  The rise of 5G deployments has created the environment for many emerging
technologies to flourish. Self-driving vehicles, Augmented and Virtual Reality,
and remote operations are examples of applications that leverage 5G networks'
support for extremely low latency, high bandwidth, and increased throughput.
However, the complex architecture of 5G hinders innovation due to the lack of
accessibility to testbeds or realistic simulators with adequate 5G
functionalities. Also, configuring and managing simulators are complex and time
consuming. Finally, the lack of adequate representative data hinders the
data-driven designs in 5G campaigns. Thus, we calibrated a system-level
open-source simulator, Simu5G, following 3GPP guidelines to enable faster
innovation in the 5G domain. Furthermore, we developed an API for automatic
simulator configuration without knowing the underlying architectural details.
Finally, we demonstrate the usage of the calibrated and automated simulator by
developing an ML-based anomaly detection in a 5G Radio Access Network (RAN).
