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Related Articles from SNS
Architecturally Significant MLOps Guidelines for ML Model Integration and Deployment: a Gray Literature Review
Announce Type: new Abstract: Context. Despite the growing adoption of Machine Learning Operations (MLOps), teams often approach MLOps projects in an ad hoc manner due to the lack of consolidated architectural guidance. The community would benefit from a reference that synthesizes knowledge to inform the architectural design of MLOps systems, especially regarding the integration and deployment of ML models.
Comparing ML-Specific and General Python Code Smells Across Project Characteristics
arXiv:2606.01882v1 Announce Type: new Abstract: Machine learning systems consist of general-purpose code as well as machine-learning-specific code. While ML-specific code smells have been identified, their connection to project characteristics and their interaction with overall code quality are not well understood.
Zero Touch Predictive Orchestration: Automating Time-Series Models for the Cloud-Edge Continuum
new Abstract: The Cloud-Edge Continuum (CEC) enables latency-critical applications by distributing resources to the far edge, but its extreme volatility makes proactive Zero Touch Management via time-series forecasting essential. However, orchestrators face a severe "cold start" problem: newly discovered nodes lack the historical data required to train localized predictive models, while generalized models fail to capture unique hardware and microservice behaviors. To solve this, we propose a...