The overall AIDOaRt infrastructure works with different kinds of data, including traditional data collected at runtime (e.g., IT monitoring, log events, etc.) and data produced during the design phase of the software development process (e.g., software models, design documentation, traceability information, source code, etc.). All data will be collected and processed via a shared Data Collection & Representation component / repository. A Core Infrastructure and Framework component is intended to support the DevOps practices efficiently combining software development and information technology (IT) operations. AIDOaRt aims to enhance the DevOps tool chain by employing AI and ML techniques in multiple aspects of the system development process (requirements, monitoring, modeling, coding, and testing). According to the AIOps methodology, an AI-augmented Toolkit component will support the monitoring of runtime data (such as logs, events and metrics), software data and traceability (Observe), the analysis of both historical and real time data (Analyze) and the automation of development operation (Automate). In order to apply and evaluate in practice the AIDOaRt Core Infrastructure and Framework in combination with the AIDOaRt AI-augmented Toolkit, a global integration approach will be specified and developed.