sul-dlss/quimby

Name: quimby

Owner: Stanford University Digital Library

Description: Infrastructure big picture reporting tool

Created: 2017-05-26 20:35:47.0

Updated: 2018-03-19 18:56:29.0

Pushed: 2018-02-05 23:43:00.0

Homepage: null

Size: 186

Language: Ruby

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README

Build Status | Coverage Status

Quimby

URL for SUL production instance:

Quimby is an infrastructure operations big picture reporting tool. It is a rails application that generates a dashboard. The dashboard presents information on servers, codebases, and analytics we can gather on the first two, for projects within SUL-DLSS and SUL-CIDR.

Requirements

This is more what the application was built with; uncertain if older versions will / could work.

  1. Ruby (2.4.1)
  2. Rails (5.1.1 or greater)
  3. Postgres
Installation / Local Setup

Clone the repository

t clone git@github.com:sul-dlss/quimby.git

Change directories into the app and install dependencies

ndle install

Create the database for the Quimby application, then migrate the schema (if needed).

ndle exec rake db:create
ndle exec rake db:migrate

Now, you want to load your data. You need to add configuration information to config/settings.yml (see Configuration below for what is required), then run the rake task to load all data.

ter editing config/settings.yml
ndle exec rake load_data:all

This will load data from the Quimby data sources into the application database.

Finally, start the local development server:

ndle exec rails s
Configuration

For each data source, you are required to have some configuration for access (captured in config/settings.yml). For this instance of the Quimby codebase, if you want to run the load_data:all rake task, you need the following configurations:

Testing

Quimby uses rspec for managing tests and factory girl for generating some of our fixtures class instances. To run tests:

ndle exec rake
Deployment

Quimby uses capistrano to deploy. Current it's deployed to a staging machine named sul-quimby-stage and deployed via:

ndle exec cap stage deploy
Data Sources

This work is supported by the National Institutes of Health's National Center for Advancing Translational Sciences, Grant Number U24TR002306. This work is solely the responsibility of the creators and does not necessarily represent the official views of the National Institutes of Health.