Private Data Center as Easy as Cloud With Juniper Apstra
Solving data center problems with Juniper Apstra software.
The internet has evolved dramatically over the last twenty years, making management of data center networks increasingly complex. Watch Mansour Karam, GVP of Data Center Products at Juniper Networks, explain how intent-based networking has helped Juniper customers manage their private data centers as easy as cloud in this presentation recorded live during Tech Field Day 18.
Learn more about Juniper Apstra software.
You’ll learn
How advances in artificial intelligence (AI) and machine learning (ML) have presented new challenges for data center network managers
How Juniper capabilities help customers navigate new opportunities in AI infrastructure and AI Ops
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Transcript
0:09 um you may know me as more most recently
0:12 as the uh founder of Abra uh but given
0:16 that recently I got an an expanded role
0:18 focusing on the data center all of the
0:20 data center products for Juniper what I
0:22 thought is talk more about the data
0:25 center and uh you know the the all of
0:28 the things we're bringing as in Juniper
0:30 to the table when it comes to uh really
0:33 solving problems for our data center uh
0:37 customers and so that's going to be the
0:39 focus today and uh we're going to also
0:41 showcase a bunch of those capabilities
0:44 uh you know throughout the session and
0:46 so but before I jump in uh what I
0:49 thought I'd do is kind of step back and
0:51 talk about the evolution of the data
0:54 center and coincidentally I'm starting
0:56 in September of 2 of 1995 which is when
0:59 actually I came to the US uh to attend
1:02 Stanford and um that was coincidentally
1:05 the same uh month where Netscape
1:08 actually went IPO if you recall uh at
1:11 the time if you were there uh it was a
1:14 crazy time where every company was kind
1:16 of rushing to go online um you know
1:19 websites were U Were you know popping
1:21 back up everywhere and so you know
1:24 networking became like the thing uh
1:27 Cisco which stock was kind of stagnating
1:29 for for for many years prior just
1:32 exploded and this is where Juniper
1:35 actually was also founded during that
1:36 same time to actually deliver on the
1:38 products to support all of this traffic
1:40 explosion that we were seeing and at the
1:43 time you know these data centers started
1:45 spurring everywhere and uh you know most
1:48 applications were quite simple client
1:50 server and so you had these
1:52 architectures which were more like north
1:54 south architecture if you recall the
1:56 access distribution core uh which were
1:59 kind of like the staple of the arch data
2:02 center architecture of the time kind of
2:04 led by Cisco uh fast forward a few years
2:08 uh around 2005 I would say uh we had
2:10 kind of a transition from you know what
2:13 were simpler services to more complex
2:16 Services more interesting offerings um
2:19 the start of the cloud right uh with
2:21 companies of course like Google but then
2:24 uh also Amazon and then actual public
2:27 Cloud which with AWS and uh and Azure uh
2:32 and so for these uh networks and for
2:35 these applications we know the the the
2:38 application itself the architecture of
2:40 the application changed it used to be
2:42 that you know you ask uh the server for
2:45 a request and then you just get a
2:46 response with these applications they
2:49 became more distributed and so for every
2:51 request that you had you know there was
2:52 a lot more chatter between the servers
2:55 and so we kind of moved from what were
2:57 north south application or the infr or
3:00 architectures to like these East West
3:02 architectures and so from the access
3:05 distribution core to like what what was
3:08 is is referred to as Leaf spine or Leaf
3:10 spine super spine that that support a
3:13 lot more East wwest traffic within the
3:16 data center at the time I was a at a
3:18 company that joined company early called
3:20 Arista uh and you know arguably they
3:23 kind of we led the way in kind of this
3:25 transition to this these Leaf spine uh
3:28 architectures and so that was in 2005
3:31 and with every one of those Evolutions
3:33 we see more explosion in traffic and in
3:36 networking traffic um then you know the
3:39 next moment that that is kind of seminal
3:42 is when of course the iPhone was
3:44 released and that's when everyone
3:46 realized that actually we can have apps
3:50 on these phones and then with these apps
3:52 anything that in the past you you had to
3:54 you have to go somewhere to do or to be
3:57 in front of your computer you actually
3:58 could do it right there from your phone
4:01 whether it's uh calling a taxi or uh
4:06 video conferencing with your U uh with
4:08 with your work uh or watching a movie or
4:12 transacting online buying something or
4:15 uh or doing a financial transaction
4:18 everything you you can think of you can
4:20 do now with your phone which means that
4:23 think about it for everything you do
4:25 you're touching a data center somewhere
4:27 you're touching a network somewhere
4:29 where so these networks not only were
4:31 growing massively in size but and they
4:34 were getting more complex but they were
4:36 becoming critical to everything we do
4:39 the networks are the foundation for
4:41 everything we do this is the phenomena
4:43 that is referred to as digital
4:46 transformation uh and uh the thing about
4:50 digital transformation is that it has
4:53 networking at at its core certainly with
4:56 the with the pandemic that everyone went
4:58 through this process has completely
5:00 accelerated and I would say Garner said
5:03 it best when they made this comment
5:04 which is that in order to be to succeed
5:07 a digital transformation you have to uh
5:10 transform your network first if you
5:13 don't then you're three times more
5:15 likely to fail at your digital
5:17 transformation and that kind that was
5:19 kind of the impetus for us actually
5:22 starting a company called abstra uh that
5:25 was back in
5:26 2014 and the goal was really to
5:29 transform the network to transform
5:32 network operations so that you no longer
5:35 have to manually uh operate your network
5:39 we wanted a network that really looks
5:41 and feels and is operated like a cloud
5:44 and so in order to do that we invented
5:46 this thing called intent based
5:48 networking the key there was that at the
5:51 end we wanted Network operators uh we
5:54 want to give them the ability not only
5:56 to move fast at the speed of the
5:58 business but the do it with utmost
6:00 reliability reliability was really the
6:03 key we wanted the network operator to
6:05 trust the software to run the network
6:09 better than they would themselves
6:10 actually in order of magnitude better
6:13 the same way in autopilot r or flies a
6:16 plane much more reliably than the pilot
6:19 themselves and so fast forward to today
6:23 uh we were acquired by Juniper we're
6:25 deployed uh across uh companies in more
6:28 than 7 countries making a difference
6:31 every day uh 83% reduction in Opex uh
6:35 multifold improvements in
6:38 reliability um essentially our customers
6:41 are getting the value of this Simplicity
6:43 the value of this reliability every
6:45 there these are a few of our customers
6:47 we have many many
6:49 more and so you would think okay so is
6:52 that it is there any more inflection
6:54 points and well you know uh over the
6:57 last few years and certainly the moment
6:59 that really captured everyone's
7:00 attention with Chad GP was Chad GPT back
7:03 in 2022 is the Advent of AI ML and yet
7:08 another inflection point yet another
7:11 explosion of traffic you know AI is of
7:14 course it captured the imagination of
7:17 everyone it's relevant to everyone we're
7:19 all using it today but what's critical
7:22 about Ai and what's really interesting
7:23 about AI is the kind of the what what it
7:27 what it take takes for the network and
7:29 for the infrastructure and for the data
7:31 centers to support all of the AI
7:33 applications that you know with all you
7:36 know all organizations want to use AI
7:39 for essentially you know there was this
7:42 blog from Andre which which I thought
7:44 was was really interesting where they
7:46 were kind of looking at where is the the
7:48 value chain for AI who's going to make
7:50 the most you know um you know like where
7:54 is the golden opportunity and uh at the
7:57 end of course AI is going to have a a
7:59 large value chain Lots there's going to
8:01 be lots of opportunity for everyone but
8:03 one thing that is 100% clear is that
8:07 it's going to at the end we're going to
8:08 need infrastructure infrastructure is
8:11 going to be you know the guaranteed
8:14 benefit of AI uh not just the gpus but
8:18 also the network we're going to have to
8:20 need to reinvent the network to support
8:23 these AI applications and if you look at
8:26 it then you know the data center um
8:29 traffic or the the number of data center
8:31 devices whichever way you want to
8:33 measure it essentially is just growing
8:35 and growing through every one of these
8:37 inflection points and you can see here
8:39 how AIML is kind of driving this new
8:42 traffic growth within Data Center and so
8:46 at the end you know the my message is
8:48 data center networking is thriving uh
8:51 it's continues to be relevant it
8:53 continues to be core and critical to
8:56 everything we do and of course with at
8:59 Juniper we're very interested in uh this
9:02 opportunity we' love to make a
9:04 difference in the life of our data
9:07 center customers and so uh then let me
9:10 tell you a bit about Juniper and and you
9:12 know what we do here when it comes to
9:14 the data center uh well first of all
9:18 we're very much relevant in the data
9:20 center market and we focus I would say
9:23 on large Enterprises Cloud customers and
9:28 uh more recently we're very focused on
9:31 the AI ml data center opportunity which
9:34 actually Cuts both across large
9:36 Enterprise and Cloud both Enterprises
9:39 and Cloud are building these AIML data
9:42 centers and so what products do we do we
9:46 do we uh do we deliver for those uh
9:48 customers you know at the from at the
9:50 basic level we have switches which are
9:53 kind of like the building blocks for
9:55 data center uh networks but then also we
9:57 have the operation software which at its
10:00 foundation leverages and utilizes abstra
10:04 both unram and U more and more in the
10:07 cloud but then you know net Juniper is
10:10 not just a data center company Juniper
10:13 while we're 100% focused on networking
10:15 that's all we do we have an entire
10:17 portfolio we actually have an endtoend
10:19 portfolio all the way from campus to
10:21 when and to security and so that's kind
10:24 of one of the benefits is that we can
10:26 leverage this extended portfolio when we
10:29 deliver data center solutions to our
10:30 customers adding on the the gateways the
10:34 security uh many virtual devices device
10:37 options and we'll get back to that but
10:39 essentially you know again with juniper
10:41 you know while we as in our business
10:43 units focused on data center Juniper has
10:45 the portfolio for in networking
10:48 Solutions end to end so you know going
10:51 talking about these devices we have a
10:53 whole portfolio uh you know we have
10:55 shallow buff shallow shallow buffer
10:58 device devices that are that are
11:01 relevant in for many applications
11:03 including IML applications for the
11:06 high-end we also have de buffer
11:08 applications we have Merchant silicon we
11:10 also have our own investment in our own
11:13 silicon and what one thing we're doing
11:15 is that we're boosting our switching for
11:18 portfolio for a IML we we actually
11:20 launched uh recently the tomahawk four
11:23 switches and this is kind of the start
11:25 of a many more products that we're going
11:28 to be delivering focusing on AI uh ML
11:32 and so that's kind of the basics now how
11:35 do we differentiate what is it that we
11:38 do differently than our competitors and
11:41 you know when I think of differentiators
11:42 the way I like I like to think about it
11:44 is what problems we're solving for our
11:47 customers uniquely and what I'd say is
11:50 that there are three pillars for our
11:52 differentiation one is operations and
11:54 this is something we're going to be
11:55 talking about a lot today second is
11:58 openness and third is endtoend Solutions
12:01 so let me talk about these starting with
12:05 operations so with operations as I said
12:09 abstra was the foundation and what we
12:10 did with abstra is this intent based
12:13 deterministic control essentially it's
12:15 software that runs your data center
12:18 Network day in and day out with the
12:21 speed to meet the business requirement
12:23 and with utmost reliability essentially
12:26 you want to trust your software to run
12:28 your network work that is kind of the
12:30 foundation for uh for uh our data center
12:35 operation strategy now in addition to
12:39 intent based and so that's that's intent
12:41 based so now in addition to intent based
12:42 what we're doing is that we're adding
12:45 other pillars to really kind of deliver
12:48 more value than anyone to really help
12:52 our Network operators operate their data
12:55 center with the Simplicity of the cloud
12:58 in fact with the utmost confidence and
13:01 so in addition to AI we're adding in in
13:05 addition to intent base we're adding in
13:07 Ai and so the way to think of it is that
13:11 intent base really gives you this
13:12 deterministic control you know there is
13:14 no room for probability when it comes to
13:18 running your data center the same way an
13:20 autopilot runs a plane when you tell it
13:22 to go to 10,000 ft you want it to go to
13:24 10,000 ft deterministically that's
13:27 essentially What in in based means but
13:30 while we're running the network with
13:33 this intent based approach we're
13:34 collecting tons of telemetry and this
13:37 Telemetry can be used and so what we do
13:39 is that we ship it to third-party
13:41 platforms but one of the platforms is
13:43 one that Juniper has which is Marvis we
13:46 have our own aiops layer which
13:49 essentially is a conversational
13:50 interface but also a data link and there
13:53 we can by sending all of the tra traffic
13:56 there and having the whole historical
13:58 perspective by applying AI you can now
14:00 deliver probabilistic insights and so
14:04 with intent based you get um tenfold
14:07 Improvement in reliability you get a uh
14:11 90% reduction in Opera operating
14:13 expenses but then when you also add AI
14:16 then what we have proven is that we can
14:19 also reduce the time to troubleshoot
14:22 problems reduce the number of tickets by
14:25 up to 90 to
14:26 95% and so by marrying this intent based
14:30 approach which is deterministic with the
14:32 probabilistic AIML approach essentially
14:36 where differentiating from everyone else
14:38 and adding that much more value to our
14:40 customers one one thing manour uh and
14:43 thank you it's great so far I love it uh
14:45 I would love to see as we get into
14:47 looking at it when we talk about
14:49 managing you know deterministic
14:51 probabilistic but also human driven the
14:54 important part here is like AI can tell
14:56 us what traffic is doing it can the app
14:59 awareness that all this stuff is great
15:01 but there's like business proprietary
15:03 you know sort of tribal knowledge that
15:05 sometimes we have I would love to see in
15:07 product kind of like how we can
15:09 influence determinism uh and sort of
15:12 like Drive the the basian inference with
15:15 a little bit of human
15:17 good you're you're right ahead of me all
15:20 right make sure this is awesome because
15:22 it's exactly what I was what I was going
15:23 to add right here and actually we're
15:25 going to show some of it today you know
15:27 the the third pillar and so like to
15:29 answer your question the third pillar
15:30 and you you talked about it the app
15:32 awareness we want to bring in the app
15:33 awareness at the end for
15:36 infrastructure uh the the the key asset
15:39 is the app right we what network
15:42 operators want to know is how is the
15:45 network performing for the app and we
15:47 want to be as Discerning as possible and
15:50 to your point some of these requirements
15:53 are very bespoke to the specific
15:56 customer and so what we need to do is
15:58 also have flexibility in how we kind of
16:02 put together these tests that leverage
16:04 all of this data so that we distill an
16:07 answer that a specific customer cares
16:10 about and so we're going to show some of
16:12 it today in terms of like the
16:13 flexibility of how you can build tests
16:16 but at the core of it is you need to
16:18 have the flow information and that's
16:19 something we just added today we added
16:22 recently we we launched it recently the
16:24 abstra flow data that's the most
16:27 contextual um uh most comprehensive flow
16:32 Telemetry uh of any data center
16:35 operations software on the market and
16:38 the reason again is because we want to
16:40 combine intent-based
16:41 Ai and application awareness together
16:44 and then have the ability to run tests
16:47 to be the most Discerning in terms of
16:49 whether or not the network is working
16:52 well for this specific app for this
16:54 specific use case okay and again we're
16:57 going to be showing uh more on on this
16:59 particular point today so that is
17:02 operations and this is very consistent
17:04 with Juniper's overarching strategy
17:06 experience first leading with operations
17:08 which is why they acquired abstra this
17:10 is why they acquired uh mist and that's
17:13 an area of core competency where we're
17:15 going to continue to invest the second
17:18 uh pillar of the Juniper data center
17:21 differentiation is openness
17:24 essentially the promise of networking
17:27 was that it is open
17:29 you the networking is so critical this
17:31 is why we have standards we don't want
17:32 to be locked into one specific vendor
17:35 this is why we've created things like
17:37 bgp and EPN VXL and so we at at Juniper
17:43 that's always been part of the DNA
17:45 because uniper kind of was founded as a
17:47 challenger to to the incumbent and
17:50 continues to be a challenger and at
17:52 abstra that was a core pillar we wanted
17:55 to deliver a solution that is
17:57 multivendor and so so although we were
17:59 acquired by Juniper we're continuing
18:02 down that path we support not only
18:04 Juniper but also uh switches from many
18:07 of uh of the other switch suppliers are
18:11 there in the market all of the
18:12 incumbents and the leading ones and so
18:16 uh if you deploy uh Juniper operations
18:19 then you can bring in uh not only
18:22 Juniper devices but Juniper devices from
18:25 the rest from from the rest of the the
18:28 the suppliers and so and when we say
18:30 that it's multivendor we don't just mean
18:33 that we support it but we also make sure
18:35 it works well so at the end we're kind
18:39 of giving you that same level of
18:40 reliability independently of your vendor
18:43 choice so that's one aspect of openness
18:46 which is unique to Juniper none of our
18:50 competitors has the other aspect to
18:52 openness is that you know at the end
18:54 we're part of an ecosystem you know this
18:57 this solution is is part of an ecosystem
18:59 and needs to work well in the context of
19:01 this ecosystem so we have open apis both
19:04 with our software with absr also with
19:06 all of the devices uh in that uh uh that
19:10 we deliver and we have Integrations with
19:14 platforms and solutions whether it's um
19:17 overlay Solutions or net devop Solutions
19:21 security Etc solutions that are
19:24 available on the market and one of the
19:27 tools that has become very popular to
19:29 manage Data Center and Cloud
19:32 environments is terraform and one of the
19:33 things we're going to Showcase today is
19:35 an integration with terraform as kind of
19:38 a unified tool to manage your data
19:40 center Network through Abra but also
19:43 your Club your your uh your public Cloud
19:46 so that's openness and the third is
19:48 endtoend Solutions and this is how kind
19:50 of it all comes together um we're kind
19:53 of taking as I mentioned Juniper is a
19:56 company that has not only focuses on
19:59 networking but has the entire portfolio
20:01 and so we want to really bring this to
20:03 bear so instead of selling products to
20:05 our customers what we want is to deliver
20:07 outcomes to deliver Solutions and so
20:10 whether you know customers think about
20:12 what use cases they have are they trying
20:13 to build an AI training cluster or a
20:16 VMware data center are they building an
20:19 eastwest three-stage Class A five-stage
20:21 class network is it an edge data center
20:25 whatever their uh their their use case
20:28 ISS what we want to do is deliver a
20:30 solution and when we what we mean with a
20:32 solution is uh a reference design that
20:35 includes the devices themselves the
20:37 topology how they're interconnected what
20:40 protocols they use what software manages
20:42 them of course primarily at its core
20:45 abstra but not only that we also are
20:47 bringing in the routers the gateways the
20:50 firewalls as part of the design um you
20:53 can use juniper uh devices but also you
20:55 can bring in devices from the
20:56 competition and then what we want to do
20:58 is give it to you in a way that is
21:01 tested end to end so you know it's going
21:04 to work and so we're kind of going to be
21:06 leading with this validated designs
21:09 because you know while some customers
21:11 are interested in kind of tailoring
21:13 their Solutions having some bespoke
21:14 designs most customers want solutions
21:18 that just work end to endend and that is
21:21 what at Juniper we want to deliver for
21:23 them and in fact one of the things we're
21:24 going to show today is how we can EAS
21:28 easily deploy build and operate an AI
21:32 cluster using Abra essentially
21:35 delivering on this validated designed
21:37 for an AI cluster and
21:41 so what did you mean for taish
21:44 troubleshooting or brother what is the
21:46 context of troubleshooting which is uh
21:50 when the AI and ml considering a trouble
21:54 when I'm shooting the trouble so uh if
21:57 is something Proactive or deterministic
22:00 as as it told and uh what if I already
22:06 know that the the the network will be uh
22:08 busy because I have a streaming so I
22:12 know that it's busy but the the
22:15 troubleshooting
22:17 um made up of abstract could consider
22:20 this an anomaly but uh I've been um um
22:25 so when we say when typically with
22:27 troubleshooting troubleshooting an issue
22:29 with an application like generally your
22:31 application is not working well right
22:33 and okay you know usually when it's when
22:36 it when it's when you're part of the
22:38 networking team you're trying to figure
22:40 out whether or not you know something
22:42 that's under your control is at fault
22:44 right whether the network is at fault
22:47 and you know if with with with abstra if
22:50 you have all of the knowledge of all of
22:52 the pieces then you can
22:53 deterministically say Hey you know there
22:54 is a problem here or there but uh in in
22:58 many cases you don't have all of that
23:00 knowledge especially when you're you're
23:02 uh you're looking at a multi- domain
23:05 infrastructure when you're kind of
23:07 looking at a problem and you're not sure
23:08 whether it's really in the data center
23:10 or whether it's somewhere on the on the
23:12 W side uh or in fact you're not even
23:16 sure whether it's on the you know it's
23:18 it's within the network infrastructure
23:20 itself and so when you have the
23:22 knowledge you can use a deterministic
23:24 approach but if you don't have all of
23:26 the knowledge then by looking at your
23:28 historical data and applying AI models
23:32 to your uh your uh your your data leg
23:35 all of the Telemetry that you have
23:37 throughout the history then you know
23:40 these AI models have the ability to kind
23:42 of point you in the right direction
23:44 right essentially you look the at all of
23:47 the knowledge that you have all of over
23:49 the over over time and you have an
23:52 ability to go and say okay well
23:53 probabilistically I believe that you you
23:55 know it's the problem is likely to be
23:58 around there right and so it kind of is
24:00 help helps you guide you it's not
24:02 guaranteed it's not deterministic but it
24:05 guides you right okay that's clear thank
24:07 you yeah so it's driven by uh Ai and ml
24:12 so that if it will prepare dynamically
24:16 some kind of templates to say this is
24:18 wrong or this is acting correctly and
24:21 and so on is it right yes correct okay
24:24 thank you thank
24:26 you
0:09 um you may know me as more most recently
0:12 as the uh founder of Abra uh but given
0:16 that recently I got an an expanded role
0:18 focusing on the data center all of the
0:20 data center products for Juniper what I
0:22 thought is talk more about the data
0:25 center and uh you know the the all of
0:28 the things we're bringing as in Juniper
0:30 to the table when it comes to uh really
0:33 solving problems for our data center uh
0:37 customers and so that's going to be the
0:39 focus today and uh we're going to also
0:41 showcase a bunch of those capabilities
0:44 uh you know throughout the session and
0:46 so but before I jump in uh what I
0:49 thought I'd do is kind of step back and
0:51 talk about the evolution of the data
0:54 center and coincidentally I'm starting
0:56 in September of 2 of 1995 which is when
0:59 actually I came to the US uh to attend
1:02 Stanford and um that was coincidentally
1:05 the same uh month where Netscape
1:08 actually went IPO if you recall uh at
1:11 the time if you were there uh it was a
1:14 crazy time where every company was kind
1:16 of rushing to go online um you know
1:19 websites were U Were you know popping
1:21 back up everywhere and so you know
1:24 networking became like the thing uh
1:27 Cisco which stock was kind of stagnating
1:29 for for for many years prior just
1:32 exploded and this is where Juniper
1:35 actually was also founded during that
1:36 same time to actually deliver on the
1:38 products to support all of this traffic
1:40 explosion that we were seeing and at the
1:43 time you know these data centers started
1:45 spurring everywhere and uh you know most
1:48 applications were quite simple client
1:50 server and so you had these
1:52 architectures which were more like north
1:54 south architecture if you recall the
1:56 access distribution core uh which were
1:59 kind of like the staple of the arch data
2:02 center architecture of the time kind of
2:04 led by Cisco uh fast forward a few years
2:08 uh around 2005 I would say uh we had
2:10 kind of a transition from you know what
2:13 were simpler services to more complex
2:16 Services more interesting offerings um
2:19 the start of the cloud right uh with
2:21 companies of course like Google but then
2:24 uh also Amazon and then actual public
2:27 Cloud which with AWS and uh and Azure uh
2:32 and so for these uh networks and for
2:35 these applications we know the the the
2:38 application itself the architecture of
2:40 the application changed it used to be
2:42 that you know you ask uh the server for
2:45 a request and then you just get a
2:46 response with these applications they
2:49 became more distributed and so for every
2:51 request that you had you know there was
2:52 a lot more chatter between the servers
2:55 and so we kind of moved from what were
2:57 north south application or the infr or
3:00 architectures to like these East West
3:02 architectures and so from the access
3:05 distribution core to like what what was
3:08 is is referred to as Leaf spine or Leaf
3:10 spine super spine that that support a
3:13 lot more East wwest traffic within the
3:16 data center at the time I was a at a
3:18 company that joined company early called
3:20 Arista uh and you know arguably they
3:23 kind of we led the way in kind of this
3:25 transition to this these Leaf spine uh
3:28 architectures and so that was in 2005
3:31 and with every one of those Evolutions
3:33 we see more explosion in traffic and in
3:36 networking traffic um then you know the
3:39 next moment that that is kind of seminal
3:42 is when of course the iPhone was
3:44 released and that's when everyone
3:46 realized that actually we can have apps
3:50 on these phones and then with these apps
3:52 anything that in the past you you had to
3:54 you have to go somewhere to do or to be
3:57 in front of your computer you actually
3:58 could do it right there from your phone
4:01 whether it's uh calling a taxi or uh
4:06 video conferencing with your U uh with
4:08 with your work uh or watching a movie or
4:12 transacting online buying something or
4:15 uh or doing a financial transaction
4:18 everything you you can think of you can
4:20 do now with your phone which means that
4:23 think about it for everything you do
4:25 you're touching a data center somewhere
4:27 you're touching a network somewhere
4:29 where so these networks not only were
4:31 growing massively in size but and they
4:34 were getting more complex but they were
4:36 becoming critical to everything we do
4:39 the networks are the foundation for
4:41 everything we do this is the phenomena
4:43 that is referred to as digital
4:46 transformation uh and uh the thing about
4:50 digital transformation is that it has
4:53 networking at at its core certainly with
4:56 the with the pandemic that everyone went
4:58 through this process has completely
5:00 accelerated and I would say Garner said
5:03 it best when they made this comment
5:04 which is that in order to be to succeed
5:07 a digital transformation you have to uh
5:10 transform your network first if you
5:13 don't then you're three times more
5:15 likely to fail at your digital
5:17 transformation and that kind that was
5:19 kind of the impetus for us actually
5:22 starting a company called abstra uh that
5:25 was back in
5:26 2014 and the goal was really to
5:29 transform the network to transform
5:32 network operations so that you no longer
5:35 have to manually uh operate your network
5:39 we wanted a network that really looks
5:41 and feels and is operated like a cloud
5:44 and so in order to do that we invented
5:46 this thing called intent based
5:48 networking the key there was that at the
5:51 end we wanted Network operators uh we
5:54 want to give them the ability not only
5:56 to move fast at the speed of the
5:58 business but the do it with utmost
6:00 reliability reliability was really the
6:03 key we wanted the network operator to
6:05 trust the software to run the network
6:09 better than they would themselves
6:10 actually in order of magnitude better
6:13 the same way in autopilot r or flies a
6:16 plane much more reliably than the pilot
6:19 themselves and so fast forward to today
6:23 uh we were acquired by Juniper we're
6:25 deployed uh across uh companies in more
6:28 than 7 countries making a difference
6:31 every day uh 83% reduction in Opex uh
6:35 multifold improvements in
6:38 reliability um essentially our customers
6:41 are getting the value of this Simplicity
6:43 the value of this reliability every
6:45 there these are a few of our customers
6:47 we have many many
6:49 more and so you would think okay so is
6:52 that it is there any more inflection
6:54 points and well you know uh over the
6:57 last few years and certainly the moment
6:59 that really captured everyone's
7:00 attention with Chad GP was Chad GPT back
7:03 in 2022 is the Advent of AI ML and yet
7:08 another inflection point yet another
7:11 explosion of traffic you know AI is of
7:14 course it captured the imagination of
7:17 everyone it's relevant to everyone we're
7:19 all using it today but what's critical
7:22 about Ai and what's really interesting
7:23 about AI is the kind of the what what it
7:27 what it take takes for the network and
7:29 for the infrastructure and for the data
7:31 centers to support all of the AI
7:33 applications that you know with all you
7:36 know all organizations want to use AI
7:39 for essentially you know there was this
7:42 blog from Andre which which I thought
7:44 was was really interesting where they
7:46 were kind of looking at where is the the
7:48 value chain for AI who's going to make
7:50 the most you know um you know like where
7:54 is the golden opportunity and uh at the
7:57 end of course AI is going to have a a
7:59 large value chain Lots there's going to
8:01 be lots of opportunity for everyone but
8:03 one thing that is 100% clear is that
8:07 it's going to at the end we're going to
8:08 need infrastructure infrastructure is
8:11 going to be you know the guaranteed
8:14 benefit of AI uh not just the gpus but
8:18 also the network we're going to have to
8:20 need to reinvent the network to support
8:23 these AI applications and if you look at
8:26 it then you know the data center um
8:29 traffic or the the number of data center
8:31 devices whichever way you want to
8:33 measure it essentially is just growing
8:35 and growing through every one of these
8:37 inflection points and you can see here
8:39 how AIML is kind of driving this new
8:42 traffic growth within Data Center and so
8:46 at the end you know the my message is
8:48 data center networking is thriving uh
8:51 it's continues to be relevant it
8:53 continues to be core and critical to
8:56 everything we do and of course with at
8:59 Juniper we're very interested in uh this
9:02 opportunity we' love to make a
9:04 difference in the life of our data
9:07 center customers and so uh then let me
9:10 tell you a bit about Juniper and and you
9:12 know what we do here when it comes to
9:14 the data center uh well first of all
9:18 we're very much relevant in the data
9:20 center market and we focus I would say
9:23 on large Enterprises Cloud customers and
9:28 uh more recently we're very focused on
9:31 the AI ml data center opportunity which
9:34 actually Cuts both across large
9:36 Enterprise and Cloud both Enterprises
9:39 and Cloud are building these AIML data
9:42 centers and so what products do we do we
9:46 do we uh do we deliver for those uh
9:48 customers you know at the from at the
9:50 basic level we have switches which are
9:53 kind of like the building blocks for
9:55 data center uh networks but then also we
9:57 have the operation software which at its
10:00 foundation leverages and utilizes abstra
10:04 both unram and U more and more in the
10:07 cloud but then you know net Juniper is
10:10 not just a data center company Juniper
10:13 while we're 100% focused on networking
10:15 that's all we do we have an entire
10:17 portfolio we actually have an endtoend
10:19 portfolio all the way from campus to
10:21 when and to security and so that's kind
10:24 of one of the benefits is that we can
10:26 leverage this extended portfolio when we
10:29 deliver data center solutions to our
10:30 customers adding on the the gateways the
10:34 security uh many virtual devices device
10:37 options and we'll get back to that but
10:39 essentially you know again with juniper
10:41 you know while we as in our business
10:43 units focused on data center Juniper has
10:45 the portfolio for in networking
10:48 Solutions end to end so you know going
10:51 talking about these devices we have a
10:53 whole portfolio uh you know we have
10:55 shallow buff shallow shallow buffer
10:58 device devices that are that are
11:01 relevant in for many applications
11:03 including IML applications for the
11:06 high-end we also have de buffer
11:08 applications we have Merchant silicon we
11:10 also have our own investment in our own
11:13 silicon and what one thing we're doing
11:15 is that we're boosting our switching for
11:18 portfolio for a IML we we actually
11:20 launched uh recently the tomahawk four
11:23 switches and this is kind of the start
11:25 of a many more products that we're going
11:28 to be delivering focusing on AI uh ML
11:32 and so that's kind of the basics now how
11:35 do we differentiate what is it that we
11:38 do differently than our competitors and
11:41 you know when I think of differentiators
11:42 the way I like I like to think about it
11:44 is what problems we're solving for our
11:47 customers uniquely and what I'd say is
11:50 that there are three pillars for our
11:52 differentiation one is operations and
11:54 this is something we're going to be
11:55 talking about a lot today second is
11:58 openness and third is endtoend Solutions
12:01 so let me talk about these starting with
12:05 operations so with operations as I said
12:09 abstra was the foundation and what we
12:10 did with abstra is this intent based
12:13 deterministic control essentially it's
12:15 software that runs your data center
12:18 Network day in and day out with the
12:21 speed to meet the business requirement
12:23 and with utmost reliability essentially
12:26 you want to trust your software to run
12:28 your network work that is kind of the
12:30 foundation for uh for uh our data center
12:35 operation strategy now in addition to
12:39 intent based and so that's that's intent
12:41 based so now in addition to intent based
12:42 what we're doing is that we're adding
12:45 other pillars to really kind of deliver
12:48 more value than anyone to really help
12:52 our Network operators operate their data
12:55 center with the Simplicity of the cloud
12:58 in fact with the utmost confidence and
13:01 so in addition to AI we're adding in in
13:05 addition to intent base we're adding in
13:07 Ai and so the way to think of it is that
13:11 intent base really gives you this
13:12 deterministic control you know there is
13:14 no room for probability when it comes to
13:18 running your data center the same way an
13:20 autopilot runs a plane when you tell it
13:22 to go to 10,000 ft you want it to go to
13:24 10,000 ft deterministically that's
13:27 essentially What in in based means but
13:30 while we're running the network with
13:33 this intent based approach we're
13:34 collecting tons of telemetry and this
13:37 Telemetry can be used and so what we do
13:39 is that we ship it to third-party
13:41 platforms but one of the platforms is
13:43 one that Juniper has which is Marvis we
13:46 have our own aiops layer which
13:49 essentially is a conversational
13:50 interface but also a data link and there
13:53 we can by sending all of the tra traffic
13:56 there and having the whole historical
13:58 perspective by applying AI you can now
14:00 deliver probabilistic insights and so
14:04 with intent based you get um tenfold
14:07 Improvement in reliability you get a uh
14:11 90% reduction in Opera operating
14:13 expenses but then when you also add AI
14:16 then what we have proven is that we can
14:19 also reduce the time to troubleshoot
14:22 problems reduce the number of tickets by
14:25 up to 90 to
14:26 95% and so by marrying this intent based
14:30 approach which is deterministic with the
14:32 probabilistic AIML approach essentially
14:36 where differentiating from everyone else
14:38 and adding that much more value to our
14:40 customers one one thing manour uh and
14:43 thank you it's great so far I love it uh
14:45 I would love to see as we get into
14:47 looking at it when we talk about
14:49 managing you know deterministic
14:51 probabilistic but also human driven the
14:54 important part here is like AI can tell
14:56 us what traffic is doing it can the app
14:59 awareness that all this stuff is great
15:01 but there's like business proprietary
15:03 you know sort of tribal knowledge that
15:05 sometimes we have I would love to see in
15:07 product kind of like how we can
15:09 influence determinism uh and sort of
15:12 like Drive the the basian inference with
15:15 a little bit of human
15:17 good you're you're right ahead of me all
15:20 right make sure this is awesome because
15:22 it's exactly what I was what I was going
15:23 to add right here and actually we're
15:25 going to show some of it today you know
15:27 the the third pillar and so like to
15:29 answer your question the third pillar
15:30 and you you talked about it the app
15:32 awareness we want to bring in the app
15:33 awareness at the end for
15:36 infrastructure uh the the the key asset
15:39 is the app right we what network
15:42 operators want to know is how is the
15:45 network performing for the app and we
15:47 want to be as Discerning as possible and
15:50 to your point some of these requirements
15:53 are very bespoke to the specific
15:56 customer and so what we need to do is
15:58 also have flexibility in how we kind of
16:02 put together these tests that leverage
16:04 all of this data so that we distill an
16:07 answer that a specific customer cares
16:10 about and so we're going to show some of
16:12 it today in terms of like the
16:13 flexibility of how you can build tests
16:16 but at the core of it is you need to
16:18 have the flow information and that's
16:19 something we just added today we added
16:22 recently we we launched it recently the
16:24 abstra flow data that's the most
16:27 contextual um uh most comprehensive flow
16:32 Telemetry uh of any data center
16:35 operations software on the market and
16:38 the reason again is because we want to
16:40 combine intent-based
16:41 Ai and application awareness together
16:44 and then have the ability to run tests
16:47 to be the most Discerning in terms of
16:49 whether or not the network is working
16:52 well for this specific app for this
16:54 specific use case okay and again we're
16:57 going to be showing uh more on on this
16:59 particular point today so that is
17:02 operations and this is very consistent
17:04 with Juniper's overarching strategy
17:06 experience first leading with operations
17:08 which is why they acquired abstra this
17:10 is why they acquired uh mist and that's
17:13 an area of core competency where we're
17:15 going to continue to invest the second
17:18 uh pillar of the Juniper data center
17:21 differentiation is openness
17:24 essentially the promise of networking
17:27 was that it is open
17:29 you the networking is so critical this
17:31 is why we have standards we don't want
17:32 to be locked into one specific vendor
17:35 this is why we've created things like
17:37 bgp and EPN VXL and so we at at Juniper
17:43 that's always been part of the DNA
17:45 because uniper kind of was founded as a
17:47 challenger to to the incumbent and
17:50 continues to be a challenger and at
17:52 abstra that was a core pillar we wanted
17:55 to deliver a solution that is
17:57 multivendor and so so although we were
17:59 acquired by Juniper we're continuing
18:02 down that path we support not only
18:04 Juniper but also uh switches from many
18:07 of uh of the other switch suppliers are
18:11 there in the market all of the
18:12 incumbents and the leading ones and so
18:16 uh if you deploy uh Juniper operations
18:19 then you can bring in uh not only
18:22 Juniper devices but Juniper devices from
18:25 the rest from from the rest of the the
18:28 the suppliers and so and when we say
18:30 that it's multivendor we don't just mean
18:33 that we support it but we also make sure
18:35 it works well so at the end we're kind
18:39 of giving you that same level of
18:40 reliability independently of your vendor
18:43 choice so that's one aspect of openness
18:46 which is unique to Juniper none of our
18:50 competitors has the other aspect to
18:52 openness is that you know at the end
18:54 we're part of an ecosystem you know this
18:57 this solution is is part of an ecosystem
18:59 and needs to work well in the context of
19:01 this ecosystem so we have open apis both
19:04 with our software with absr also with
19:06 all of the devices uh in that uh uh that
19:10 we deliver and we have Integrations with
19:14 platforms and solutions whether it's um
19:17 overlay Solutions or net devop Solutions
19:21 security Etc solutions that are
19:24 available on the market and one of the
19:27 tools that has become very popular to
19:29 manage Data Center and Cloud
19:32 environments is terraform and one of the
19:33 things we're going to Showcase today is
19:35 an integration with terraform as kind of
19:38 a unified tool to manage your data
19:40 center Network through Abra but also
19:43 your Club your your uh your public Cloud
19:46 so that's openness and the third is
19:48 endtoend Solutions and this is how kind
19:50 of it all comes together um we're kind
19:53 of taking as I mentioned Juniper is a
19:56 company that has not only focuses on
19:59 networking but has the entire portfolio
20:01 and so we want to really bring this to
20:03 bear so instead of selling products to
20:05 our customers what we want is to deliver
20:07 outcomes to deliver Solutions and so
20:10 whether you know customers think about
20:12 what use cases they have are they trying
20:13 to build an AI training cluster or a
20:16 VMware data center are they building an
20:19 eastwest three-stage Class A five-stage
20:21 class network is it an edge data center
20:25 whatever their uh their their use case
20:28 ISS what we want to do is deliver a
20:30 solution and when we what we mean with a
20:32 solution is uh a reference design that
20:35 includes the devices themselves the
20:37 topology how they're interconnected what
20:40 protocols they use what software manages
20:42 them of course primarily at its core
20:45 abstra but not only that we also are
20:47 bringing in the routers the gateways the
20:50 firewalls as part of the design um you
20:53 can use juniper uh devices but also you
20:55 can bring in devices from the
20:56 competition and then what we want to do
20:58 is give it to you in a way that is
21:01 tested end to end so you know it's going
21:04 to work and so we're kind of going to be
21:06 leading with this validated designs
21:09 because you know while some customers
21:11 are interested in kind of tailoring
21:13 their Solutions having some bespoke
21:14 designs most customers want solutions
21:18 that just work end to endend and that is
21:21 what at Juniper we want to deliver for
21:23 them and in fact one of the things we're
21:24 going to show today is how we can EAS
21:28 easily deploy build and operate an AI
21:32 cluster using Abra essentially
21:35 delivering on this validated designed
21:37 for an AI cluster and
21:41 so what did you mean for taish
21:44 troubleshooting or brother what is the
21:46 context of troubleshooting which is uh
21:50 when the AI and ml considering a trouble
21:54 when I'm shooting the trouble so uh if
21:57 is something Proactive or deterministic
22:00 as as it told and uh what if I already
22:06 know that the the the network will be uh
22:08 busy because I have a streaming so I
22:12 know that it's busy but the the
22:15 troubleshooting
22:17 um made up of abstract could consider
22:20 this an anomaly but uh I've been um um
22:25 so when we say when typically with
22:27 troubleshooting troubleshooting an issue
22:29 with an application like generally your
22:31 application is not working well right
22:33 and okay you know usually when it's when
22:36 it when it's when you're part of the
22:38 networking team you're trying to figure
22:40 out whether or not you know something
22:42 that's under your control is at fault
22:44 right whether the network is at fault
22:47 and you know if with with with abstra if
22:50 you have all of the knowledge of all of
22:52 the pieces then you can
22:53 deterministically say Hey you know there
22:54 is a problem here or there but uh in in
22:58 many cases you don't have all of that
23:00 knowledge especially when you're you're
23:02 uh you're looking at a multi- domain
23:05 infrastructure when you're kind of
23:07 looking at a problem and you're not sure
23:08 whether it's really in the data center
23:10 or whether it's somewhere on the on the
23:12 W side uh or in fact you're not even
23:16 sure whether it's on the you know it's
23:18 it's within the network infrastructure
23:20 itself and so when you have the
23:22 knowledge you can use a deterministic
23:24 approach but if you don't have all of
23:26 the knowledge then by looking at your
23:28 historical data and applying AI models
23:32 to your uh your uh your your data leg
23:35 all of the Telemetry that you have
23:37 throughout the history then you know
23:40 these AI models have the ability to kind
23:42 of point you in the right direction
23:44 right essentially you look the at all of
23:47 the knowledge that you have all of over
23:49 the over over time and you have an
23:52 ability to go and say okay well
23:53 probabilistically I believe that you you
23:55 know it's the problem is likely to be
23:58 around there right and so it kind of is
24:00 help helps you guide you it's not
24:02 guaranteed it's not deterministic but it
24:05 guides you right okay that's clear thank
24:07 you yeah so it's driven by uh Ai and ml
24:12 so that if it will prepare dynamically
24:16 some kind of templates to say this is
24:18 wrong or this is acting correctly and
24:21 and so on is it right yes correct okay
24:24 thank you thank
24:26 you