Deployment
This page provides an overview of approaches to deploy RDepot.
It is recommended to have a look at the Architecture page first to familiarize yourself with the RDepot components and their role.
Docker
Images
OpenAnalytics-maintained Docker images are available on Docker Hub:
- Manager App: openanalytics/rdepot-app
- Repo Server: openanalytics/rdepot-repo
- Web UI: openanalytics/rdepot-client
The manager app and repo server images are based on adoptopenjdk images. The web UI image is based on NGINX.
All RDepot images are available under several tagging strategies:
- versioned (e.g.
2.4.0
): Recommended for production. - snapshots (e.g.
2.5.0-SNAPSHOT
): Bleeding edge. Not recommended for production.
Example (Docker Compose)
The following prerequisites are needed:
-
docker (https://www.docker.com/)
-
docker-compose (https://docs.docker.com/compose/)
While not a strict requirement, docker-compose will help you better manage the multiple containers that are involved. This guide will continue to use docker-compose, but you should be able to convert the example to standard docker.
(Install i.e. by issuing
pip install docker-compose
) -
port 80 is not used (localhost, check for nginx or apache service)
Please see the demo deployment on GitHub.
Alternatively, an example docker-compose YAML file:
services:
proxy:
image: nginx:alpine
container_name: oa-rdepot-proxy
restart: unless-stopped
volumes:
- ./docker/compose/proxy/nginx.conf:/etc/nginx/nginx.conf:ro
- ./docker/compose/proxy/rdepot.conf:/etc/nginx/sites-enabled/rdepot:ro
- repository:/opt/rdepot/repo/:ro
- logs:/var/log/nginx/
ports:
- ${RDEPOT_PORT}:80
depends_on:
- backend
- repo
- frontend
networks:
- oa-rdepot
db:
image: postgres:alpine
restart: unless-stopped
hostname: oa-rdepot-db
container_name: oa-rdepot-db
environment:
- POSTGRES_DB=rdepot
- POSTGRES_USER=rdepot
- POSTGRES_PASSWORD=mysecretpassword
networks:
- oa-rdepot
backend:
image: openanalytics/rdepot-app:2.4.0
restart: unless-stopped
hostname: oa-rdepot-backend
container_name: oa-rdepot-backend
volumes:
- repositories:/opt/rdepot/repositories/
- snapshots:/opt/rdepot/generated/
- queue:/opt/rdepot/new/
- ./docker/compose/backend/application.yaml:/opt/rdepot/application.yml
networks:
- oa-rdepot
depends_on:
- db
environment:
- DB_URL=jdbc:postgresql://oa-rdepot-db:5432/rdepot
- DB_USERNAME=rdepot
- DB_PASSWORD=mysecretpassword
- ALLOWED-ORIGIN=http://localhost:${RDEPOT_PORT}
healthcheck:
test: ["CMD-SHELL", "if [ \"$$(curl -I localhost:8080 2>/dev/null | grep HTTP/1.1 | cut -d\" \" -f2)\" != \"302\" ]; then exit 1; else exit 0; fi;"]
interval: 10s
timeout: 10s
retries: 10
repo:
image: openanalytics/rdepot-repo:2.4.0
restart: unless-stopped
hostname: oa-rdepot-repo
container_name: oa-rdepot-repo
volumes:
- repository:/opt/rdepot/
- ./docker/compose/repo/application.yaml:/opt/repo/application.yml
networks:
- oa-rdepot
frontend:
container_name: oa-rdepot-frontend
image: openanalytics/rdepot-client:2.4.0
restart: unless-stopped
networks:
- oa-rdepot
environment:
- VITE_LOGIN_SIMPLE=true
- VITE_LOGIN_OIDC=false
- VITE_URL_PREFIX=/
- VITE_SERVER_ADDRESS=http://localhost:${RDEPOT_PORT}/backend
networks:
oa-rdepot:
ipam:
config:
- subnet: 192.168.49.0/24
volumes:
repository:
repositories:
snapshots:
queue:
logs:
The missing files (for volume mapping) can be found in our Git repository:
The final step is to launch the Docker containers using docker-compose:
docker-compose up -d
One can then go to http://localhost to log in.
There is an admin user with username einstein
and password testpassword
.
See the RDepot manager application.yml for the included configuration which specifies the user credentials.
One can override these parameters using environment variables.
To complete an end-to-end flow: R or Python package to RDepot to Repository Server to R or Python client, the following steps are needed:
- create a repository with (or edit)
- a name: repositoryName
- a repository’s publication URI: http://localhost/repo/repositoryName and
- a server address: http://oa-rdepot-repo:8080/repositoryName
- a technology: R or Python
- submit one or more packages to that repository via the RDepot web interface
- publish the repository using the published checkbox on the repositories list page (if needed)
- go to the package details page (repositories list page, click on the repository name, click on the package name, then on the details button)
- use the install command shown on the package details page to install the package in R or Python:
orinstall.packages("somePackage", repos = c("http://localhost/repo/repositoryName", getOption("repos")))
pip install --index-url http://localhost/repo/repositoryName somePackage
To (re)start with fresh database:
- remove the containers via
docker-compose down -v
- start up again using
docker-compose up -d
Kubernetes
Kustomize
Kustomize is a tool for template-free configuration of applications running in Kubernetes. It offers a purely declarative approach to configuration customization.
Base recipes and a number of overlays are available for RDepot here.
Bases
The recipes are tagged according to the compatible RDepot release version and should be stable to use as a remote base:
apiVersion: kustomize.config.k8s.io/v1beta1
kind: Kustomization
resources:
- github.com/openanalytics/rdepot-kubernetes/base/app-stateful?ref=2.4.0
- github.com/openanalytics/rdepot-kubernetes/base/repo?ref=2.4.0
You can also clone the bases locally, copy the recipes or use a tool like kpt depending on the amount of independence you want to have w.r.t. the OpenAnalytics upstream.
Overlays
Next to the base recipes you can find a number of overlays which range from simple extensions on top of the base recipes to complete demo deployments. The example below uses one of these overlays.
Helm?
There are currently no plans to maintain RDepot helm charts from OpenAnalytics.
Example (Minikube)
The following prerequisites are needed:
-
kustomize (https://kustomize.io).
The standalone
kustomize
binary is recommended as some features are used which are not available in the version included withkubectl
-
minikube (https://minikube.sigs.k8s.io/docs/start/)
minikube is a distribution of Kubernetes that can easily run on a single machine with moderate resources.
To deploy the demo, please refer to the documentation.
The demo includes:
- an instance of the RDepot repository server
- an instance of RDepot manager, preconfigured with a
demo
repository on the repository server and protected with simple authentication - a single-node postgres deployment
All volumes are provided through the dynamic provisioning in minikube
You can port-forward the manager app:
kubectl -n rdepot-demo port-forward svc/rdepot-app 8080:80
and visit the app in your browser at http://localhost:8080 (login einstein
/testpassword
)
Similarly, you can port-forward the repository:
kubectl -n rdepot-demo port-forward svc/rdepot-repo 8081:80
and point your browser to http://localhost:8081/repo/demo to browse your uploaded packages.
You can tear down the demo with:
kubectl delete namespace rdepot-demo
Refer to the README for more info.
WAR & JAR
The latest versions of RDepot are available on our downloads page in WAR and JAR format (except for the web UI application).
This is currently not the recommended approach to deploy RDepot. This route is only relevant in the following cases:
- you wish to develop and/or extend RDepot
- you are not able to run Docker on your platform of choice
Download both rdepot-app-2.4.0.war (sha1, md5) and rdepot-repo-2.4.0.jar (sha1, md5) and start them by executing java -jar rdepot-app-2.4.0.war
and java -jar rdepot-repo-2.4.0.jar
respectively.