Peng (

Studies and many incidents in the headlines suggest misconfigurations remain a major cause of unavailability in large systems despite the large amount of work put into detecting, diagnosing and repairing them. In part, this is because many of the solutions are either post-mortem or too expensive to use in production cloud-scale systems. Configuration validation is the process of explicitly defining specifications and proactively checking configurations against those specifications to prevent misconfigurations from entering production. We propose a generic framework, ConfValley, to make configuration validation easy, systematic and efficient, and to allow configuration validation as an ordinary part of system deployment. ConfValley consists of a declarative language for practitioners to express configuration specifications, an inference engine that automatically generates specifications, and a checker that determines if a given configuration obeys its specifications. Our specification language expressed the configuration validation code from Microsoft Azure in 10x fewer lines, many of which were automatically inferred. Using expert-written and inferred specifications, we detected a number of configuration errors in the latest configurations deployed in Microsoft Azure.