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Exposing the True Nature of the Robust IoT Cloud

Exposing the True Nature of the Robust IoT Cloud

The True Nature of the Robust IoT Cloud Service

Episode 21

On the surface, building your own IoT cloud seems pretty straightforward, but brush away some of the fluff and you’ll find the non-trivial issues of data velocity, message processing, scalability, redundancy and robustness. In this episode of the IoT Business Show I discuss the IoT cloud with Dan Collins, its differences with the IT cloud and the issues to consider when building or buying.

In this episode of the IoT Business Show, I discuss the IoT cloud with Dan Collins, its differences with the IT cloud and the issues to consider when building or buying.

Dan is the Chief Data Officer at ThroughTek. He got his PhD in Physics from University of Oxford and then joined the British Government as its first data scientist. He is currently working on data collection and analysis for ThroughTek.

It’s relatively easy to use a bare metal cloud service to spin up a small cluster of machines to ingest small amounts of data. All the core functionality is available but stitching together the various services to handle high velocity data, with the right priorities in a way that is scalable, robust and resilient to failure is a hard engineering problem to solve. But that’s the point – it’s an engineering problem. Although there will certainly be corner cases, developing the IoT network fabric doesn’t need to be an IoT product company core competency. Don’t reinvent the wheel and create your own IoT cloud unless absolutely necessary. Buy or rent an IoT cloud service or IoT platform that has already worked through all the hard issues for you.

Here’s What We’ll Cover in this Episode

  • The differences between an IoT cloud and an IT cloud
  • The need for a robust stream processing system
  • The data audit
  • Why you generally need both stream and batch processing
  • The importance of data transfer in a distributed cloud environment
  • The undiscussed issues that arise when dealing with thousands of data streams in the cloud
  • IoT cloud business and technology best practices
  • The upfront importance of schema design and data modeling

Mentioned in this Episode and Other Useful Links

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