The Evolution of Cloud Ecosystems: How AWS, Azure, and GCP Transformed Between 2008 and 2025
Resumo
Research Context: Cloud computing has become foundational in the digital world, with AWS, Azure, and GCP leading dynamic ecosystems that enable rapid adoption of technologies such as infrastructure as code, MLOps pipelines, and generative AI. Scientific and/or Practical Problem: Frequent changes in APIs, services, and compliance requirements demand constant adaptation from developers. However, there is limited understanding of how communities respond to these evolving platforms over time. Proposed Solution and/or Analysis: We analyze cloud-related discussions on Stack Overflow from 2008 to 2025 to uncover how developer concerns evolve across adoption stages. Related IS Theory: This study draws on the Platform Ecosystem Theory, which conceptualizes digital platforms as evolving systems of interdependent actors. From this perspective, developer communities act as co-creators of platform knowledge and adaptability, shaping both technological trajectories and governance mechanisms. Research Method: We apply a reproducible method combining large-scale Q&A mining, topic modeling, and contextual trend analysis across three time windows. Summary of Results: We identify successive thematic waves in discussions, reflecting stages from IaaS (Infrastructure as a Service) and PaaS (Platform as a Service) provisioning to containers, serverless, and, more recently, data engineering and AI. These transitions mirror both platform evolution and developer needs. Contributions and Impact to IS area: Our findings offer theoretical and practical insights on developer engagement, documentation strategies, and platform governance. We also contribute a replicable methodology for longitudinal analysis of evolving digital ecosystems.
Referências
Em: Journal of Information Technology, Cybersecurity, and Artificial Intelligence 1.1, pp. 52–63. DOI: 10.70715/jitcai.2024.v1.i1.007.
Armbrust, Michael et al. (2010). “A view of cloud computing”. Em: Communications of the ACM 53.4, pp. 50–58.
Bajaj, Kushal, Karthik Pattabiraman e Ali Mesbah (2014). “Mining questions asked by web developers”. Em: Proceedings of the 11th Working Conference on Mining Software Repositories (MSR). ACM, pp. 112–121.
Barbosa, Luciano e S. Alves (2011). “A survey on software ecosystems: existing models and research directions”. Em: Proceedings of IWSECO, pp. 1–10.
Barua, Anton, Shaowei Thomas e Ahmed E. Hassan (2014). “What are developers talking about? An analysis of topics and trends in Stack Overflow”. Em: Empirical Software Engineering 19.3, pp. 619–654.
Blei, David M., Andrew Y. Ng e Michael I. Jordan (2003). “Latent Dirichlet Allocation”. Em: Journal of Machine Learning Research 3, pp. 993–1022.
Buyya, Rajkumar, James Broberg e Andrzej Goscinski (2010). Cloud Computing: Principles and Paradigms. Hoboken: Wiley.
Buyya, Rajkumar, Chee Shin Yeo et al. (2009). “Cloud computing and emerging IT platforms: vision, hype, and reality”. Em: Future Generation Computer Systems 25.6, pp. 599–616.
Chen, Xiaohui et al. (2022). “From Stack Overflow to Slack: Migrating Tech Q&A Communities”. Em: Proceedings of the ACM on Human-Computer Interaction 6.CSCW2, pp. 1–24. DOI: 10.1145/3555616.
Deng, Ying, Guofeng Jiang e Jing Song (2015). “Modeling cloud ecosystem value chains: a demand–supply–support framework”. Em: Journal of Systems and Software 106, pp. 111–125.
Gartner (2023). Magic Quadrant for Cloud Infrastructure and Platform Services. Gill, Sukhpal Singh et al. (2019). “Transformative Effects of IoT, Blockchain and Artificial Intelligence on Cloud Computing: Evolution, Vision, Trends and Open Challenges”. Em: Internet of Things 9, p. 100118. DOI: 10.1016/j.iot.2019.100118.
Manikas, Konstantinos e Klaus Marius Hansen (2013). “Software ecosystems: A systematic literature review”. Em: Journal of Systems and Software 86.5, pp. 1294–1306.
Marston, Sean et al. (2011). “Cloud computing — The business perspective”. Em: Decision Support Systems 51.1, pp. 176–189.
Mell, Peter e Timothy Grance (2011). The NIST Definition of Cloud Computing. Rel. técn. NIST SP 800-145. National Institute of Standards e Technology.
Messerschmitt, David G. e Clemens Szyperski (2003). Software Ecosystem: Understanding an Indispensable Technology and Industry. MIT Press.
Popović, Kresimir e Zoran Hodžić (2010). “Cloud computing security issues and challenges”. Em: International Conference on Information Society (i-Society).
Rimal, Bhaskar Prasad, Eunmi Choi e Ian Lumb (2011). “A taxonomy and survey of cloud computing systems”. Em: Proceedings of INC, IMS and IDC, pp. 44–51.
Santos, João D. D. et al. (2018). “Supporting governance of mobile application developers by mining and analyzing technical questions”. Em: Journal of Software Engineering Research and Development 6.1, pp. 1–27.
Sharma, Viney e Gur Mauj Saran Srivastava (2016). “Evolution and present status of cloud computing: a comprehensive analysis”. Em: International Journal of Business Information Systems 22.2, pp. 123–142. DOI: 10.1504/IJBIS.2016.075356.
Son, Young e Jinwoo Kim (2023). “A Comparative Analysis of Topic Modeling Techniques for Software Engineering Text Mining”. Em: Information 14.6, p. 602.
Stack Exchange (2025). Stack Exchange Data Dump - March 2025. [link]:. Accessed: April 2025.
Treude, Christoph e Markus Wagner (2019). “Predicting Good Configurations for GitHub and Stack Overflow Topic Models”. Em: Proceedings of the 16th International Conference on Mining Software Repositories (MSR). IEEE/ACM, pp. 84–88.
Wang, Shaowei, David Lo e Lingxiao Jiang (2013). “An Empirical Study on Developer Interactions in StackOverflow”. Em: Proceedings of the 28th Annual ACM Symposium on Applied Computing (SAC). ACM, pp. 1019–1024.
Wareham, Jonathan, Peter Fox e Jose Luis Cano Giner (2014). “Technology ecosystem governance”. Em: Organization Science 25.4, pp. 1195–1215.
Zhang, Ge, Yun Chen e Gaoyong Li (2020). “The Evolution and Emerging Trends of Cloud Computing Adoption Research: Visual Analysis of CiteSpace Based on WOS Papers”. Em: Proceedings of the 2020 International Conference on Smart Production and Management of Logistics (SPML). Beijing, China: ACM. DOI: 10.1145/3432291.3433641.
Zhang, Qi, Lu Cheng e Raouf Boutaba (2010). “Cloud computing: state-of-the-art and research challenges”. Em: Journal of Internet Services and Applications 1, pp. 7–18.
Zolduoarrati, E., S. A. Licorish e N. Stanger (2024). “Harmonising contributions: exploring diversity in software engineering through CQA mining on Stack Overflow”. Em: ACM Transactions on Software Engineering and Methodology (TOSEM) 33.7, p. 179.
