This project aims to evaluate a data analytics network based on K3S and IPFS. It allows to run analytics workflows in a scalable and reproducible way while utilizing the resources of a K3S cluster. For example, idle resources of edge devices can be harnessed that way.
Performance graphs, sample data, scripts, and failover tests are stored in evaluation.
K3S_URL=<Host-IP of master> K3S_TOKEN=test curl -sfL https://get.k3s.io | sh -
- Place
setup/registries.yamlin/etc/rancher/k3s/registries.yaml - Edit
/etc/systemd/system/k3s-agent.serviceto match./k3s-agent.service
If Docker and Docker Compose are installed, you can run this system locally.
Simply use the scripts/setup.sh script to create the system.
IPDR is used to serve container images from IPFS. This enables a reproducible workflows later on by utilizing the content-addressed CIDs. Please see this fork for ipdr.
ipdr push-oci <path to image file>.tar
argo submit --kubeconfig <path to kubeconfig.yaml> --watch <path to workflow.yaml>