"When you build a production analytic or AI system, there are two parts of the problem. One is having the right data and data access, and the other part of the problem is the analytics: actually running the software to analyze the data. Analytics applications require a lot of coordination, and with the increasingly widespread containerization of applications, it's essential to have a way to coordinate processes running in containers. Kubernetes, an open-source orchestration system for managing deployment of containerized applications, is emerging as a leading solution. But to avoid being limited as to which applications can be containerized, you need a data platform with the capability to persist data (state) from containerized applications as a variety of data structures.
It's an undeniable fact how a mobile application can add more simplicity and comfort to our lives. There are positively plethora of apps out there that demonstrate this point. Customization has added another layer to applications that can adjust and change following the client. Organizations like Apple and Amazon have shown the effect that human-made brain power can have on a machine unit with developments like Siri and Alexa. These voice-controlled AI applications assist users with their daily errands and chores.