The software development model is changing fast, and the challenge of security remains the primary attention, particularly with the implementation of Development and Operations (DevOps), Distributed Ledger Technology (DLT), and other methods. Thus, when such technologies are integrated within organizations, it becomes essential to measure the use of the technologies in Anomaly Detection (AD) and access management. This research work evaluates the competence of these technologies based on measures such as the Detection Rate (DR) and the False Positive Rate (FPR). Statistics reveal that as the number of records increases. DR improves across all methods, with DevOps Resilience with Authentication (DevOps-RAS) achieving the highest DR of 95.94% at 500 records, compared to 81.23% for CAMS and 85.43% for DLT. Conversely, FPR increases with record size, with DevOps RAS presenting a higher FPR of 95.78% at 500 records, compared to 76.45% for CAMS and 83.56% for DLT. These visions should help organizations determine the most effective security method for Cyber-Physical Systems (CPS), thereby maximizing DR while minimizing the FPR required to enhance the system’s overall robustness.