https://github.com/datitran/cf-demo
End-to-end data science example running on Cloud Foundry
https://github.com/datitran/cf-demo
Last synced: about 1 month ago
JSON representation
End-to-end data science example running on Cloud Foundry
- Host: GitHub
- URL: https://github.com/datitran/cf-demo
- Owner: datitran
- License: mit
- Created: 2016-07-05T09:49:29.000Z (almost 9 years ago)
- Default Branch: master
- Last Pushed: 2016-07-19T14:45:12.000Z (almost 9 years ago)
- Last Synced: 2025-03-31T00:41:15.345Z (2 months ago)
- Language: Jupyter Notebook
- Homepage: http://engineering.pivotal.io/post/api-first-for-data-science/
- Size: 2.47 MB
- Stars: 19
- Watchers: 10
- Forks: 10
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Data Science on Cloud Foundry
This is a full end-to-end data science example running on Cloud Foundry (CF).
## Getting Started
#### Concourse CI
1. Clone the repo: `git clone https://github.com/datitran/cf-demo.git`
2. Change to the cloned repo and do: `vagrant up`
3. Target your local VirtualBox: `fly -t example-ci login -c http://192.168.100.4:8080`
4. Run the pipeline: `fly -t example-ci set-pipeline -p data-science-ci -c pipeline.yml -l credentials.yml`
5. Unpause the pipeline: `fly -t example-ci unpause-pipeline -p data-science-ci`
#### Docker
1. Build docker image from file: `docker build -f dockerfile -t datitran/cf-demo .`
## Dependencies
- [Anaconda](https://www.continuum.io/downloads) Python 3.5.2
- Python conda environment (install with `conda env create --file environment.yml`)
- [PCF Dev](https://github.com/pivotal-cf/pcfdev)
- [Concourse](http://concourse.ci/index.html)
- [Docker](https://www.docker.com/)
- [Vagrant](https://www.vagrantup.com/)
## Copyright
See [LICENSE](LICENSE) for details.
Copyright (c) 2016 [Dat Tran](http://www.dat-tran.com/).