Part3: Use case on Migrating real time IoT data analytics to Edge

As-Is Solution

Migration Plan

  • Core edge platform identification team.
  • Edge platform and administration development team.
  • AI team.
  • Data Engineering team.
  • Solution and services team.
  • Main dashboard and alerting was tweaked to include to show only the alerts, notification, decisions and windowing output done by the edge.
  • An application service will run at the edge side. If a user still needs to access real time data, then request will be forwarded to the edge instance(Since all gateways are present in same VPC, they are discoverable)
  • Edge uploads daily telemetry data as a nightly job to the google storage bucket. This data was used by further model development

Deployable Pipeline:

  • If a decision based control is required, for e.g as part of Pipeline an AI service is invoked and based on response some decisions need to be taken, it is difficult.
  • Any customizations that are required needs to be written using jython.
  • Even if you manage to find a jython resource, it is tough to integrate the customizations along with CI/CD processes.

Local Data Storage

  • Async file uploads during non peak hours
  • Detailed data becomes available for data modelling.



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