The core backend service for the ChRIS distributed software platform, also known by the anacronym CUBE. Internally the service is implemented as a Django-PostgreSQL project offering a collection+json REST API. Important ancillary components include the pfcon
and pman
file transfer and remote process management microservices.
ChRIS Ultron Back End (sometimes also ChRIS Underlying Back End) or simply CUBE is the main core of the ChRIS system. CUBE provides the main REST API to the ChRIS system, as well as maintaining an internal database of users, files, pipelines, and plugins. Currently CUBE has two separate compute paradigms depending on deployment context. In the case of development all components of CUBE use docker
and docker swarm
technologies. In the case of production technologies such as openshift
and kubernetes
are also supported.
Consult this page for instructions on starting CUBE in either development or production contexts. For documentation/overview/background, please see the documention.
Linux is the first class host platform for all things CUBE related. Linux distributions used by various core developers include Ubuntu, Arch, and Fedora. The development team is happy to provide help to folks trying / struggling to run CUBE on most any Linux distribution.
macOS is fully supported as a host platform for CUBE. Please note that you must update/tweak some things first. Most importantly, macOS is distributed with a deprecated version of the bash
shell that will not work with our Makefile. If you want to host CUBE on macOS, you must update bash
to a current version. Instructions are out of scope of this document, but we recommend homebrew as your friend here.
In a word, don't (ok, that's technically two words). CUBE is ideally meant to be deployed on Linux/*nix systems. Windows is not officially supported nor recommended as the host environment. If you insist on trying on Windows you can consult some unmaintained documentation on attempts to deploy CUBE using the Windows Subsystem for Linux (WSL) here. This probably will break. Note that currently no one on the core development uses Windows in much of any capacity so interest or knowledge to help questions about Windows support is low. Nonetheless, we would welcome any brave soul though who has the time and inclination to fully investigate CUBE on Windows deployment.
Currently tested platforms:
Docker 18.06.0+
Docker Compose 1.27.0+
Ubuntu 18.04+ and MAC OS X 10.14+
Consult this page https://docs.docker.com/engine/install/linux-postinstall/
If you read nothing else on this page, and just want to get an instance of the ChRIS backend services up and running with no mess, no fuss:
The all in one copy/paste line to drop into your terminal (assuming of course you are in the repo directory and have the preconditions met):
docker swarm leave --force && docker swarm init --advertise-addr 127.0.0.1 && \
./unmake.sh && sudo rm -fr CHRIS_REMOTE_FS && rm -fr CHRIS_REMOTE_FS && \
./make.sh -U -I -i
This will start a bare bones CUBE. This CUBE will NOT have any plugins installed. To install a set of plugins, do
./postscript.sh
Start a local Docker Swarm cluster if not already started:
docker swarm init --advertise-addr 127.0.0.1
Get the source code from CUBE repo:
git clone https://github.com/FNNDSC/ChRIS_ultron_backend
cd ChRIS_ultron_backend
Run full CUBE instantiation with tests:
./unmake.sh ; sudo rm -fr CHRIS_REMOTE_FS; rm -fr CHRIS_REMOTE_FS; ./make.sh
Or skip unit and integration tests and the intro:
./unmake.sh ; sudo rm -fr CHRIS_REMOTE_FS; rm -fr CHRIS_REMOTE_FS; ./make.sh -U -I -s
Once the system is "up" you can add more compute plugins to the ecosystem:
./postscript.sh
The resulting CUBE instance uses the default Django development server and therefore is not suitable for production.
For convenience a deploy.sh
bash script is provided as part of the Github repo's source code.
Internally the script uses the docker stack
or Kustomize
tools to deploy on a Swarm or Kubernetes cluster respectively.
git clone https://github.com/FNNDSC/ChRIS_ultron_backend
cd ChRIS_ultron_backend
- Create appropriate
secrets
subdirectory:
mkdir swarm/prod/secrets
-
Copy all the required secret configuration files into the
secrets
directory, please take a look at this wiki page to learn more about these files. -
Deploy CUBE backend containers:
./deploy.sh up
- Tear down and remove CUBE backend containers:
cd ChRIS_ultron_backend
./deploy.sh down
- Create appropriate
secrets
subdirectory:
mkdir kubernetes/prod/secrets
- Copy all the required secret configuration files into the
secrets
directory, please take a look at this wiki page to learn more about these files.
- Deploy CUBE backend containers:
./deploy.sh -O kubernetes up
- Tear down and remove CUBE backend containers:
cd ChRIS_ultron_backend
./deploy.sh -O kubernetes down
- Deploy CUBE backend containers:
./deploy.sh -O kubernetes -T nfs -P <nfs_server_ip> -S <storeBase> -D <storageBase> up
-
Both
storeBase
andstorageBase
are explained in the header documentation of thedeploy.sh
script. -
Tear down and remove CUBE backend containers:
cd ChRIS_ultron_backend
./deploy.sh -O kubernetes -T nfs -P <nfs_server_ip> down
Start a local Docker Swarm cluster if not already started:
docker swarm init --advertise-addr 127.0.0.1
Start CUBE from the repository source directory by running the make bash script
git clone https://github.com/FNNDSC/ChRIS_ultron_backEnd.git
cd ChRIS_ultron_backEnd
./make.sh
All the steps performed by the above script are properly documented in the script itself. After running this script all the automated tests should have successfully run and a Django development server should be running in interactive mode in this terminal.
Later you can stop and remove CUBE services and storage space by running the following bash script from the repository source directory:
./unmake.sh
Then remove the local Docker Swarm cluster if desired:
docker swarm leave --force
Install single-node Kubernetes cluster. On MAC OS Docker Desktop includes a standalone Kubernetes server and client. Consult this page https://docs.docker.com/desktop/kubernetes/. On Linux there is a simple MicroK8s installation. Consult this page https://microk8s.io. Then create the required alias:
snap alias microk8s.kubectl kubectl
microk8s.kubectl config view --raw > $HOME/.kube/config
Start the Kubernetes cluster:
microk8s start
Start CUBE from the repository source directory by running the make bash script
git clone https://github.com/FNNDSC/ChRIS_ultron_backEnd.git
cd ChRIS_ultron_backEnd
export HOSTIP=<IP address of this machine>
./make.sh -O kubernetes
Later you can stop and remove CUBE services and storage space by running the following bash script from the repository source directory:
./unmake.sh -O kubernetes
Stop the Kubernetes cluster if desired:
microk8s stop
Open another terminal and run the Unit and Integration tests within the container running the Django server:
To run only the Unit tests:
cd ChRIS_ultron_backEnd
docker-compose -f docker-compose_dev.yml exec chris_dev python manage.py test --exclude-tag integration
To run only the Integration tests:
docker-compose -f docker-compose_dev.yml exec chris_dev python manage.py test --tag integration
To run all the tests:
docker-compose -f docker-compose_dev.yml exec chris_dev python manage.py test
After running the Integration tests the ./CHRIS_REMOTE_FS
directory must be empty otherwise it means some error has occurred and you should manually empty it.
Make sure the chris_backend/
dir is world writable. Then type:
docker-compose -f docker-compose_dev.yml exec chris_dev coverage run --source=feeds,plugins,uploadedfiles,users manage.py test
docker-compose -f docker-compose_dev.yml exec chris_dev coverage report
Using HTTPie client to play with the REST API
A simple GET request to retrieve the user-specific list of feeds:
http -a cube:cube1234 http://localhost:8000/api/v1/
A simple POST request to run the plugin with id 1:
http -a cube:cube1234 POST http://localhost:8000/api/v1/plugins/1/instances/ Content-Type:application/vnd.collection+json Accept:application/vnd.collection+json template:='{"data":[{"name":"dir","value":"cube/"}]}'
Then keep making the following GET request until the "status"
descriptor in the response becomes "finishedSuccessfully"
:
http -a cube:cube1234 http://localhost:8000/api/v1/plugins/instances/1/
swift -A http://127.0.0.1:8080/auth/v1.0 -U chris:chris1234 -K testing list users
Available here.
Install Sphinx and the http extension (useful to document the REST API)
pip install Sphinx
pip install sphinxcontrib-httpdomain
Build the html documentation
cd docs/
make html
Available here.
Available here.
Available here.
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