Solution Study
Montag, 20. November
09:15 - 09:45
Live in Berlin
Weniger Details
The integration of Machine Learning (ML) and Artificial Intelligence (AI) into DevOps and Platform Engineering is here to revolutionize the landscape of software development and infrastructure management. This abstract explores the imminent impact of ML/AI on DevOps and Platform Engineering, highlighting how these technologies enhance automation, optimize processes, and facilitate predictive analysis. The fusion of ML/AI with DevOps practices streamlines the software development lifecycle, enabling faster, more efficient deployment, monitoring, and maintenance of applications. Additionally, in Platform Engineering, ML/AI tools contribute to adaptive and self-healing systems, ensuring resilient, scalable, and secure infrastructure. This abstract discusses the transformative potential of ML/AI in DevOps and Platform Engineering, emphasizing the paradigm shift towards intelligent, data-driven, and automated practices in the software development and infrastructure management domains.
Matthias has been in the IT industry for nearly 25 years – with roles in software development, architecture, test automation, application lifecycle management and DevOps for IBM, Borland, Microsoft and codecentric. For the past five years, he has been helping large companies get their software to production faster with XebiaLabs’ release orchestration and deployment automation – from classic Java EE environments to containers and cloud up to serverless architectures. Now with Digital.ai, he helps large enterprises achieve their digital transformation goals through value stream management.