Powerful basis for optimal AI analysis of large amounts of data
In the area of IIoT, DaSense analyzes and evaluates large amounts of data for various business areas of the customer. Marketing data as well as development and production data are controlled with the AI software and visualized in tables and graphs using dashboards. The underlying architecture was previously a Hadoop cluster. In the current project, this architecture is to be raised to a modern level. For this purpose, Hadoop is replaced by Kubernetes.
Microservice-based architecture, containers and Kubernetes are the current standard for optimally operating AI and big data solutions. In the microservice-based approach, software is developed in a modular manner, existing software is divided into smaller, independent units. These building blocks are packed into containers in which all the files, certificates or configurations associated with the software are bundled. This makes the software more flexible and faster, because these containers can be duplicated by the system without any further action. This increases scalability and ensures the same standards throughout the company.
Kubernetes architecture automates complex operations
However, the containers are more complex to operate. Here Kubernetes supports. Kubernetes is a system developed by Google as open-source software for operating a container environment that is currently establishing itself as a standard. Central services of the previously manual operation are automated by Kubernetes. The system monitors the instances independently and, for example, starts up a corresponding replacement if a server fails. This makes the system reliably fail-safe and always highly available. In addition to scalability and high availability, the current project also aims to achieve cloud capability and "Service as a Code" with the new architecture. In the form of containers, applications can be easily brought to different cloud platforms since the environment plays a subordinate role for them.If a new service is implemented, only the current configuration file needs to be checked in, and Kubernetes takes care of the implementation. This creates versionability.Another plus point for the customer is that the packaged solution set up in Germany can be passed on to foreign branches and installed identically there.
“From a technological point of view, big data analyzes, and the use of artificial intelligence take place on several levels. Users can only exploit the full potential of AI if applications and the underlying architecture are optimally coordinated. And that brings joy to the technology: When huge amounts of data can be analyzed in real time and there are no limits in the system, neither in the application nor in the implementation of ideas," explains Dr. Tobias Abthoff. “With the development of the Kubernetes architecture, NorCom is consistently pursuing the strategy of always offering its customers the most advanced open-source technology. We are happy to have found a customer who is so open to new developments.”
Die NorCom Information Technology GmbH & Co. KGaA entwickelt und implementiert Big-Data-Lösungen für internationale Unternehmen. NorCom unterstützt Kunden dabei, ihre Daten in weltweit verteilten Rechenzentren mithilfe moderner Big-Data-, Machine-Learning- & Deep-Learning-Tools in einer produktiven Umgebung zu bearbeiten und analysieren.
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