The evolution of the cyber threat landscape drives companies towards state-of-the-art security monitoring techniques. Adyen, a payment service provider company, has both legal and moral obligations to perform security monitoring within the company to remain an ethical and sustainable business. The challenge is to uncover a well-founded solution to detect real-time incidents using lightweight network traffic metadata. This research identifies an optimal clustering solution to perform anomaly detection on the logged network metadata and enhances the analysis using individual probability-based network profiles for each host. The proof of concept implemented for this research is called Mapyen, and it is validated against three different attack scenarios, namely port scans, malware infection simulations, and data exfiltration scenarios. Despite the low precision and recall scores of the initial Mapyen system, it shows great potential for future security research and development.