Edge Scheduler offers software components that allow users to submit "jobs" that run applications (user plugins) on edge computing nodes.
One cloud scheduler manages multiple node schedulers. Each node scheduler must contact to only one cloud scheduler. Users interact only with a cloud scheduler to submit and monitor jobs.
# Build a Docker image with the version 0.0.0
$ version=0.0.0 make docker
configure_cloudscheduler.sh creates a RabbitMQ account for the cloud scheduler to push science goals to node schedulers and generates k3s objects to run the cloud scheduler in a Kubernetes cluster.
Waggle edge stack should already have configured the cluster for the node scheduler
configure_nodescheduler.sh creates a RabbitMQ account for the node scheduler to receive science goals from the cloud scheduler and generates k3s objects to run the node scheduler in a Kubernetes cluster.
We assume that a Kubernetes computing cluster runs on each cloud and edge computing platform. Then, use Cloud Kubernetes objects to run the cloud scheduler in the cloud and use Node Kubernetes objects to run node scheduler at the edge.
# Run cloud scheduler in the cloud computing cluster
$ kubectl apply -f kubernetes/cloudscheduler
# Run node scheduler in the edge computing cluster
$ kubectl apply -f kubernetes/nodescheduler