The Self-Driving Network™ Episode 4_ The Progression copy
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The vision of
a self-driving network
might seem
a very difficult one.
And many people ask me,
"Is that a ten-year journey?
Is that a five-year journey?
How do we get there?"
The first thing is there's some
base technologies that you need.
Definitely you need automation.
Automation makes a lot of
the mundane tasks easier to do. . .
The second thing
you need is telemetry.
You need to know
what the network is doing.
You need the network topology. . .
You need to know
what kind of flaws are going on,
who's talking to whom.
And you need that information
in real time,
in a way that's consumable
by machines
so that you can do the analysis.
And the next step is
that analysis that you want to do.
So you want to be able
to look at all this data,
and then figure out
what should be done.
And you could use
rule-based systems to do that
or you could use
machine learning to do that.
Probably you'd use
a combination of those two.
And that will get you to an action
that you need to take.
And then you take that action
again going back to the automation,
you can push that action
out to many things.
And if I see something
anomalous going on
in some part of the network,
I can zoom in and say
"What's going on there?"
and say "Oh, it's okay. It's not bad."
Or maybe I have
to take some action.
And then I'll zoom out again.
And so I can have the right level
of telemetry whenever I need it.
An important component of self-driving networks is intent-driven networking,
or declarative programming, where you
express what you want the network to do
rather than telling
every device how to do it.
And that makes your job
much easier...
This is a journey
that's going to take a while.
But we have
a lot of elements today.