Event‑driven architecture

[Atul_Joshi85]

What are best practices for using SAP Event Mesh with AI services to handle real‑time utility events (like grid imbalance or meter exceptions)? For instance, a utility might route millions of smart meter events per day into Event Mesh. Joule or SAP AI Core could subscribe to those events, classify them (normal vs. exception), and trigger automated responses — such as opening a service ticket in S/4HANA, or sending a predictive alert to field crews. Another example: grid imbalance events could be streamed into Event Mesh, where AI models forecast demand spikes and automatically adjust load‑balancing workflows in BTP.

[henry-collins1]

A good approach is to keep Event Mesh focused on reliable event routing and let AI services handle the intelligence layer. Use clear event schemas, avoid sending unnecessary data, and make sure AI decisions are traceable before triggering business actions in S/4HANA. For large-scale utility scenarios, monitoring, retry handling, and human approval paths for critical actions are just as important as the AI model itself.

[Atul_Joshi85]

Thanks for the input. My requirement is specifically about large‑scale utility workflows where Event Mesh must do more than just route events — it needs schema governance, replay, and filtering to support AI services at scale.

The answer doesn’t fully explain how Joule or AI Core subscribe to Event Mesh topics, classify millions of meter events, and then trigger SAP Build Process Automation or S/4HANA actions. Without that integration detail, the solution doesn’t meet the operational needs of meter‑to‑cash and outage management in real utility landscapes.