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#123 - From Nokia to AI-IoT: Engineering the Physical World with Bernd Groß // CEO @ Cumulocity
Bridging operational technology and cloud architecture for industrial-scale systems
The convergence of AI and IoT is reshaping how technical leaders approach industrial systems architecture. Bernd Groß, CEO and co-founder of Cumulocity, shares insights from building Germany's leading IoT platform—from its origins as a Nokia spin-off to becoming a critical infrastructure for companies managing tens of thousands of connected industrial assets.
This conversation explores the unique engineering challenges of industrial IoT, where systems must process 50 terabytes of monthly data from wind turbines while maintaining real-time control capabilities. Bernd discusses the evolution from monolithic architectures to microservices, the complexity of supporting hundreds of industrial protocols, and the emerging "AI-IoT" paradigm.
Key technical insights:
• 🏗️ Speed-layer architecture design for real-time data processing with cloud data lake offloading
• 📡 Managing protocol complexity through certified partner ecosystems (320+ PLC protocols)
• 🔄 Microservices transformation strategies for industrial platforms on Kubernetes
• 🤖 AI model deployment and operationalization across distributed industrial assets
• ⚡ Edge-cloud hybrid architectures for latency-critical and regulated environments
• 🛠️ Technical debt management during platform evolution and acquisition cycles
Thx 2 our partner SoSafe for sponsoring this Episode.
Or start a free safety simulation with SoSafe
TIMESTAMPS:
[00:01:04] Introduction to Bernd Groß and Cumulocity's Industrial IoT Platform
[00:03:45] Early Programming: From ZX Spectrum to PC Building
[00:07:07] The Nokia Rejection: Language Barriers in Early Career
[00:11:51] Nokia's Innovation Incubator and Cloud Computing (2010)
[00:17:24] Meeting Werner Vogels: Early AWS and Cloud Architecture
[00:20:07] Spinning Off Cumulocity from Nokia Networks
[00:21:21] IoT Device Management: Original Platform Vision
[00:23:56] Real-Time Architecture vs. Legacy VPN Systems
[00:26:33] From APIs to Applications: Learning Customer Needs
[00:31:19] Software AG Acquisition: Strategic Partnership
[00:34:03] Management Buyback from Silver Lake Partners
[00:37:53] AI's Impact on IoT: The Emergence of "AI-IoT"
[00:42:03] Speed-Layer Architecture and Data Lake Integration
[00:46:46] Edge vs. Cloud: Hybrid Deployment Strategies
[00:48:53] Technical Debt: Protocol Complexity and Modernization
[00:52:37] Partner Ecosystem: Managing 320+ Industrial Protocols
[00:56:59] Leadership Lessons: Trust and Authentic Communication
QUOTES:
• "When you compare that to the generation, the technology which was available before, there was really a VPN system where you needed to dial into the wind turbine… And today it's very, very different with real-time analytics happening in the background." - Bernd Groß [00:23:56]
• "Our platform does data acquisition, data normalization, contextualization of the data. So you need to help structure the data because that is the foundation for your training for your AI model training." - Bernd Groß [00:42:03]
View all episodes
By Tobias Schlottke - alphalist CTO Podcast
5
66 ratings
Bridging operational technology and cloud architecture for industrial-scale systems
The convergence of AI and IoT is reshaping how technical leaders approach industrial systems architecture. Bernd Groß, CEO and co-founder of Cumulocity, shares insights from building Germany's leading IoT platform—from its origins as a Nokia spin-off to becoming a critical infrastructure for companies managing tens of thousands of connected industrial assets.
This conversation explores the unique engineering challenges of industrial IoT, where systems must process 50 terabytes of monthly data from wind turbines while maintaining real-time control capabilities. Bernd discusses the evolution from monolithic architectures to microservices, the complexity of supporting hundreds of industrial protocols, and the emerging "AI-IoT" paradigm.
Key technical insights:
• 🏗️ Speed-layer architecture design for real-time data processing with cloud data lake offloading
• 📡 Managing protocol complexity through certified partner ecosystems (320+ PLC protocols)
• 🔄 Microservices transformation strategies for industrial platforms on Kubernetes
• 🤖 AI model deployment and operationalization across distributed industrial assets
• ⚡ Edge-cloud hybrid architectures for latency-critical and regulated environments
• 🛠️ Technical debt management during platform evolution and acquisition cycles
Thx 2 our partner SoSafe for sponsoring this Episode.
Or start a free safety simulation with SoSafe
TIMESTAMPS:
[00:01:04] Introduction to Bernd Groß and Cumulocity's Industrial IoT Platform
[00:03:45] Early Programming: From ZX Spectrum to PC Building
[00:07:07] The Nokia Rejection: Language Barriers in Early Career
[00:11:51] Nokia's Innovation Incubator and Cloud Computing (2010)
[00:17:24] Meeting Werner Vogels: Early AWS and Cloud Architecture
[00:20:07] Spinning Off Cumulocity from Nokia Networks
[00:21:21] IoT Device Management: Original Platform Vision
[00:23:56] Real-Time Architecture vs. Legacy VPN Systems
[00:26:33] From APIs to Applications: Learning Customer Needs
[00:31:19] Software AG Acquisition: Strategic Partnership
[00:34:03] Management Buyback from Silver Lake Partners
[00:37:53] AI's Impact on IoT: The Emergence of "AI-IoT"
[00:42:03] Speed-Layer Architecture and Data Lake Integration
[00:46:46] Edge vs. Cloud: Hybrid Deployment Strategies
[00:48:53] Technical Debt: Protocol Complexity and Modernization
[00:52:37] Partner Ecosystem: Managing 320+ Industrial Protocols
[00:56:59] Leadership Lessons: Trust and Authentic Communication
QUOTES:
• "When you compare that to the generation, the technology which was available before, there was really a VPN system where you needed to dial into the wind turbine… And today it's very, very different with real-time analytics happening in the background." - Bernd Groß [00:23:56]
• "Our platform does data acquisition, data normalization, contextualization of the data. So you need to help structure the data because that is the foundation for your training for your AI model training." - Bernd Groß [00:42:03]
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