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Windows Admin Center and System Insights.

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The AZ‑800 exam gets more into Windows Admin Center holistically,

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Here,

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we're concerned with a specific capability that we use WAC

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to manage and that is a Windows feature,

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a Windows server feature called system insights.

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You should be aware walking into AZ‑801 that system insights is not

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a cloud service, and this comes as a surprise,

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I think,

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initially because we started this course looking at all the different

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Microsoft 365 cloud services that we can leverage,

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including their artificial intelligence capabilities,

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to help in our hybrid cloud administration,

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but no, this one runs entirely on Windows server locally,

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and what it offers you is predictive analytics with no cloud dependency.

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Now what does that mean?

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Well,

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the short Cliffs Notes explanation here is that system insights takes

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advantage of some artificial intelligence actually.

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There are some machine learning models integrated into system insights,

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these are called capabilities, that can look at your data historically.

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You'll want to have it run for a while before it can

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start to make good predictions, but it can give you good predictions.

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You're going to be running out of space on your disks pretty soon.

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It looks like your CPU is going to need an upgrade.

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It looks like your disk maybe reaching end of life.

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These are some of the business use cases.

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Now depending upon your sample time if you're doing

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per second per minute per hour,

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you want to think about the footprint that system insights will have.

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You can selectively enable or disable capabilities,

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and again, you can adjust the data collection aggressiveness.

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You get 1 year of data retention here.

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You configure it with Windows Admin Center,

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like I mentioned before,

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and the built‑in capabilities are on CPU and network capacity forecasting,

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and then for storage, storage and volume consumption forecasting,

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and these capabilities, the framework and API is extensible.

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So it's likely over time we'll see more and more providers support on where

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you can load and look at different aspects of your system,

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and again,

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taking advantage of machine learning where it's able to take

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new data that's arising from your system,

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compare it to the model that it's developed or it's been

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trained to develop over time in the past,

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and make a prediction on that given subsystem.

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That's the value prop. Let's take a look at a demo now.