Siemens Modernizes Manufacturing with Confluent’s Data Streaming Platform

Siemens technology transforms everyday infrastructure that drives digitization initiatives in everything from power grids to railways and hospitals.

With solutions spanning industrial automation, smart buildings, and healthcare systems, success depends on maintaining consistent real-time data flows that enable faster product delivery, operational visibility, and seamless communication between factory equipment and business applications.

But progress was stalled by inefficient Kafka clusters that escalated costs, restricted consumption tracking, and required dedicated infrastructure across each department—even for the smallest pilot projects.

Confluent’s data streaming platform dramatically simplified how teams access and share information at Siemens by creating a unified data backbone that connected operational technology with business systems.

Now, Siemens teams focus on what matters most: connecting physical equipment with digital systems, getting products to market faster, and improving visibility through real-time data.

A Kafka cluster headache for Siemens

Providing smart technology for factories, power grids, and healthcare systems across 200+ countries generates a mountain of data. 

And while Siemens was capturing all of its critical day-to-day operations data using open-source Apache Kafka®, that data was stored, inefficiently, across disconnected systems.

"Each department that requested Kafka would receive their own dedicated cluster, which frequently sat underutilized," explains Jose Carlos Mendes Neves, Service Owner at Siemens. "We couldn't share resources between them, and tracking what each team was actually using was nearly impossible."

Independent clusters meant critical factory data remained isolated from business systems, which limited how Siemens could use its data while simultaneously increasing costs and technical complexity. 

This approach didn’t align with Siemens’ future aspirations. "We needed one centralized platform that could support our data and AI strategy globally," says Jose Carlos. "Something that would let different types of systems talk to each other while eliminating all the infrastructure complexity."

That’s when Siemens turned to Confluent…   

Deploying a platform built for simplicity and scale

Siemens deployed Confluent as the data streaming platform for its unified data strategy.

With Confluent serving as their centralized data streaming backbone, Siemens could seamlessly connect their operational estate with their analytical estate. Using Connectors, the data is now able to flow efficiently between Siemens’ global network of applications, ERP’s and inventory management systems to the data warehouses, and AI/ML platforms. As the complexities of Kafka infrastructure are handled by Confluent, Siemens' technical teams could shift their focus from maintaining clusters to putting their data to work—creating business value and operational efficiencies, instead of managing technical overhead.

Creating a "Topic as a Service" model for enterprise-wide adoption

Through Confluent, Siemens created a "Topic as a Service" model where teams can request any "topic" – a stream of data within an Apache Kafka cluster – they need without worrying about the technical details.

"'Topic as a Service' lets our internal customers simply order the number of topics they need for each project," explains Anibal Pereira, Service Owner at Siemens. "They don't have to understand Kafka, maintain infrastructure, or worry about scaling, they just focus on the data."

This approach was particularly valuable for departments just starting with data streaming. Teams can begin with just a few topics, see immediate results, and expand as needed—all without significant upfront investment or specialized expertise.

Additionally, Confluent's elastic scaling capabilities mean workloads automatically adjust to meet demand. "With Confluent, the throughput increases as our usage grows, without needing to manually scale up clusters," notes Jose Carlos.

This approach has transformed Siemens' data infrastructure, turning what was once a collection of fragmented, underutilized resources into a streamlined, cost-efficient platform that scales with actual usage.

Product-like thinking for master data management

One of Siemens' early use cases was the creation of a Product Master Data Streaming solution, which transforms how product information flows throughout the organization.

This initiative marked a pivotal shift in how the organization viewed data, treating it as a product rather than scattershot leftovers of business processes. "Previously, our product data was trapped in batch processes, and treated as an afterthought rather than a strategic asset," explains Stefan Baer, Senior Key Expert for Data Integration, Siemens. "We transformed our approach to event-based data streaming, positioning master data as a service that internal customers could use and build upon"

The new architecture decouples producers and consumers, allowing SAP systems, e-catalog generation systems, and regional sales systems to interact seamlessly.

"Before, regional sales systems could wait up to four weeks for product updates. With Confluent, this has been reduced to just two days, with consumers receiving updates as soon as they're processed."

Siemens’ platform handles an average of 2 million produced messages and 8 million consumed messages daily, with peaks of up to 19 million messages during major price updates. But despite this high volume, the system typically operates at just 3% of cluster load as resources are accessed and managed incredibly efficiently. 

Diverse use cases powered by "Topic as a Service"

After the initial success, Siemens looked to expand its use of Confluent across the business, with teams developing innovative solutions for their specific challenges. 

Modernizing factory logistics with data streaming

Siemens has modernized its factory logistics through a modular platform built on Confluent. This solution utilizes a microservices architecture to improve the internal supply chain, ensuring the right materials arrive at the right time for production.

"We analyzed our monolithic system and separated it into standardized pre-packaged software components," explains Stefan. "The communication between these business capabilities is now asynchronous and runs via Confluent Cloud."

The results were transformative: in-time delivery of materials, no manual reordering needed, and a fully automated push-based supply chain. The architecture's flexibility eliminated rigid customized connections and enabled easy integration of reporting and monitoring systems.

Quality inspection data management

Another valuable implementation is Siemens' quality inspection data management lifecycle. Using Confluent, quality inspection machine parameters and test results are streamed from SQL databases to a centralized location, where they're verified for each machine type.

"The validated or modified parameters are then sent back to quality inspection using data streaming," explains Jose Carlos. "This continuous improvement loop would be impossible without real-time data streaming, and it has significantly improved our quality processes by creating a single source of truth for inspection reports across our facilities."

Asset collection and job orchestration

Siemens also implemented an asset collector and packager system using Confluent Cloud for topic orchestration. This system manages tasks between various asset management systems, providing full transparency of processes through robust monitoring capabilities.

"Snaplogic serves as our main integration tool, while Confluent Cloud handles all the topic orchestration," notes Stefan. "This makes it incredibly easy to add or change requesting or generating applications without disrupting the overall system."

By centralizing asset management workflows, Siemens has achieved greater agility, improved tracking capabilities, and enhanced collaboration between teams working with digital assets—resulting in faster time to market for new products and services.

Faster operations, connected systems, and significant cost savings

Huge savings through resource optimization

By consolidating resources through Confluent, Siemens has eliminated underutilized infrastructure and gained better cost control over their data infrastructure. 

"By centralizing our Confluent deployment, we've leveraged both volume discounts from our annual commitment and the efficiency of a shared platform," explains Anibal. "Plus, individual departments no longer need dedicated clusters, which significantly reduces our overall infrastructure costs too.”

A bridge between IT and OT Systems

In its manufacturing division, Siemens uses Confluent to break down the barriers between operational technology (OT) and information technology (IT) systems.

"We're streaming data from industrial devices directly to energy management applications using Kafka in Confluent," explains Anibal. "This integration is helping us merge the OT and IT worlds into a single data ecosystem."

This convergence of previously siloed systems enables Siemens to develop comprehensive digital twins of their physical systems, supporting everything from predictive maintenance to real-time operational optimization.

Real-time quality improvements loops

With real-time data, Siemens implemented a new quality inspection lifecycle system for its machines that resulted in a faster and more visible quality process, quality reports, and test certificates.

Siemens streams quality inspection machine parameters and test results from an SQL database to a data sink. Then in a centralized location, parameters and test sets are verified for each machine type. The validated or modified parameters are then sent back to the quality inspection team using Confluent. 

"This continuous improvement loop would be impossible without real-time data streaming," says Jose Carlos. "This approach has significantly improved our quality processes and created a single source of truth for inspection reports across our facilities."

What’s next for Siemens and Confluent?

Looking ahead, Siemens is expanding its service platform to support more diverse use cases across the organization.

"We're focusing heavily on automation to make our service even more accessible," explains Anibal. "By creating a self-service portal where teams can request topics, monitor usage, and estimate costs, we'll accelerate adoption while maintaining governance."

The team is also exploring stream processing with Apache Flink to unlock more sophisticated real-time analytics within their data streams.

"As we expand our platform, we're actively contributing to Siemens' broader digital and AI strategy," says Jose Carlos. "The data streaming foundation we've built with Confluent will increasingly power our factory modernization initiatives and smart infrastructure deployments."

Siemens sees their Confluent-powered data streaming platform as essential to their vision of combining the physical and digital worlds. By enabling real-time data flows between operational systems and business applications, they're creating the foundation for a more efficient, sustainable, and data-driven organization.