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DT4DevOps: Comprehensive Digital Twin for the DevOps environments, processes and products

We will investigate the way to model and monitor the entire DevOps systems, including the team, the environments, the processes and the final products, using the digital twin concept.

Ill.: Pixabay

Short description

Jore software development practice, represented by DevOps, is an organic but complicated system, where a group of developers collaborate for fast and continuous development of software products, operating them on complex infrastructures spanning from IoT devices to the central cloud, using many dedicated software development tools, and follow an agile but strict process. Understanding and continuous improving the whole DevOps system is important for not only the productivity of the DevOps team, but also the trustworthiness of the products and services. However, despite many techniques and tools to monitor specific parts or perspectives of the system (i.e., cloud monitoring frameworks, logging of CI/CD pipelines, evaluation methods for the team and its cultures, etc.), there lacks a way to put all the parts together and provide a comprehensive view of the entire DevOps system.

Master Project

This is a long thesis.

Research Topic focus

We will investigate the way to model and monitor the entire DevOps systems, including the team, the environments, the processes and the final products, using the digital twin concept.
The research methodology will be a mix of qualitative research with DevOps teams about what they want to know about their DevOps system and how to model them; together with design research to explore the combination of existing monitoring tools into a comprehensive digital twin, and the evaluation of the approach by support analysis and improvement of the system based on the digital twin.

Expected Results and Learning Outcome

A prototype digital twin for either a sample DevOps system in a company, or a simulated one based on real setups. A sample application of high-level analysis based on the digital twin, such as identifying the weak points, the signature of decreased productivities, the potential technical debts, etc.

Qualifications

Good knowledge in Software Engineering, good programming skills.

References

If applicable

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