The Evolution of Cloud Ecosystems: How AWS, Azure, and GCP Transformed Between 2008 and 2025 - Arruda, Angelica dos Santos; Santos, Rodrigo Pereira dos; Moura, Pedro Nuno de Souza; Alvim, Adriana Cesário de Faria; Moraes, Laura de Oliveira Fernandes (Anais do Simpósio Brasileiro de Sistemas de Informação (SBSI); 2026: Anais do XXII Simpósio Brasileiro de Sistemas de InformaçãoDO - 10.5753/sbsi.2026.248685, 2026)
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 API, 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 socio-technical theory as an inspiration for analyzing 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.