Leo and Simona (Senior Product Program Manager, Microsoft) continued their Azure IoT Operations video series with an in-depth discussion on OPC UA (Open Platform Communications Unified Architecture).
The conversation covered OPC UA fundamentals, security practices, data modeling, and Microsoft’s approach to scalable industrial IoT operations—including use of an OPC UA broker and orchestration via Kubernetes.
Key takeaways included the importance of secure, scalable data connectivity from industrial assets to the cloud, and the transformation of physical assets into Azure resources.
The session included hands-on demonstration elements, highlighting OPC UA broker architecture and practical asset management in Azure IoT Operations.
Action Items
No explicit action items or due dates were mentioned in the transcript.
OPC UA Fundamentals and Industry Context
Simona explained OPC UA is not merely a protocol but a standard managed by the OPC Foundation that provides secure, standardized connectivity and data modeling for industrial automation.
OPC UA bridges operational technology (OT) and information technology (IT), addressing both openness in data models and robust security for connected industrial devices.
Security, including authentication, authorization, certificate management, and support for multiple communication protocols (e.g., TCP/IP, UDP, MQTT), was emphasized as central to safe digitization.
Microsoft has been involved with OPC UA since its inception and supports both open-source and proprietary data models.
Security, Connectivity, and Schema Management
Proper configuration of OPC UA servers and clients—especially around endpoint URLs, security policies, and certificates—was highlighted as critical for successful and secure connectivity.
Common connection issues are often due to misconfiguration or rejected certificates; reviewing server policies and rejected certificates is crucial for troubleshooting.
OPC UA namespaces and schemas enable standardized data extraction and mapping, but raw industrial data often requires schema interpretation for meaningful analytics.
The push for more openness and interoperability in data schemas, including support for customized or advanced schemas for AI models, is ongoing.
Microsoft’s OPC UA Broker and IoT Operations Approach
Microsoft has developed an OPC UA broker to simplify and scale industrial asset connectivity, leveraging Kubernetes for infrastructure scalability and high availability.
The OPC UA broker’s architecture includes Discovery Handler, Connector, and Operator components; it integrates with Kubernetes APIs and supports seamless asset onboarding and data extraction.
The broker enables publishing of OPC UA telemetry to MQTT brokers, supporting both real-time monitoring and historical analysis, with a focus on zero data loss and event-driven insights.
Asset management is tightly integrated: device endpoints, schemas, and telemetry definitions are managed as resources in Azure, enhancing digital transformation and data science capabilities.
Demonstration and Practical Configuration
Simona demonstrated asset discovery, connection, data publication, and management within Azure IoT Operations, using both simulators and actual asset endpoints.
The demo showed the process from endpoint configuration, schema definition, certificate validation, to end-to-end data flow into Azure resources.
Asset types, endpoint profiles, and writeable parameters are managed via configuration files, supporting both out-of-the-box and advanced custom schemas for various use cases.
Practical advice included involving OT experts early, using configuration files for repeatable deployments, and validating connectivity and telemetry at each step.
Decisions
No formal decisions were specifically made or recorded during this episode.
Open Questions / Follow-Ups
Continued work needed on automating discovery handler execution for asset changes.
Further developments planned around enriching schema management and enabling more flexible, open, and interoperable data modeling.
Ongoing advancements anticipated in achieving true zero data loss for industrial IoT telemetry streams.