Rekcurd dashboard is the project for managing ML model and deploying ML module. Any Rekcurd service is manageable. It can deploy the Rekcurd service to Kubernetes cluster and can control traffic weights which Istio manages.
https://github.com/rekcurd/community
- Rekcurd: Project for serving ML module.
- Rekcurd-dashboard: Project for managing ML model and deploying ML module.
- Rekcurd-client: Project for integrating ML module.
From source:
$ git clone --recursive https://github.com/rekcurd/dashboard.git
$ cd dashboard/frontend
$ yarn install && yarn run build && cd ..
$ pip install -e .From PyPi directly:
$ pip install rekcurd-dashboardCheck the belows in detail.
You can generate the template of settings.yml file.
$ rekcurd_dashboard template$ rekcurd_dashboard db --settings settings.yml init
$ rekcurd_dashboard db --settings settings.yml migrate
$ rekcurd_dashboard server --settings settings.yml# For dev
$ docker-compose -f docker-compose/docker-compose.develop.yaml up
# For prod
$ docker-compose -f docker-compose/docker-compose.production.yaml upIf you run this on AWS (such as EKS), you need to configure aws-cli setting.
Follow the official document.
Rekcurd-dashboard docker container will mount the configuration files,
so the IAM account used by configuration needs to have enough permissions to access to Kubernetes resources on AWS.
# For dev
$ docker-compose -f docker-compose/aws/docker-compose.develop.yaml up
# For prod
$ docker-compose -f docker-compose/aws/docker-compose.production.yaml upSee docs in detail.
$ python -m unittest test/*/test_*## sudo sh scripts/kube-init.sh
$ sudo sh e2e_test/startup.sh
$ python -m unittest
$ sudo sh e2e_test/cleanup.shRekcurd can be run on Kubernetes. See community repository.