What is the connection between AI, Cloud-Native and Edge devices?


I was asked this question: What is the connection between AI, Cloud-Native and Edge devices?


On first impressions, it sounds like an amalgamation of every conceivable buzzword around - but I think there is a coherent answer which points to a business need. 


Let us start with the term ‘Cloud Native.’


Cloud-native computing is an approach in software development that utilizes cloud computing technologies such as

  • Containers
  • Microservices
  • Continuous Delivery
  • DevOps


Using Cloud Native technologies, we can create loosely coupled systems that are scalable and resilient.


In practice, this means

a) The system is built as a set a set of microservices that run in Docker containers

b) The containers may be orchestrated via Kubernetes

c) The deployment is managed through docker containers through a CI/CD process


In itself, this approach is valuable and follows a stack that is rapidly emerging at the Enterprise level. 


But how does it tie to Edge devices?

  1. Docker allows you to create a single packaged deployment through a container, which creates a virtualized environment at the target device. AI models are trained in the cloud and deployed on edge devices. The docker/ cloud-native format enables you to run AI in containers across various environments, including at the Edge. The container-based architecture is especially relevant for AI on edge devices because of the diversity of devices.
  2. Secondly, AI models need to be refreshed and deployed frequently – including on edge devices. For this reason, also, the cloud-native and container architecture helps.


Welcome thoughts and comments

Image source: Cloud Native Definition


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Tags: dsc_ai, dsc_tagged


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