AIOps for Autonomous Management of Containerized Infrastructures: Rapid Review Data Extraction and Quality Assessment

This dataset provides the supporting materials for the Rapid Review entitled "AIOps for Autonomous Management of Containerized Infrastructures: A Rapid Review". The review synthesizes 39 studies published between 2021 and 2026, focusing on Artificial Intelligence for IT Operations (AIOps) and autonomous management mechanisms for containerized infrastructures, particularly Kubernetes-based environments. The dataset contains two Excel workbooks: Synthesis_Extraction_Rapid_Review.xlsx: Bibliographic information, study classifications, research-question mappings, operational approaches, technologies, evaluation contexts, reported challenges, and research-gap coding for the 39 included studies. Quality_Assessment_Rapid_Review.xlsx: Study-level quality assessment based on six criteria addressing methodological reporting, empirical validation, workload realism, reproducibility, infrastructure relevance, and operational capabilities. The data support descriptive analysis and qualitative synthesis across six research questions addressing AIOps tools, self-healing, autoscaling, heterogeneous deployment environments, data-driven operations, and open research problems. Limitations: The deposited materials document the retained studies and their extraction and assessment results. Original database search exports, complete deduplication records, and full-text exclusion logs are not included. Consequently, the dataset does not provide a complete reconstruction of the literature search and screening process. These materials are made available to support transparency, inspection, reuse, and further research in AIOps and software engineering.