ShareThe electricity market processes an unimaginable number of events: we turn on the lights, dry our hair, or work on our laptop while charging our phone—these are all separate events which need to be handled by the electricity industry. Our client requested one thing: build a platform which can handle it all. Not a small request!
The problem
The electricity market operates on half-hourly settlement periods, requiring precise calculation and reconciliation of energy consumption across multiple market participants.
This creates significant technical challenges:
- Massive data volumes exceeding 1 billion events daily
- Strict accuracy requirements for financial settlement
- Real-time processing needs across the entire market
- Complex coordination between multiple systems and stakeholders
The existing landscape required a platform that could handle scale, speed, and reliability simultaneously.
The solution
We designed and built a cloud-native, microservices-based platform on Microsoft Azure to process and aggregate energy market data at national scale.
The architecture included:
- Azure Databricks → high-throughput data processing
- Azure Data Factory → orchestration of data pipelines
- Azure Event Hubs & Service Bus → real-time data ingestion and messaging
- Azure Kubernetes Service (AKS) → scalable microservices infrastructure
- Cosmos DB & Azure SQL → storage and transactional processing
How does it work?
The platform enables:
- Continuous ingestion of high-volume energy data
- Real-time aggregation and transformation
- Settlement-period calculations across the market
As the platform evolved, machine learning capabilities were introduced to support predictive analytics, advanced forecasting, and automated model pipelines.
The impact
The platform delivers:
- Scalability, which handles 1B+ events daily with room for growth.
- High reliability designed for continuous, uninterrupted operation.
- Accuracy, supporting critical financial settlement processes.
Key takeaways
At this scale, the challenge isn’t just processing data, it’s designing systems that remain reliable under constant load, flexible and maintainable over time. Cloud-native architecture makes this possible, but only when designed correctly from the start.