Industry perspectives on Kubernetes: a multi-method empirical analysis of adoption drivers, usage patterns, and ecosystem activity
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BRAC University
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Abstract
Kubernetes has rapidly become the backbone of cloud native computing, yet we
still know relatively little about how it is adopted and practiced in day-to-day software
engineering work. Despite its central role in modern infrastructure, systematic
empirical research that captures both practitioner experiences and open-source evidence
has been largely absent. To address this gap, we conducted a mixed-method
study combining 22 semi-structured practitioner interviews, survey responses from
31 professionals, and an analysis of 1,429 public repositories. Together, these sources
provide a comprehensive view of Kubernetes adoption, usage, and challenges. The
interviews informed the design of the survey, which in turn guided our analysis of
repositories. By linking practitioner perspectives with the technical evidence from
repositories, we were able to observe which practices appeared frequently, which were
less common, and which showed variation between the two sources. Our findings
highlight the widely shared practices as well as gaps where aspirational best practices
are not consistently reflected in real-world repositories. We also highlight ongoing
five key challenges that illustrate how Kubernetes remains a maturing ecosystem
rather than a fully developed technology. Taken together, this work contributes
to a deeper understanding of Kubernetes in practice. For practitioners, it offers
lessons for navigating adoption and maintenance, while for researchers, it provides a
unique empirical dataset that links qualitative insights with quantitative repository
evidence.
Description
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 65-70).
This thesis is submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, 2025.
Includes bibliographical references (pages 65-70).
This thesis is submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, 2025.
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Thesis