DevConf.IN 2026

In the era of globalized AI adoption, data sovereignty has emerged as a critical challenge for both government and industry stakeholders. Regulatory mandates and emerging national data residency laws require organizations to ensure that data remains within prescribed jurisdictions while still enabling innovation and analytics. Traditional centralized architectures conflict with these mandates, forcing organizations to choose between compliance and AI performance. AI-enabled Data Mesh Architecture that allows domain-oriented ownership, federated governance, and localized model training to meet sovereignty requirements without sacrificing scalability.

This session will go in-depth exploring challenges and approaches with regards to AIOps. Distributed environments entail everything from microservices running on the same server to physically distributed far edge compute. This session will cover different components such as anomaly detection, root-cause analysis (RCA) and remediation, possible maturity classifications and predictive as well as generative AI approaches. Finally, this project is an invitation to join and contribute to the Linux Foundation hosted AIOps project.