Logging and log synchronization play a pivotal role in cloud forensics by enabling the reconstruction of events, detection of anomalies, and verification of user activities across distributed cloud infrastructures. Research in this domain focuses on developing reliable, tamper-resistant, and scalable mechanisms for log generation, storage, and correlation in multi-tenant and multi-cloud environments. Key topics include secure log management frameworks, blockchain-based immutable logging, and real-time log synchronization across virtual machines, containers, and cloud services. Other significant areas involve machine learning-assisted log anomaly detection, timestamp alignment for forensic timeline reconstruction, and privacy-preserving log sharing among stakeholders. Emerging research directions also explore distributed consensus protocols for synchronized logging, provenance-based log validation, and integration of standardized log formats to enhance interoperability across diverse cloud platforms. Furthermore, designing forensic-ready logging systems, automated evidence correlation tools, and compliance-aware log retention policies remain critical for strengthening transparency, accountability, and reliability in cloud forensic investigations.