We helped a utility establish Apache Kafka as a central event streaming hub connecting IT and OT systems and feeding a Databricks data lake. The architecture replaced fragile point to point integrations with real time data flows and scalable ingestion of meter and grid events. As a result, the utility gained a unified data foundation, supported advanced analytics and forecasting, and enabled future digital use cases without rearchitecting core systems.
Background
An electric utility company operated with multiple legacy and modern IT/OT systems (Headend, DMS, Asset Management, Billing, etc.). These systems generated large amounts of real-time and batch data but lacked a unified way to exchange information and create an enterprise-wide data foundation for analytics.
Challenge
- The utility needed a scalable architecture to handle real-time data (e.g., meter reads, outage events) while also ensuring that all historical and operational data could be analyzed in one place.
- Siloed systems made it difficult to share data across departments.
- Point-to-point integrations were costly and fragile.
Solution
The utility adopted Apache Kafka as a central data hub:
- All operational systems publish and consume events through Kafka topics, ensuring real-time data flow across the organization.
- Kafka acts as the backbone for event-driven integration, decoupling producers (Headend, DMS, Asset Management, Billing, Vending, etc.) from consumers.
- Using Kafka Connect, data streams are persisted into a Databricks-powered data lake. This enables long-term storage, batch analytics, and machine learning use cases (e.g., predictive maintenance, demand forecasting).
Benefits
- Unified Data Flow: Kafka eliminated complex system-to-system integrations by centralizing data exchange.
- Scalability: The architecture now supports millions of smart meter reads and sensor events per day.
- Analytics Readiness: By storing all utility data in a Databricks data lake, the company gained a single source for advanced analytics and AI.
- Future Proofing: The event-driven approach allows new applications (e.g., grid digital twins, real-time customer portals) to be added without re-architecting.
Outcome
Within one year, we established Kafka as the enterprise nervous system, while Databricks provided the brain for analytics. This combination enabled more robust architecture, a scalable system, a basis for load forecasting, and new insights into asset performance - driving efficiency and reliability in the electric grid.
Sotex Solutions + Confluent
As Confluent’s partner, Sotex Solutions helps IT Architects put Kafka at the center of the enterprise architecture.
With Kafka + Confluent, you get:
- A real-time backbone instead of brittle point-to-point integrations
- Scalable event streaming
- Enterprise-grade Kafka with connectors, schema registry, and governance
- Seamless pipelines into data lakes and analytics platforms
We help you design architectures that are decoupled, resilient, and ready for the future—powered by Kafka
📧 bd@sotexsolutions.com
📞 +381-64-165-7193
