Getting ahead of feedback

Amazon is making its Greengrass functional programming cloud-to-premises bridge available to all customers…
This is an important signal to the market in the area of IoT, and also a potentially critical step in deciding whether edge (fog) computing or centralized cloud will drive cloud infrastructure evolution…
The most compelling application for [Amazon] Lambda is event processing, including IoT. Most event processing is associated with what are called “control loop” applications, meaning that an event triggers a process control reaction. These applications typically demand a very low latency for the obvious reason that if, for example, you get a signal to kick a defective product off an assembly line, you have a short window to do that before the product moves out of range. Short control loops are difficult to achieve over hosted public cloud services because the cloud provider’s data center isn’t local to the process being controlled. [Amazon] Greengrass is a way of moving functions out of the cloud data center and into a server that’s proximate to the process
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Tom Nolle
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It seems to me that closed-loop thinking is going to be one of the biggest factors to impact OSS in coming years.

Multi-purpose machine learning (requiring feedback loops like the one described in the link above) is needed by OSS on many levels. IoT requires automated process responses as described by Tom in his quote above. Virtualised networks will evolve to leverage distributed, automated responsiveness to events to ensure optimal performance in the network.

But I’m surprised at how (relatively) little thought seems to be allocated to feedback loop thinking currently within our OSS projects. We’re good at designing forward paths, but not quite so good at measuring the outcomes of our many variants and using those to feed back insight into earlier steps in the workflow.

We need to get better at the measure and control steps in readiness for when technologies like machine-learning, IoT and network virtualisation catch up. The next step after that will be distributing the decision making process out to where it can make a real-time difference.

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