Enexis Kafka maturity for smart metering | use case
Enexis, a Dutch grid operator, partnered with Axual to implement a real-time data streaming solution. This enabled efficient smart meter data management, reducing labor and enhancing data processing.
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Enexis is a local grid operator (Distribution System Operator, or DSO) in the Netherlands. With 4,700 employees, Enexis manages the electricity and gas grid for over 3 million households and businesses. In 2019 several projects required data streaming capabilities at Enexis. This triggered them to explore solutions.
This use case is about how Enexis implemented Axual’s platform to enable them to start with real-time data. During their proof of concept, they implemented the Kafka based platform with the help of our lead developer and started with an initial use case around smart metering.
Take complexity out of Kafka
Axual offers an out-of-the-box Kafka solution for energy companies. Our platform combines the data streaming capabilities of Strimzi, an open-source Kafka on Kubernetes framework, with a user-centric interface that enables large organizations to utilize Apache Kafka with enterprise features such as access control, data governance and a visual way to see where data is flowing. The goal of our platform is to take the complexity out of Kafka so organizations such as Enexis can focus on building out their use case instead of maintaining Apache Kafka.
Solution for Data Processing
Enexis needed a solution that would be responsible for smart meter lifecycle management, data processing, branching to BI systems and connecting with technologies such as Tibco, Menix, Debezium, OSGI, Jaba, S3 and Snowflake. In addition, the organization needed a solution that would provide the streaming capabilities of Kafka, without the need for the technical knowledge required for managing Apache Kafka.
Strimzi Kafka can help by providing a Kubernetes-based platform to run Apache Kafka, simplifying its deployment and management. Strimzi automates tasks like scaling, monitoring, and configuration, making it easier for Enexis to use Kafka for data streaming without requiring deep technical expertise in Kafka administration. This allows the company to benefit from Kafka’s streaming capabilities while focusing on their core tasks.
Use case Smart metering
Enexis’ first and biggest use case is built around lifecycle management of smart meters. These smart meters collect vast amounts of consumption data from households and business. This is required for all kinds of purposes, from billing to grid management and from power quality to fraud detection. Within their initial setup, an employee would collect the required data by logging into their low-level AMR system. This workflow was labor-intensive. In addition, company and data rules weren’t being enforced because this wasn’t possible. Because this workflow wasn’t really standardized, request responses were messy.
A streaming plaform
To solve this problem, Enexis required a data streaming platform that would be controllable, scalable, reducing development cycles and manageable in costs both for development and maintenance. Axual provides just that, a reliable and scalable solution around Kafka that doesn’t need a lot of technical knowledge. The platform enables you to assign roles and visualize the data flows. This way, smart meter data is efficiently collected, processed and sent to the teams that required this for their use case.
To enable Enexis to really get going with Kafka, Axual provided support with the implementation and enabled teams by providing training to speed up their adoption path. One of our lead-developers set up the infrastructure and connections to make sure that data produced by smart meters would be available to the people requesting this.
The Result - Strimzi, Kafka and Axual is a success
This implementation of the Axual Platform has resulted in an ongoing collaboration between Enexis and Axual. Enexis has successfully scaled the Axual platform internally, now supporting over 70 streams, 60 applications, and more than 150 developers collaborating on the platform.
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