.NET / C# / Azure Cloud Software Developer, Consultant, Architect

6/2022 – 10/2024

After the successful development and deployment of an IoT platform at their daughter company “Symmedia” (2020-2022, see below), I transferred to GF Machining Solutions (GFMS) to contribute to the development of specialized applications that leverage this platform.
The Machine Monitor application was designed to provide real-time visibility into machine park operations. This included displaying current job statuses, graphing key performance indicators (KPIs), and offering detailed insight into machine-raised messages. The solution also incorporated statistical analysis of events occurring on individual machines, improving operational oversight and decision-making for the end-users.
I also developed the Sustainability Dashboard, a system that integrates data from power sensors to track machine consumption of electricity and compressed air. The solution correlates power usage with machine states and running jobs, enabling a detailed breakdown of energy consumption per job. This functionality allows for a comparative analysis of job-level power efficiency, empowering users to optimize energy use in their manufacturing processes. A key feature is the system’s capability to process hundreds of data points samples per-second, and storing it in for years. The power curves can then be efficiently graphed and compared, and trends can be shown. For example how cleaning a filter can suddenly decrease power usage, and thus carbon emissions, by double digit percentages. This project is GFMS’s implementation of the efficiency evaluation of machines following ISO 14955 / VDMA 34179.
In addition to application development, I played a key role in optimizing GFMS's cloud infrastructure. I transitioned their solution to a fully automated infrastructure management approach using Terraform, eliminating manual modifications and improving the reliability and scalability of their deployment process. I introduced unit testing frameworks using SpecFlow, enhancing the testing of critical components. I also provided Linux system engineering and consulting on broader system engineering issues, offering expertise in both cloud and on-premise environments.
Key problems solved were how to design multiple microservices that process large quantities of data from thousands of machines, without having to scale out vertically. I was further responsible for DevOps operations of the existing cloud infrastructure.
We developed versions of our software libraries that can be used in the cloud, but also on-prem, so that high security companies in aerospace do not need to send their data into the cloud, but can run the portal applications on-prem. For this we created abstraction layers for CosmosDB (MongoDB), EventHub (RabbitMQ), and Azure Data Explorer (InfluxDB).

.Net, Microsoft Azure, Internet of Things (IoT)

12/2020 – 5/2022

Industrial IoT with Azure for global company in Industrial IoT services
Key technologies: .NET, Java, Spring Boot, Azure IoT Edge, Azure Industrial IoT, OPC UA, Microservices, Kubernetes, GraphQL, Azure Functions, Azure Data Explorer (Kusto, Time Series DB), Azure Event Grid, Azure EventHub, Azure IoT Hub, Azure IoT Edge, Azure Service Bus, Large Scale Data Storage, Service Bus, Mongo DB, Azure CosmosDB, SQL Server, Terraform, ArgoCD, ATTD/Cucumber

symmedia has been developing service solutions for mechanical engineering since 1997. The symmedia SP/1 software is used as the "Internet of machines" in over 100 countries. Leading machine manufacturers and operators use symmedia SP/1 as a convenient service portal: Remote Service, Parts, Maintenance and Monitoring are proactively offered directly at the machine. 

The existing, server/client based product SP/1 offers a remote access, service, and management solution for industrial machine manufacturers worldwide and is being replaced by a green-field developed cloud-based solution. The new product will be used by manufacturers, service providers, and customers to remote service machines, collect data, calculate KPIs, analyze machine behaviour, and provide a global data analysis and processing platform for 3rd party vendors. The scale of the project at project start alone includes several thousand IoT edge devices within connected factories, and gigabytes of data collected per machine for predictive maintenance and quality prediction of the products manufactured. Data collection in the first phase is performed through OPC UA, but Symmedia’s product support includes dozens of custom industry protocols.
The system is built in a way so that Symmedia can offer generic IoT platform capabilities to manufacturers and clients, with a “marketplace” offering 3rd party data acquisition and processing apps, that are then deployed in a safe and shielded environment on the IoT edge devices.

The project: As a cloud solutions architect, together with experts from the client and their parent company, I was responsible to consult and largely design the cloud and IoT edge infrastructure and technical details of most backend services. Besides consulting on the general parts, my focus was on data collection and processing beginning at the factories and IoT edge devices, over hot/cold data path, processing and storing the data in Azure Data Explorer and CosmosDB, and providing GraphQL services that were linked together with GraphQL federation.
I designed and developed the Azure Industrial IoT edge solution starting from the application marketplace, deployment of the solution to IoT edge devices, monitoring, and reporting. This also included the actual application to acquire data via OPC UA from machines and transmit, store, and process it in the cloud. We furthermore analyzed the usage of different industrial protocols, including the emerging umati / OPC UA Machinery specification, and had meetings with VDMA and Microsoft to be able to potentially include this in the Microsoft Industrial IoT solution.
During this project we worked together with the Azure IoT Edge and Industrial Azure IoT Edge teams from Microsoft to fix issues and add much required functionality. I furthermore handled the public bug reporting and generic community interaction  with Microsoft, Terraform, etc.; a long list of GitHub bug reports in Microsoft’s IoT, Industrial IoT, and Azure Java SDK projects gives an overview of this. 
I furthermore introduced concepts like acceptance test driven design using Cucumber, and consulted in integration tests and CI/CD pipelines for end to end testing beginning at the data collection towards the data processing and querying stage. I was member of the core QA team.
The project uses Azure Data Explorer (Kusto) as data storage, and various techniques such as CosmosDB and EventHub for hot path data transmission.
The CI/CD pipelines are hosted on Azure DevOps, extensive integration test suites run on pull request completions, and deployments to test devices start running.
The infrastructure is hosted in Kubernetes and managed with ArgoCD and Terraform.
Most Microservices, Azure Functions, and IoT Edge modules are written in Java (11/17), with some written in .NET Core for specific reasons, or because the mother company GFMS is using .NET exclusively. My hybrid Java/.NET knowledge was an advantage in this project, with my Java knowledge being reactivated at the beginning of the project.

.Net, Graphql, Internet of Things (IoT), Java (allg.), Microsoft Azure, Test Management

9/2019 – 6/2020

Development of microservices, event service platform and architecture

Key technologies: .NET, Microservices, Azure App Service, Azure Functions, Azure FrontDoor, Azure EventGrid, Azure EventHub, Azure Service Bus, ASP.Net Core, Queues, Data Storage, Service Bus, mongoDB, Docker Containers

The project: Development of a stock and reservation tracking system as a .NET Core 3.1 microservice, running in Azure. I used MongoDB as backing database because of the document-based architecture, and the transaction support (only limited support for this in Azure CosmosDB). Test-Driven-
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09 / 2019 – 06 / 2020
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}Curriculum Vitae: S. S.| Project reference (Freelance) Development with ATDD and SpecFLOW, full CI/CD pipeline with unit and functional testing, full API
specification test coverage. Auto-scaling, automatic nightly benchmarks and performance analysis.
Setup and integration of monitoring. Schooling of on-site developers in .NET Core, the technologies used, and principles of ATDD. Help with integration in the existing technology landscape.
Analysis of current communication systems and consulting in creating a new event based architecture. Based on EventGrid and Service Bus, to easily integrate with current and future infrastructures. Defining the interfaces and event types for the first system to use it.

Mongodb, DevOps, DevOps (allg.), Agile Methodologie, Scrum, Test Automation, Testdesign (IT), Software Architecture, .Net, .Net Framework (Microsoft), Backend, C#, Docker, Cloud (allg.), Cloud Computing, Microsoft Azure, ASP.NET, Representational State Transfer (REST), Solution Architektur