements.txt

Set up the environment

$ export MLSPLOIT_BROKER_URL='amqp://admin:password@localhost:5672/mlsploit'
$ export MLSPLOIT_BACKEND_URL='redis://localhost:6379'
$ export MLSPLOIT_API_ADMIN_TOKEN=<token here>

USAGE

$ celery worker -A mlsploit -B \
    -l info \
    -Ofair \
    -c 5

The -B flag should be enabled only on one node worker since it queues the pending jobs.