Joana Soares Machado

Joana is a data scientist at Swisscom. As part of the Data, Analytics and AI department, she develops ML solutions to automate the real-time monitoring of Swisscom’s business processes and IT services. Her experience includes a project at CERN where she developed a tool to monitor the responsiveness of the complex event processing engine of the ATLAS experiment. Joana holds a Master’s degree in Communication Systems from EPFL, where she previously worked as a research scientist in the domain of applied machine learning in privacy and security.

Talk: Business Process Monitoring with Anomaly Detection in Practice

DevOps teams within Swisscom are responsible for ensuring that any issues that could affect users are quickly addressed. This quest is challenging due to the high volume of available metrics, events, and traces (~300GB daily).
We will show how we designed and deployed an anomaly detection system based on Prophet models, PySpark, and MLflow, which analyses performance, throughput, and error metrics of important business processes. These analytics are displayed in an end-to-end monitoring tool which provides a holistic view of many distributed systems and gives actionable insights to the teams.