TimeTrack: A dataset for exploring temporal patterns and predictive insights into OpenAirInterface (OAI) CI/CD cluster

The rapid adoption of cloud-native architectures and telecommunications frameworks has intensified the need for efficient resource management and network performance monitoring. Time series data plays a critical role in these settings by capturing sequential changes in metrics, enabling advanced analytics and ma chine learning models for anomaly detection, predictive maintenance, and resource allocation optimization. However, existing public datasets lack the granularity or breadth

of metrics required for in-depth research, often omitting critical computing and network performance indicators, particularly within cloud-native environments for telecommunications workloads. TimeTrack addresses this gap by offering a comprehensive time series dataset collected from an OpenAirInterface (OAI)

Continuous Integration/Continuous Deployment (CI/CD) cluster. The dataset contains monitoring data on both computing and network resources used by the CI/CD of OAI components (gNodeB, User Equipments and Core Network), providing a

unique perspective on the demands of cloud-native telecommunications

systems. The primary objective of TimeTrack is to support research in resource management, anomaly detection, and network optimization in similar environments.