AIDOaRt | AI-augmented automation for efficient DevOps, a model-based framework for continuous development At RunTime in cyber-physical systems

Summary
The project idea is focusing on AI-augmented automation supporting modeling, coding, testing, and monitoring as part of a continuous development in Cyber-Physical Systems (CPSs). The growing complexity of CPS poses several challenges throughout all software development and analysis phases, but also during their usage and maintenance.

Many leading companies have started envisaging the automation of tomorrow to be brought about by Artificial Intelligence (AI) tech. While the number of companies that invest significant resources in software development is constantly increasing, the use of AI in the development and design techniques is still immature.

The project targets the development of a model-based framework to support teams during the automated continuous development of CPSs by means of integrated AI-augmented solutions. The overall AIDOaRT infrastructure will work with existing data sources, including traditional IT monitoring, log events, along with software models and measurements. The infrastructure is intended to operate within the DevOps process combining software development and information technology (IT) operations. Moreover, AI technological innovations have to ensure that systems are designed responsibly and contribute to our trust in their behaviour (i.e., requiring both accountability and explainability).

AIDOaRT aims to impact organizations where continuous deployment and operations management are standard operating procedures. DevOps teams may use the AIDOaRT framework to analyze event streams in real-time and historical data, extract meaningful insights from events for continuous improvement, drive faster deployments and better collaboration, and reduce downtime with proactive detection.
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More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/101007350
Start date: 01-04-2021
End date: 30-09-2024
Total budget - Public funding: 22 968 348,00 Euro - 6 898 683,00 Euro
Cordis data

Original description

The project idea is focusing on AI-augmented automation supporting modeling, coding, testing, and monitoring as part of a continuous development in Cyber-Physical Systems (CPSs). The growing complexity of CPS poses several challenges throughout all software development and analysis phases, but also during their usage and maintenance.

Many leading companies have started envisaging the automation of tomorrow to be brought about by Artificial Intelligence (AI) tech. While the number of companies that invest significant resources in software development is constantly increasing, the use of AI in the development and design techniques is still immature.

The project targets the development of a model-based framework to support teams during the automated continuous development of CPSs by means of integrated AI-augmented solutions. The overall AIDOaRT infrastructure will work with existing data sources, including traditional IT monitoring, log events, along with software models and measurements. The infrastructure is intended to operate within the DevOps process combining software development and information technology (IT) operations. Moreover, AI technological innovations have to ensure that systems are designed responsibly and contribute to our trust in their behaviour (i.e., requiring both accountability and explainability).

AIDOaRT aims to impact organizations where continuous deployment and operations management are standard operating procedures. DevOps teams may use the AIDOaRT framework to analyze event streams in real-time and historical data, extract meaningful insights from events for continuous improvement, drive faster deployments and better collaboration, and reduce downtime with proactive detection.

Status

SIGNED

Call topic

ECSEL-2020-2-RIA

Update Date

27-10-2022
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Horizon 2020
H2020-EU.2. INDUSTRIAL LEADERSHIP
H2020-EU.2.1. INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies
H2020-EU.2.1.1. INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT)
H2020-EU.2.1.1.7. ECSEL
H2020-ECSEL-2020-2-RIA-two-stage
ECSEL-2020-2-RIA ECSEL-2020-2-RIA