µs
https://mjuz.rocks

Infrastructure as code (IaC) for decentralized deployment automation. Please find more information on the µs website.

Publications

1. ProTI
   µs
   

   Reliable infrastructure as Code for Decentralized Organizations

   Daniel Sokolowski

   Doctoral dissertation, Universität St. Gallen, 2024

   Abstract PDF

   IT must be reliable for organizations to thrive and quickly adaptable for their swift reaction to their environment. Agility is vital, and DevOps achieves these goals by empowering independent cross-functional teams in decentralized organizations and automating the entire software pipeline. Infrastructure as Code (IaC) is the critical tool to automate software operations, including infrastructure provisioning, application deployment, and configuration. Beyond simple IaC scripts, developers implement IaC programs in programming languages like TypeScript and Python. Such IaC programs are software, and their reliability is crucial to the functionality and security of the deployed systems. Still, techniques for the rapid development of reliable IaC programs are missing, limiting organizations’ agility. Specifically, developers lack automation for deployment coordination and updating and quality assurance tools for, e.g., testing and verification.

   We surveyed 134 IT professionals, finding that coordination across deployments is commonly needed and often requires manual coordination, even though IT professionals believe automated coordination yields better agility. However, automated approaches are centralized, limiting team independence and agility in decentralized organizations. To solve this issue, we propose automating coordination across deployments in a decentralized fashion through μs ([mju:z] “muse”), a novel IaC solution. With μs, teams have separate IaC programs, which express and jointly automate the correct order of operations across deployments. We further show how μs enables safe updating through IaC programs, preventing updates from breaking distributed transactions or workflows.

   Beyond automating the coordination of IaC programs, we address the reliability of IaC program code. To unblock studies, we built a dataset of 37 712 public IaC programs. In initial analyses, only a vanishing fraction implements tests. We identified that available testing techniques are either slow and resource-intensive or require excessive development effort. To solve this dilemma, we propose ACT, an extensible automated unit testing approach that enables testing IaC programs quickly in hundreds of configurations, often without writing additional testing code.

   This dissertation studies the coordination and testing of IaC programs. Empirically motivated, we present μs for safe deployment coordination and updating in decentralized setups and ACT for efficient testing of IaC programs. Our contributions nurture future research and reliable deployments in decentralized organizations, ensuring agility.

2. IEEE Software
   µs
   

   Decentralizing Infrastructure as Code

   Daniel Sokolowski, Pascal Weisenburger, Guido Salvaneschi

   IEEE Software 40 (1), 2023

   Abstract PDF

   Infrastructure as Code (IaC) automates deployments for single teams, falling short of decentralized deployments across groups. We need mature IaC solutions that embrace and consolidate software engineering principles to enable testing and automation advances for decentralized organizations.

3. ESEC/FSE DS
   µs
   

   Infrastructure as Code for Dynamic Deployments

   Daniel Sokolowski

   In Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/FSE, 2022

   Abstract PDF

   Modern DevOps organizations require a high degree of automation to achieve software stability at frequent changes. Further, there is a need for flexible, timely reconfiguration of the infrastructure, e.g., to use pay-per-use infrastructure efficiently based on application load. Infrastructure as Code (IaC) is the DevOps tool to automate infrastructure. However, modern static IaC solutions only support infrastructures that are deployed and do not change afterward. To implement infrastructures that change dynamically over time, static IaC programs have to be (updated and) re-run, e.g., in a CI/CD pipeline, or configure an external orchestrator that implements the dynamic behavior, e.g., an autoscaler or Kubernetes operator. Both do not capture the dynamic behavior in the IaC program and prevent analyzing and testing the infrastructure configuration jointly with its dynamic behavior.

   To fill this gap, we envision dynamic IaC, which augments static IaC with the ability to define dynamic behavior within the IaC program. In contrast to static IaC programs, dynamic IaC programs run continuously. They re-evaluate program parts that depend on external signals when these change and automatically adjust the infrastructure accordingly. We implement DIaC as the first dynamic IaC solution and demonstrate it in two realistic use cases of broader relevance. With dynamic IaC, ensuring the program’s correctness is even harder than for static IaC because programs may define many target configurations in contrast to only a few. However, for this reason, it is also more critical. To solve this issue, we propose automated, specialized property-based testing for IaC programs and implement it in ProTI.

4. ESEC/FSE
   µs
   

   Automating Serverless Deployments for DevOps Organizations

   Daniel Sokolowski, Pascal Weisenburger, Guido Salvaneschi

   In Proceedings of the 29th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/FSE, 2021

   Abstract PDF Supp Code

   DevOps unifies software development and operations in cross-functional teams to improve software delivery and operations (SDO) performance. Ideally, cross-functional DevOps teams independently deploy their services, but the correct operation of a service often demands other services, requiring coordination to ensure the correct deployment order. This issue is currently solved either with a central deployment or manual out-of-band communication across teams, e.g., via phone, chat, or email. Unfortunately, both contradict the independence of teams, hindering SDO performance – the reason why DevOps is adopted in the first place.

   In this work, we conduct a study on 73 IT professionals, showing that, in practice, they resort to manual coordination for correct deployments even if they expect better SDO performance with fully automated approaches. To address this issue, we propose μs ([mju:z] “muse”), a novel IaC system automating deployment coordination in a fully decentralized fashion, still retaining compatibility with DevOps practice – in contrast to today’s solutions. We implement µs, demonstrate that it effectively enables automated coordination, introduces negligible definition overhead, has no performance overhead, and is broadly applicable, as shown by the migration of 64 third-party IaC projects.

5. ESEC/FSE DS
   µs
   

   Deployment Coordination for Cross-Functional DevOps Teams

   Daniel Sokolowski

   In Proceedings of the 29th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/FSE, 2021

   Abstract PDF

   Software stability and reliability are the core concerns of DevOps. They are improved by tightening the collaboration between developers and operators in cross-functional teams on the one hand and by automating operations through continuous integration (CI) and infrastructure as code (IaC) on the other hand. Ideally, teams in DevOps are fully independent. Still, their applications often depend on each other in practice, requiring them to coordinate their deployment through centralization or manual coordination.

   With this work, we propose and implement the novel IaC solution µs ([mju:z] “muse”), which automates deployment coordination in a decentralized fashion. µs is the first approach that is compatible with the DevOps goals as it enables truly independent operations of the DevOps teams. We define our research problem through a questionnaire survey with IT professionals and evaluate the solution by comparing it to other modern IaC approaches, assessing its performance, and applying it to existing IaC programs.