Masterarbeit, 2017
109 Seiten, Note: 1,3
1. Introduction
1.1. Motivation
1.2. Research Questions
1.3. Research Design
1.4. Outline / Remainder
2. Research Methods
2.1. Literature Review Methods
2.2. Empirical Methods
3. Literature Review
3.1. Scope
3.2. Research Process
3.2.1. Systematic Literature Review
3.2.2. Targeted Review
3.3. Results
3.3.1. Systematic Literature Review
3.3.2. Targeted Review
4. Empirical Research
4.1. Case Description
4.2. Research Process
4.3. Results
4.3.1. Practitioner Perception of DevOps
4.3.2. Model Revision, Iteration 1
4.3.3. Model Revision, Iteration 2
5. The DevOps Assessment Model
5.1. Model Presentation
5.1.1. The DevOps Mindset Assessment
5.1.2. The DevOps Capability Assessment
5.2. Model Development
5.3. Managerial Implications on Using the DevOps Assessment Model
6. Evaluation
6.1. Summative
6.2. Formative
7. Discussion, Limitations, Future Research
This thesis aims to clarify the ambiguous term "DevOps" by identifying its core characteristics and implementation criteria. Through a synthesis of existing literature and empirical research conducted within an IT service organization, the work develops and validates a maturity model designed to help practitioners assess their organization’s DevOps performance and identify areas for improvement.
DevOps Definitions
The definitions of DevOps vary distinctly in content and specificity between the sources of the literature review. Many sources name this circumstance explicitly. For example, Tony Clear states that DevOps as a term was ‘described as ambiguous, difficult to define and multifaceted’ (Clear 2017). The part of the definition most sources agree on is the goal to ‘bridge the gap between development and operations’ (Barna et al. 2017, p. 65). The described means DevOps applies to achieve this goal often include increased communication and collaboration between workers of these different disciplines (Waller et al. 2015). Some sources go further and suggest these disciplines to work together within the product lifecycle ‘as early as possible’ (Woods 2016, p. 20). The groundwork for these collaboration and communication improvements are of course cultural changes which are described to be a vital part of DevOps (Chung and Bang 2016). Some sources even consider the cultural values associated with DevOps so unique that they name this set of values the DevOps mindset (Chen et al. 2015).
Another goal many sources ascribe to DevOps is the ability to develop software of higher quality (Perera et al. 2016) and in less time (Soni 2015) with increased stability (Betz et al. 2016) and scalability and in a more efficient process (Spinellis 2016). This is achieved by establishing a ‘quick flow of changes to a production environment’ (Gottesheim 2015, p. 3) through smaller batch sizes (Callanan and Spillane 2016), build, test and deployment automation (Clear 2017). As described by Zhu et al. DevOps tries to apply these techniques to the entire product lifecycle to ‘reduce the time between committing a change to a system and the change being placed into normal production’ (Zhu et al. 2016, p. 33). Altogether, DevOps is described as a means for better collaboration between IT and the business by bringing ‘innovative product and features faster to the market’ (Ebert et al. 2016, p. 98).
1. Introduction: This chapter provides the motivation for the study, defines the research questions, and outlines the overall research design and the structure of the thesis.
2. Research Methods: This section details the application of Action Design Research (ADR) and the specific qualitative methods, including the systematic literature review and Problem-centered Interviews, utilized in the study.
3. Literature Review: The chapter synthesizes existing academic knowledge to characterize DevOps, defining its principles, practices, and outcomes based on current literature.
4. Empirical Research: This chapter describes the practical research conducted at an IT service organization, presenting stakeholder perceptions and the iterative process of model refinement.
5. The DevOps Assessment Model: The final state of the maturity model is presented, including both the "Mindset" and "Capability" assessments, along with an explanation of its development phases.
6. Evaluation: This chapter details the evaluation of the model through workshops in different divisions, assessing its usability and effectiveness in practice.
7. Discussion, Limitations, Future Research: The thesis concludes by discussing the findings, addressing the limitations of the research, and suggesting directions for future scientific inquiry.
DevOps, Maturity Model, IT Service Management, Continuous Delivery, Action Design Research, Software Development, Organizational Culture, Infrastructure as Code, Automation, Systems Thinking, Collaboration, Lean Startup, Continuous Integration, Continuous Deployment, IT Operations.
The thesis focuses on defining the term "DevOps" and developing a research-based maturity model to help organizations assess their current DevOps practices and guide implementation improvements.
Central topics include the cultural and organizational shifts required for DevOps, the role of automation and continuous delivery in IT, and the bridging of silos between development and operations teams.
The research is guided by five questions, primarily aiming to identify key DevOps characteristics, translate them into measurable indicators, and determine how a maturity model can be used to assess and improve an organization’s performance.
The study employs Action Design Research (ADR), which allows for the iterative construction and evaluation of an IT artifact—in this case, the DevOps Assessment Model—through interaction with practitioners.
The main body covers a comprehensive systematic literature review, empirical research conducted through Problem-centered Interviews in an IT service environment, and the multi-stage design and evaluation of the DevOps Assessment Model.
The model is described as a "prescriptive" maturity model, intended to provide organizations with an overview of their maturity while offering guidance on how to approach improvements to gain business value.
The separation was made because the cultural "Mindset" aspects (related to values) are best assessed by human estimation, whereas technological and organizational "Capabilities" can be assessed through clearly defined, objective maturity levels.
Practitioners provided feedback through interviews and workshops, which helped refine the model's items, clarify terminology, and ensure the criteria were practical and relevant for their specific IT service environment.
The "Pre-DevOps" (or level zero) stage acts as an entry point for organizations that have not yet begun adopting DevOps practices, allowing them to identify their initial state within the maturity scale.
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