Having worked with Jenkins-CI in the life sciences context for the last few years, I am finding that Jenkins satisfies key requirements of a robust framework for efficient data pipelining integration, and analysis. Here I will briefly describe the attributes that make Jenkins-CI a suitable platform for data scientists
What was suggested in JENKINS-23772, was that instead of accepting only integers for the width, that the plug-in started to accept text values as well. This way
10% as valid values. The challenge in user requests like this, is how to maintain backward compatibility in your plug-in, while releasing a new version that changes objects and attributes.
figshare is a platform where users can upload and share images, graphs, presentations and other documents. These artifacts can be generated using different tools - including Jenkins. The BioUno figshare Plug-in integrates Jenkins and figshare. The figshare API uses OAuth 1.0, and requires data such as client key, client secret, token key and token secret stored in Jenkins.
What the Jenkins Credentials Plug-in does, basically, is store these credentials in a way that it is both safer and easier to maintain in Jenkins. Before that, users would add passwords as parameters in jobs or store credentials globally in Jenkins via plug-ins. This resulted in security problems, and was also difficult to maintain with a high number of jobs with different credentials.