Rehearsal: A Configuration Verification Tool for Puppet

Large-scale data centers and cloud computing have turned system configuration into a challenging problem. Several widely-publicized outages have been blamed not on software bugs, but on configuration bugs. To cope, thousands of organizations use system configuration languages to manage their computing infrastructure. Of these, Puppet is the most widely used with thousands of paying customers and many more open-source users. The heart of Puppet is a domain-specific language that describes the state of a system. Puppet already performs some basic static checks, but they only prevent a narrow range of errors. Furthermore, testing is ineffective because many errors are only triggered under specific machine states that are difficult to predict and reproduce. With several examples, we show that a key problem with Puppet is that configurations can be non-deterministic. This paper presents Rehearsal, a verification tool for Puppet configurations. Rehearsal implements a sound, complete, and scalable determinacy analysis for Puppet. To develop it, we (1) present a formal semantics for Puppet, (2) use several analyses to shrink our models to a tractable size, and (3) frame determinism-checking as decidable formulas for an SMT solver. Rehearsal then leverages the determinacy analysis to check other important properties, such as idempotency. Finally, we apply Rehearsal to several real-world Puppet configurations.Comment: In proceedings of ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI) 201

Building a collaborative culture

Background. DevOps is a set of practices and cultural values that aims to reduce the barriers between development and operations teams. Due to its increasing interest and imprecise definitions, existing research works have tried to characterize DevOps---mainly using a set of concepts and related practices. Aims. Nevertheless, little is known about thepractitioners practitioners' understanding about successful paths for DevOps adoption. The lack of such understanding might hinder institutions to adopt DevOps practices. Therefore, our goal here is to present a theory about DevOps adoption, highlighting the main related concepts that contribute to its adoption in industry. Method. Our work builds upon Classic Grounded Theory. We interviewed practitioners that contributed to DevOps adoption in 15 companies from different domains and across 5 countries. We empirically evaluate our model through a case study, whose goal is to increase the maturity level of DevOps adoption at the Brazilian Federal Court of Accounts, a Brazilian Government institution.Results. This paper presents a model to improve both the understanding and guidance of DevOps adoption. The model increments the existing view of DevOps by explaining the role and motivation of each category (and their relationships) in the DevOps adoption process. We organize this model in terms of DevOps enabler categories and DevOps outcome categories. We provide evidence that collaboration is the core DevOps concern, contrasting with an existing wisdom that implanting specific tools to automate building, deployment, and infrastructure provisioning and management is enough to achieve DevOps. Conclusions. Altogether, our results contribute to (a) generating an adequate understanding of DevOps, from the perspective of practitioners; and (b) assisting other institutions in the migration path towards DevOps adoption.Comment: 11 page