How much information is too much? When is it not enough? Are the runbooks up-to-date? Are they used? Do you even have any? Let's discuss the methodology of building runbooks for solving known issues, and the process for keeping this information relevant. We'll coin the term remediation-as-code, and see how Jupyter makes runbooks continuously relevant.