The Oluwatosin Oladayo Aramide Interview.

With 16+ years of experience in enterprise, data center, and cloud environments, Oluwatosin Oladayo Aramide 🌍💻 is a powerhouse in networking. A CCIE-certified engineer with deep skills in automation and security, Tosin has led groundbreaking projects across AWS, the United Nations, and now NetApp—where his work in automation, congestion control, and interoperability is shaping the future of hybrid cloud. In this interview, Tosin shares his journey, defining moments, and insights into AI, cyberwarfare, and the next generation of networks ⚡🔐. From personal growth to global tech challenges, this conversation bridges innovation, resilience, and vision for the future. 🚀

https://www.linkedin.com/in/iamaramide/
https://www.researchgate.net/profile/Oluwatosin-Aramide

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Episode Transcript

Speaker 1 (00:00):
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(00:23):
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welcome all, enjoy the show. Ladies and gentlemen, Plaza, welcome
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Speaker 2 (00:43):
Good morning, good evening, good afternoon, depending on where you
are in the world. My name is Deanie and this
is Vigilantes Radio live right here on iHeartRadio. We have
a very special for We have a special guest for
you guys. Before I go any further though, this is
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(01:04):
it to your inboxes.

Speaker 3 (01:05):
And for you guys who subscribe to the show, you'll
be the first to know, and I always appreciate that. Well,
this is the frequency of the fearless. You know, technology
shapes the world we live in, but it's the engineers
behind the scenes who design the backbone of how we connect, communicate,

(01:26):
and defend today's guests.

Speaker 4 (01:28):
Has spent over sixteen years mastering.

Speaker 3 (01:30):
The art of networking, from data centers to the cloud,
from automation to security. His journey spans the United Nations,
Amazon Web Services and now NetApp, where he's pushing the
limits of what networks can do. You're not just here
for a talk show. And this isn't just radio. This

(01:51):
is revival for your mind, body, and spirit. This is
Vigilantes Radio Life. My name is Coachtini and change is possible.

Speaker 4 (02:01):
Are you ready?

Speaker 5 (02:08):
Are you ready? Are you ready? Are you ready?

Speaker 4 (02:23):
All right? All right again, Welcome to the show. You're
listening to VRL.

Speaker 3 (02:27):
That's Vigilantes Radio Live right here on iHeart Radio, and
I am your host, Deani. Our interviews are designed to
go beyond music, news, books, art, acting, films, technology, education, entrepreneurship, entertainment, spirituality,
and sometimes even past that thing that we call the ego.

(02:48):
Our interviews are designed to go behind the scenes into
the minds of these brilliant people, you know, the ones
who are out there giving it. They're all for me,
for you, and for the world.

Speaker 4 (02:59):
Will ladies and.

Speaker 3 (03:00):
Gentlemen with more than sixteen years of global experience and networking.
Oluwa Toosen Oladeo Aramadi is a seasoned engineer, innovator.

Speaker 4 (03:14):
And thought leader.

Speaker 3 (03:15):
From deploying massive infrastructures at AWS to spearheading experimental R
and D at NetApp, his expertise spans automation, lossless networking,
and high performance computing fabrics. A CCIE and multi center professional,
Toson's work has reduced timelines, solve complex intereropability issues, and

(03:40):
advanced the state of networking across industries.

Speaker 4 (03:44):
His insights on AI, automation.

Speaker 3 (03:46):
And cyber warfare place him at the forefront of tomorrow's
digital battles. So please join me in saying welcome friend
to Tosin.

Speaker 4 (03:57):
Hey, Hey, welcome to the show. Hi, how are you
doing good? How are you good?

Speaker 6 (04:04):
Good?

Speaker 4 (04:04):
Thank you for having me chip absolutely toting.

Speaker 3 (04:07):
So, before we get into your incredible journey career and research,
what's been on your mind or inspiring your thoughts in
the recent weeks?

Speaker 6 (04:19):
Yeah, what's being in my mind?

Speaker 7 (04:22):
It is our much of the road of network and
it's saying because of are like for years networks we're
seeing seeing as trumping not important but also invisible. Now
with AI, big data networks have moved to the centers
in the vision right before traffic is network is just

(04:46):
saying as a path to move.

Speaker 6 (04:49):
Data from one point together.

Speaker 7 (04:50):
But at the moment you actually need to give a
touch to watch are actually building the network for.

Speaker 6 (04:56):
Instid of you're building the network.

Speaker 7 (04:58):
Reason have you building your road for example, You're actually
building the road for the kind of vehicle that's going
to be using that road or the kind of instrument
that will be going through that out.

Speaker 6 (05:09):
So you can't train large language.

Speaker 7 (05:11):
Models or one I performance coage without thinking about legacy,
convergency and lost as salvage.

Speaker 6 (05:20):
Else you will be building GP us building.

Speaker 7 (05:25):
Started fabrics, but underlaying network is not efficient for us.
In one of my papers JA and Impact on the
Residents Air Fabric Design, I argue that data locality and
distributed intelligence than our baseline as our based adoptions.

Speaker 6 (05:44):
Are exactly.

Speaker 7 (05:46):
What I see in practice, focusing on not just bands
but the G time.

Speaker 6 (05:50):
The minimization precise is.

Speaker 7 (05:53):
A PC PFC tuning and yes is tuning I predictable
conjection behavior so you abstoually know the way your network
is going to behave before you can view on this.
So all this I've been in my mind literally thinking
about II is changing our feud. II is going to

(06:14):
make food better. I AI doing see.

Speaker 6 (06:17):
You prove our. I try to perform in the industry.

Speaker 4 (06:22):
Indeed, to is my my curiosity, and I won't. I don't.

Speaker 3 (06:27):
I don't want to say problem. But I keep seeing
the term automation. No matter which industry I tend to,
I tend to cross, it's automate this, automate that, automate this. Hey,
this will make your workflow faster if.

Speaker 4 (06:43):
You automate this.

Speaker 3 (06:45):
And me, I'm I'm I'm technical, but not that technical
to understand, uh what automation is. So maybe you could
simplify it for me and help me understand, like why
I need I know, I know AI is here to stay.

Speaker 4 (07:01):
I even use AI uh for the.

Speaker 3 (07:03):
Most intricate parts of what I do, from booking to to.

Speaker 4 (07:10):
Just like sending the email. Those are things I do
automate so I don't have to sit here and type
type type. You know, that's old. That's old. That's doing
it the old way. You know, we're in a we're
in a new century.

Speaker 3 (07:24):
Now, we're in a new digital age where if you're
not using AI or technical based automations.

Speaker 4 (07:31):
Year behind, you're behind the curve.

Speaker 3 (07:34):
Uh So maybe you can simplify that for me, Why
how can I understand automation better to maybe even write
programs myself that would take care of the nuances of
even what I do in everyday life.

Speaker 6 (07:47):
I basically have to.

Speaker 7 (07:50):
Because you do you do my ninety For example, do
you where you turn out your turning your PC antire
apossible some couple of programs that you want to work
with for the day, like you're timing out your web browser,
open your zoom zoom.

Speaker 6 (08:07):
Or wapp or idmessic.

Speaker 7 (08:09):
You can basically just write a screet that immediately you
turn on your computer and you love and you launch
that particular skip, it's going to run open all those
time now, open all the subtworts for you, run all
the necessary things, and everything keep running with it for
you to ask. In my opinion, that amplifies how we

(08:30):
work from on the day to day and it's not
replacing us. It's just happening us to be more efficient.
Like people currently say in the industry, AI is not
going to take your job because someone that knows how
to use AI is going to take a job. So
going from the traditional automation that does things based on

(08:51):
what you've told him to do, so too AI that
basically understand you even more than you know yourself. So
for example, this is just apothetical. In the morning, when
I wake up and my AI see the time that
it's already five seven o'clock, that start my day. So

(09:11):
you start of me coming on my computer and launching
those it says the time it knows that I've worken up.
There's on one or two activities primaters that have fled
into the AI, into the assets and launched all these
applications get things running for me. So it eliminates things
like me launching the script, It eliminates things like me

(09:35):
opening my laptop to do that.

Speaker 6 (09:36):
It just takes over.

Speaker 7 (09:37):
The the activity, basically making me more efficient, making me
more effective. They can getting you ready before I I'm
even ready. So it's going to make our life better.
The better we know how to use it, the better
we know how to interact with it, the more efficient

(09:58):
we get. So I don't see the area are green anyway,
but I see AI. It leave forward from our traditional as.

Speaker 4 (10:07):
Admission absolutely go ahead.

Speaker 7 (10:12):
I wrote the paper around that twenty twenty four assist
network monitoring using them and multi agent systems because it
was basically, I need to partner with a machine. At
the end of the day, it looks it looks dystopian,
but that is what it is at the moment, and

(10:33):
the future of engineers will spend less time thye, paying
config thipe pain scripts and most time formulating polites, validating
outcomes and designing and architecting graduates around our day to
day activities.

Speaker 4 (10:52):
And d indeed, thank you for the answer. So let's
talk about your journey.

Speaker 3 (10:56):
You know what first inspired you to become a net
work engineer and were there any early challenges that shaped
your path.

Speaker 7 (11:07):
Yeah, I originated from my GA and my doing doing
my secondary school es. Todays I was the president of
Engineer Engineers in my secondary school, so engineering has been
something in great intervitings that retired. And while going up,

(11:28):
I had an uncle in the UK and I to
make a cotting you have to go to a phone
boot and uh, it was always fascinating to me. I
was packet moved from Nigeria to the UK, so that
got being into engineering, made me made me studied electric
electronics and at the end of the day moved started

(11:49):
to lay complication engineering in Italy from my master's degree.
So it's just the curiosity of our things work on
done it and just the meetings. But we had led
me to writing different papers on programmable, programmable and data
plane five performance networking.

Speaker 6 (12:08):
Basically instead of us.

Speaker 7 (12:10):
Using the traditional I say that and the manufacturer as
pre configure to move back and in a sact exertain way,
basically now using something called Intel P four, if I
would program my own asy and how to move packets
from the source to destination and can even dorig in

(12:33):
trigger analysis on those pockets before moving from sauce to
a destination, be enforcing subsecurity policies, encryption and decryption on
the make itself. So all this uh evolution technture advancements

(12:54):
got me inspired into integering into the secondinery and specifically
I think that's kicking me in the industry even up
party now.

Speaker 4 (13:05):
Awesome. Uh So.

Speaker 3 (13:08):
Of all the projects you've led, you know, from a
WS migrations to net app innovations.

Speaker 4 (13:15):
And I read a few of your papers. Uh I forgot.

Speaker 3 (13:20):
Which which platform that was, but he had quite a
few and some that you wrote recently this month alone,
I think two of them.

Speaker 4 (13:28):
So I read, I read a few of your your projects.

Speaker 3 (13:33):
Which one of these like a WS migrations to net
app innovations, which one most changed the way you approach
technology today?

Speaker 7 (13:42):
Yeah, like I would say about the sixteen everything that
everything that shaped me into the network engine and today.

Speaker 6 (13:50):
So coming from if tried.

Speaker 7 (13:52):
Show that precedent, well like when I was working for
the United nationships thinks I want you think that difference
compared away what Pascuala like amazonay A building data centers
upon in in in the range of hundreds of terabytes
of traffic, of capacity and traffic model, and you most

(14:14):
building data centers Gonta do any form of operations and
the diss are centers without affecting customer traffic. So this
has just shipped me into knowing that efficiency is not
it's not you can't it's not a trader, it is

(14:34):
in sang in the business is trigger to the industry
moving to a company like Netra well build we are
solely in chat of a cluster fabric that are the
host the net controllers. That was a storage infrastructure. You
know that things have to be done differently in terms

(14:54):
of eye you resilience, UH, implement quality of service and
digs defermines traffic patterns. So it's not just can't. I
won't just pick specific thing. It's just it's at a
range of ideas picked from different in a different accompany,

(15:15):
different industries.

Speaker 6 (15:16):
That's shaping me. I keep shaping me to get better.
That's not what I do.

Speaker 7 (15:21):
And comingly, from the academic points of view, I would
pay for predictive network maintainers and anomal deduction. So it
would be introduces how to do network color metric using
AI and matching then to predict different kind of risk
it up from network outage to security risk. And with

(15:50):
this is I would answer does not manifest. So basically
it's still shaping me. Becoming AI trend is still shaping
me to become even better than the second.

Speaker 3 (16:01):
Absolutely, networking often feels invisible until it breaks.

Speaker 4 (16:07):
What keeps you fascinated with this field? Yeah? What keeps
you fascinated with this field after sixteen years? Yeah?

Speaker 7 (16:14):
I think so that talk is a very interesting field. Yeah,
it's the matter of mathematics, the matter of computer science.
It can a matter of a graph theory, a matter
of control, a matter.

Speaker 6 (16:29):
Of arguing different political design.

Speaker 7 (16:32):
So you're bringing in different ideas of different groups from
different field to make something work. But that that that
in itself gives me fascinatedly feel.

Speaker 6 (16:46):
I mean, I'm a life longerly not like if I
have a family.

Speaker 7 (16:51):
And I still dedicated a lot of that we can
to reading and studying and developing myself.

Speaker 4 (17:00):
H Like.

Speaker 7 (17:01):
For example, there's been a lot of discussions around infinite
band for machine learner moments with the air going on
a course the big traditional industry words chinner word eternals,
which is open source, I wouldn't call it episodes, but

(17:22):
which is industry prove and what we what we all
use at the moment, but we are with the advert
of finished, but we did more provitary to media us not.
There is a new trend coming out which is all
try U try italics so which on paks trade between

(17:43):
world performers and ecosystem, maturity of internet and gives us
good performance inherited from TNE infinite band, so we can
get that because that's fabric field that it finished, that
gives nache which was packaged into Itstert's using ROCKIEV two

(18:11):
or Rocky view one. So things like this advance mat developments,
new trains, keeps me going and gets the fascinated about
the industry.

Speaker 3 (18:20):
Indeed, and you've worked with r d M, R d
M A R O C E V two and congestion control.

Speaker 6 (18:31):
Yeah.

Speaker 4 (18:31):
Terms, most people never hear as you as you just heard.

Speaker 3 (18:37):
Can you explain what a matter for AI big data and.

Speaker 4 (18:42):
Our big data and cloud services.

Speaker 6 (18:49):
It's a Panama training.

Speaker 7 (18:51):
An AI model is like pulling a massive swimming pool
with a buyout.

Speaker 6 (18:57):
You wonder what sort of feel first? If only are
without spail.

Speaker 7 (19:03):
Our d M and Rugby V two are specialized viles
and the bank pass traditional over aligning GPUs and cyber
quick to talk to each other directly with the in latency.
So for example, you have to tw endles that want
stuck to die in a traditional way. So it goes

(19:24):
from the memory to the kernel, to the NIQUE and
the saber and does the same over the network to
be to the claim. But with the odd M which
is related to your frail band and Rocky B two
which is bringing our d M to eat, and we

(19:44):
are able to achieve that direct memory to memory communications
between the client and the cyber So this way the
boxers are going from the corner or the CPU or
the is directly uploaded, and that we shoulduce latency for us.
And in terms of our conjecture control, it ensures that

(20:10):
if thousands of people are exactly have thousands of people
trying to use a tu lean irate, if if all
of us are there, you are going to get congested
at the point and the important traffic like an ambulance
trying to service a patient is also going to be congested,

(20:30):
which can all just lead to something detrimental. So breaking
it into air they're trying to train a model for
the link is congested, it's going to be making a
messed about training parameters and training gata and something that
should take weeks is going to end up taking us

(20:52):
or even get corroted. And you have to start a Worday,
So this two is out deal may work to any
contentual controlment within this ID and very very important for
AI fabric It pictures a brief does fibric clouds has.

Speaker 4 (21:10):
All right? All right, that that makes it easy. Thank you.

Speaker 3 (21:15):
So you've built custom automation frameworks.

Speaker 4 (21:19):
What is your philosophy on automation?

Speaker 3 (21:21):
And I know I asked you, uh, something about automation
in the beginning, but what is your philosophy on automation
and how do you see it redefining networking careers?

Speaker 7 (21:32):
Yeah, I uh, the missionary's kinds that it's very tigre.
And second, like, for example, if you're working with an
Iper skeet up, it's it's it doesn't make sense lugging
into a thousand or two thousand routs per day to

(21:52):
YouTube a comeback, So that basically the CLI in an
scalar day. So if you want to push configuration to
a thousand devices, the best way to do it is
after making your configuration, which actually takes away the human
error in the entire process, and that way you're able

(22:14):
to push be able to do to push conflicted those devices,
do your necessary change.

Speaker 6 (22:22):
Then introduced.

Speaker 7 (22:24):
It gives you a capacity and the ability to actually
do some pre and post checks making sure that whatever
change you're trying to make, your assumptions are validated before
the change, and after they change, your assumptions are going
to be viidated that traffic is moving in the right direction.
So for example, one of the changes I one of

(22:44):
the activities I did of migrating from a three point
two avites fabric to around to a point eight by
five way and.

Speaker 6 (22:54):
That's good.

Speaker 7 (22:55):
That's like hundreds of routers involved or a hundreds of suites involved,
and you expect zero down time like literally zero dancer
because you have customers and the clowd that are going
to be affected. And that's the second of down time.
Is a lot of need for the company. So does

(23:18):
have to be with our pusly be enhance planning for
the change and has monetary for the change. And with
the advance of AI, this even gives us more capability
to answer our monitor and announcer our change, making sure
that every single packet is for polarly validated, every single

(23:39):
part is for value virus data, and we can predict.

Speaker 6 (23:46):
Every oppression during.

Speaker 7 (23:47):
And after the change. So everyone going into AI, everyone
going to networking now or in the future, should lend me.
You should endeavor to get off the speak with some
different the mission framework is using Byton, you're doing using
good Land or using any other level programming and like

(24:09):
worst or simplus fault or using even big already big
network at the mision framework, I can't sable Noah.

Speaker 4 (24:21):
And now.

Speaker 6 (24:24):
Check a puppet.

Speaker 7 (24:27):
Yeah, I would I pay around that actually predicted network
maintain a normally detection with Actually, if anybody is interested, we.

Speaker 6 (24:37):
Check my Google's clouds to take that all.

Speaker 3 (24:40):
Right, all right, and I will also include wings to
your abstracts. So one of your ascrapts talks about AI
as both a weapon and a defense. How should nations
or organizations prepare for this paradox?

Speaker 7 (24:58):
Yes, Well, Traditionally, when we're doing when we're talking about
cyber security, were we assume that the attacker are the
exact TUE have accessed with the exact soup exact security
moneytoring platform. You have the exact firewall that you have

(25:20):
and Trustmittele have done a lot of stress that same
to make sure that either fund the abilities or a
way to a big different dection ygainst. So bringing that
same part of that same idea into a we expect
the different attackers to have the same accessor to the

(25:40):
same or even even better because they could have trained
the because of ethics around uh different air land language
models like tragepty.

Speaker 6 (25:55):
Goupy Germany Germanian uh.

Speaker 7 (25:58):
X GROG, the exics around that that may not allow
them to have access to.

Speaker 6 (26:05):
The default models and be able to craft attacks around that.

Speaker 7 (26:11):
But they may always already have their own a system
that they have trained with either activity or grow I
actually I grow up or and so they have advanced
their own training training data, their own attacks office training
data which uh with their own library using different agents.

(26:36):
So as soon they have access to do we should
also make sure that our blue teams access to the
necessary necessary training data necessary as to make sure that
any difference can be predicted, any act that can be
predicted and proper deference can be made against attacks.

Speaker 6 (26:56):
Coming from the batter us. So there should be a
lot of policies by government.

Speaker 7 (27:05):
I want that I use agents, and there should be
a lot of collaboration between life agencies and the security.

Speaker 6 (27:15):
Scene well in all the industries, all companies and.

Speaker 7 (27:19):
Industries, because national audition need to prepare like based in
Irish City, Astects of Exica, friend.

Speaker 4 (27:26):
Works indeed indeed, So.

Speaker 3 (27:30):
Uh, what's one technical challenge that really tested your skill
set and how did you overcome it?

Speaker 7 (27:41):
Yeah, like we said in the every day the less
a day one. Just like an example, I just gave
about a different artists and the bad as what is
not gonna bad? Also always have different with to attack it,

(28:01):
So how do you make sure that your system is
every single.

Speaker 6 (28:05):
Bad actor coming into trying to attack with.

Speaker 7 (28:08):
So we often need to balance efficiency, finance network with resilience,
make sure that we have enough capacity, make sure we
have enough defense in debt, layers of defense and all that.
So remember once orfiltrating, frustrating a network that requires sero

(28:31):
dance time. When I actually build different they have from firewalls, so.

Speaker 6 (28:39):
The ideas and ips related for different brick.

Speaker 7 (28:45):
So there's a lot of things in play in every
single networking project, every single activities that we need to do.
So every day is a different challenge and that's why
we call it a days a day one.

Speaker 3 (29:03):
Indeed, you run level of it publishing technical blogs like
I said, I found a few in the rhythm. It's
a very intricate information I can I can really tell
that you know exactly what you're talking about, what you're
doing as a professional. Why do you believe it's important

(29:24):
for engineers to share knowledge openly.

Speaker 7 (29:30):
It's something that comes natural oct to me and something
I believe I gained from about a period of games
that work in the industry. For example, you have technologies
like g c P I P b GP. I know
those were designed by some very intelligence people.

Speaker 4 (29:48):
In the future.

Speaker 7 (29:49):
If you've just kept it in an h in a company,
nobody's going to know about it, they're going to be
using it. Well, it's that developed up what you have
developed the moments. So sharing knowledge, sharing technologies, sharing ideas
not only help people to develop and know things or

(30:11):
understand the particular concept. Also it's also of that particle
you that sharing it or that particular product that you're
sharing evolve and gets better. So talking about my blog,
I help the fact that I'm publishing stuff on a
weekly basis. On a daily basis, it helps me to

(30:32):
learn twice. For example, when I'm trying to develop that
particular blog and trying to do the right I have
to read a lot. I actually love things and validate
my assumption. Validates whatever I read, then bring that into
writing to tate to.

Speaker 4 (30:51):
People in the industry.

Speaker 7 (30:53):
Then when people start giving feedback or commenting, either validates Mason.

Speaker 6 (31:00):
But what what's I put out.

Speaker 7 (31:02):
There or challenging my assumptions to go defy and explain its.

Speaker 6 (31:09):
Assumptions that I make.

Speaker 7 (31:11):
I try to clarify whatever thing ast So like my
my parents is then going up, Uh, explain.

Speaker 6 (31:21):
If you can explain something to your.

Speaker 7 (31:22):
Grandma, then then in a way that she's going to
understand that that makes you really understand what you're saying.
So it's been a philosophy that now I grew up
with and I think it's something that everybody should endeavored
to do to develop themselves and to develop the becoming generation,

(31:43):
to keep building espcially and stableness, because in the coming years,
the current network we have is not going to be efficient.

Speaker 6 (31:52):
It's not going to be reported enough, especially when the.

Speaker 7 (31:56):
Coming with the advent of air that we're currently going
to with quantum computing that's coming, which is latly going
to break all the equiption that we have when it's
really fledged. So learning sharing is very in the industry.

Speaker 8 (32:16):
Yes, sir, So as someone from Nigeria who has studied
and worked globally, how do you hope your story inspires
future African or international engineers.

Speaker 6 (32:31):
I don't want to.

Speaker 7 (32:32):
I don't want to limit to So yeah, I studied
and enjoy that moved across the GULB.

Speaker 6 (32:40):
Engineering network.

Speaker 7 (32:42):
Engineran and particularities is a good bossing and everybody you
should be able to show case as kills we gard
less of where you are or your backbone.

Speaker 6 (32:53):
So I'm excited about what I've done. Uh, I want.

Speaker 7 (33:00):
People's lend from a team that from things I've done,
Like basically, like around the papers are reaching around, the
blows are within to inspire them to develop things and
learn more and keep you in the network for the future,
because we're gonna coming is GON. We're going to need

(33:22):
terabites of oh Data Center US that can move ter
abtes a beta and that's not just going to come
from a single it's a single region. We would want
something that comes to glow like a para of their fibrics.
I would be running and making our lives are seeing better.

Speaker 3 (33:46):
Absolutely, So this one I wanted to ask you about
personally because many engineers UH and another interviewed a few
over the past few years.

Speaker 4 (33:57):
But most engineers that I know stay behind the scenes.
But not you. Not you.

Speaker 3 (34:04):
Why do you think visibility and storytelling our part are
important for tech professionals today.

Speaker 7 (34:14):
I really understand what you're saying with that you you
have to be honest and like I used to be
like that, Like we're comfortable and in front of our
PC fixing problems, solving problems, identifying problems, but we are
very bad at telling these stories of how we fix

(34:35):
those problems I've identify for these problems, how I will.

Speaker 6 (34:38):
Come up with those solutions.

Speaker 7 (34:39):
I think a lot of us uh and that responsibility
to even managers of venture capitalists to go to sell
those products, for.

Speaker 6 (34:49):
Products, managers to service prod from us.

Speaker 7 (34:51):
But one thing I've come to realized, nobody is going
to tell your story better than you, better yourself, the matter,
the product developed, the matter day. That's all creates engineers,
and to tell them, tell people out your design decisions
into those products, your design decisions into those networks, our

(35:14):
topologies or ideas to put into design, just actualecting those
network Nobody's going to tell us story the way you
expect the way it should be told. So we've changed
ourselves a lot from the Indian engineering feed by living
that we give it the responsibility to other professionals.

Speaker 6 (35:36):
But I think it's time for us to get out
there tell people what we do. Let them mother. Networking
is not just a field.

Speaker 7 (35:46):
That should that is in the background and just running
and especially in the present day, networking is a can
is very important for everything that's going to be coming
with a red and we should tell people what to
do out the cheap things we do and hour what
we do actually back every day life. For example, if

(36:08):
you go to if we're in an hospital and any
all those complete that others are to. Other machines are
connected through a network, but you are probably going to
see the networking teams in the basements making sure that
things are running effortless.

Speaker 6 (36:29):
Nobody sees them, nobody tells the study, nobody tells talk
about them.

Speaker 7 (36:35):
So it's time we tell we start talking at telling
people out things we do are tunely make things run
effortlessly without issues.

Speaker 4 (36:49):
And they you mentioned that you had a family.

Speaker 3 (36:53):
But also when you step away from research and consoles,
what keeps you grounded and keeps your your interest in
this field and what keeps sparking your creativity?

Speaker 6 (37:07):
What gives start my creativity is first principles.

Speaker 7 (37:14):
I get myself into different rsses, even though that sees
are not correctly using in my day to pay engagement,
it's good to get yourself into ours outings that developed
how the talk process was paid by different technologies you're
working with.

Speaker 6 (37:32):
That way, if problem comes out to mow.

Speaker 7 (37:36):
You can go back to the talk process of the
developers and that's where you you can fix problems and
suggest solutions. I go into a lot of rses and
go into a lot of packet actors. Creativity for me
is performed across pollination of different ideas. For example, I'm

(37:58):
a nest of continer, going to cyber security, going to AI,
machine learning, bring ideas from those different OH fields, pasture
them and see how they are going to make my

(38:19):
network work better. But Gampa, I was discussing with someone,
was it two days ago?

Speaker 6 (38:24):
Two days ago?

Speaker 7 (38:25):
And we're like, how do you build your fabric for
your GPUs? We just make it bigg as big as
enough I would like. So you don't have any from
a quality of service configuration. We are not prioritizing from
a traffic Yeah, we don't have that at the moment.

Speaker 6 (38:44):
And trust me, this is a complaining that will consider
a unicorn and they don't have something like that.

Speaker 7 (38:51):
So I see that they don't have and they do
have personnels trying to improve in themselves by bringing ideas
from different places to make the network better function.

Speaker 6 (39:06):
And on podgets.

Speaker 7 (39:09):
So it's it's quite important for me doppling into things
and that gives me going in the fact that I
need to lend different things from different places gives me
going aspect.

Speaker 3 (39:22):
Absolutely all right, tell us, and where can our listeners
connect with you on the internet read more abstracts or
blogs and papers that you've wrote publications.

Speaker 4 (39:34):
I mean, where can they check those out as well
and just basically connect with you on the internet.

Speaker 6 (39:40):
Yeah, you can check my lendin.

Speaker 7 (39:45):
I'm actually I'm quite active on LinkedIn. You can check
my Goo Goods collar that's put a bit of a
lot of my articles and publications. And you can subscribe
to my blog which is level of I T do
x y z A. You can't see it things that
public from I don't only public networking topics. I also

(40:08):
public topics I probably put up in puduct managing topics.
Our network engineers should see network that put us not.

Speaker 6 (40:18):
Just as possible. So yeah, my nag names I want
to sax gates.

Speaker 4 (40:37):
Absolutely all right.

Speaker 3 (40:40):
Today, guys all over, Toolson gave us a master class
sort of on the future of networking, automation and cybersecurity.

Speaker 4 (40:50):
His journey spans from Nigeria to Ireland.

Speaker 3 (40:53):
His defining work at a ws and net app and
its insights into AI's role in cyber warfare. Tolson, your
ability to merge the technical expertise with global perspective is
definitely inspiring and hopefully that you're aspiring the next generation
to do what you do and understand the processes that

(41:16):
goes into cloud integrations and the new technology and AI.
So listeners be sure to follow Toson's work. Check out
his publications and level up it blog, stay tuned for
his upcoming research, connect with them on LinkedIn, and I
will include those links in the description of this episode
and in the show notes.

Speaker 4 (41:36):
So all you guys have to do is just click
the links and reach out.

Speaker 3 (41:41):
So as always subscribed to Vigilantes Radio, leave us a ratings,
share this episode, and you can support our mission over
at by me at coffee dot com forward slash Vigilantes Radio.
What I do with that is I buy coffee in
books because I like to read and sip coffee while
I read.

Speaker 4 (41:58):
You know, look important in places, but not I just
do that in my leisure.

Speaker 3 (42:03):
Until next time, guys, let's stay connected.

Speaker 4 (42:07):
Thank you so much, Tosan.

Speaker 6 (42:10):
Yeah you're saying much E too.

Speaker 4 (42:12):
Take care, Thank you, but peace to all.

Speaker 3 (42:17):
My name is Deni and I am the host of
Vigilantes Radio Live.

Speaker 4 (42:24):
I think that we are beyond just.

Speaker 3 (42:28):
Asking cool questions and getting cool responses. I think that
we are here as creatives to provide an example that
you can do things different outside of expectations. Because some
of us simply were not born into the club. But

(42:48):
there is perhaps a door window or back gate that
we can leave a clue for you to get into.
Life is short, but there are plenty any of moments
to try and get it right. Pursuing your dreams and
learning from mistakes may be tough, but regret it's tougher

(43:09):
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(43:35):
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Speaker 1 (43:58):
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