This visualization produces reliability graphs for project ecosystems running on BigBoat.
Copy the file lib/config.json to config.json and adjust environmental
settings in that file. The following configuration items are known:
visualization_url: The URL to the visualization hub. This may include a protocol and domain name, but does not need to in case all the visualizations and the BigBoat status are hosted on the same domain (for example in a development environment). The remainder is a path to the root of the visualizations, where the dashboard is found and every other visualization has sub-paths below it.path: The relative path at which the BigBoat status is made available on the server. This can remain the default.to work just fine.
The data for the BigBoat status can be collected, analyzed and output through
runs of scripts from the data-gathering and data-analysis repositories. The
documentation for those repositories may provide more details on how to deploy
the collection scripts, but as a summary the gathering scripts
scraper/bigboat_to_json.py and either controller/auth/status.py (as part of
a control server) or import_bigboat_status.py, as well as the
bigboat_status analysis report, may be part of the data pipeline. The entire
data collection must be placed in the public/data directory.
The visualization can be built using Node.js and npm by running npm install
and then either npm run watch to start a development server that also
refreshes browsers upon code changes, or npm run production to create
a minimized bundle. The resulting HTML, CSS and JavaScript is made available in
the public directory.
This repository also contains a Dockerfile specification for a Docker image
that can perform the installation of the app and dependencies, which allows
building the visualization within there. Also, a Jenkinsfile contains
appropriate steps for a Jenkins CI deployment, including data collection and
visualization building.