ZKast with Bob Friday
AI is driving a major paradigm shift in networking says Mist founder
If you’re fascinated by the future of networking, you’ll want to watch this information-packed interview with Bob Friday, founder of Mist, which is now part of Juniper Networks.
You’ll learn
Why companies must put the end-user experiences first, second, and third
How Mist’s AI-driven Marvis technology now answers 70% of trouble tickets
The reasons for closely pairing the customer support and data science teams
Who is this for?
Host
Guest speakers
Transcript
0:00 [Music]
0:04 uh welcome everybody i'm zeus caraval
0:06 from zk research and i'm here
0:08 for another z cast video podcast as
0:11 always this is done in conjunction with
0:12 my media partner eweek i'm joined today
0:15 as part of a thought leadership series
0:17 with
0:17 bob friday who was one of the founders
0:20 of mist who's now actually part of
0:22 juniper networks who was
0:23 they were acquired a couple of years ago
0:25 now so bob why don't you say hi to
0:27 everybody introduce yourself
0:29 and give us a little background on what
0:30 miss does yeah thank you zeus and uh
0:33 thank you for having me here today you
0:34 know
0:35 my background has been mostly wireless
0:36 most of my career now i sent a thank you
0:38 letter the fcc every year for the
0:40 unlicensed you know
0:41 most my career has been spent building
0:43 mesh networks unlicensed wireless
0:45 controller type of stuff
0:46 you know i did airspace one time which
0:48 was really around wireless controllers
0:50 for the enterprise
0:51 sold that company to cisco and was cisco
0:54 cto for
0:55 six eight years uh and then left cisco
0:58 to go off to start mist
0:59 which is really around cloud and ai and
1:01 you know where i'm here with you today
1:02 to discuss
1:03 yeah and we all we we've kind of joked
1:05 over the years since uh you've been part
1:07 of
1:07 juniper that this was almost a reverse
1:09 acquisition where
1:10 uh well although juniper acquired missed
1:13 missed uh you can see the missed
1:14 influence
1:15 inside juniper now uh you know having
1:18 this ai
1:18 influence across the entire enterprise
1:20 portfolio so that's been kind of fun to
1:22 watch
1:22 i've noticed um the enterprise business
1:26 of juniper it seems like jim was almost
1:28 doubled down on the enterprise i think
1:30 in
1:30 during the last earnings call we just
1:31 had actually a um an analyst call
1:34 with some of the juniper execs and uh
1:36 romney talked about
1:37 enterprise being the growth engine he
1:39 actually predicted that pretty soon it
1:41 would be bigger than service fighter
1:42 which
1:43 i think a few years ago um no one would
1:46 have predicted that
1:47 right for for juniper to have an
1:48 enterprise business that's going that
1:50 fast so
1:50 can you can you expand on that you know
1:54 if you look what romney and the
1:55 executive team general are looking at
1:57 doing you know
1:58 juniper historically has been known as
2:00 kind of a high performance
2:01 routing company for service providers
2:03 you know romney and team are really
2:05 looking to diversify
2:06 juniper and really turn it into more of
2:09 a software company right
2:11 you know so you see a lot of things
2:12 happening at junior as it transforms
2:14 itself
2:15 you know we're extending the businesses
2:17 across sp
2:19 enterprise data center and security so
2:22 organizationally we're getting focused
2:24 around these four different business
2:26 areas and then inside those businesses
2:29 we're really starting to transform
2:30 ourselves from kind of the hardware
2:32 to more of a day zero day one day two
2:35 software company
2:36 you kind of see that because that's
2:38 where our customers are driving us to
2:39 right that's where customers are asking
2:41 for help as these networks come
2:42 become more complex you know they're
2:44 really asking for their vendors to
2:46 actually become
2:47 you know help them with the software
2:49 problem of how they deploy and operate
2:51 software and how we're going to operate
2:52 these networks going forward
2:54 so i think that's where you're seeing
2:55 romney and the team actually being
2:57 driven by
2:58 both the investors and and from the
3:00 customers that are driving us more
3:02 towards this
3:03 diversified company with more of a
3:05 software focus
3:06 yeah now one of the the principles with
3:09 which i conduct my research is
3:11 has always been uh that market you know
3:14 share gains an opportunity to create a
3:16 remarketing transition
3:18 and i think in the enterprise network
3:20 space it seems like
3:21 we're in this big transition where more
3:24 and more networking
3:26 is moving to the cloud right in fact if
3:28 you look
3:29 at the impact clouds had across all of
3:32 ikea
3:33 everything's moved to the cloud except
3:35 networking it's kind of lagged behind
3:37 so can you talk a little bit about
3:39 what's been driving them
3:41 yeah you know if you look at the origin
3:43 story from mist right i mean
3:44 sushi and i were at cisco when we
3:47 acquired meraki right
3:48 you know and that was really the
3:50 beginnings of how cloud was going to be
3:52 able to simplify
3:53 networking uh but what we started to
3:55 really hear from customers when i was
3:57 there
3:58 was really you know we're watching kind
4:00 of these wireless networks go from a
4:02 nice to have
4:03 to a must-have to really they're going
4:05 to business critical and i had a couple
4:07 of very large customers tell me bob
4:09 hey before we put any consumer
4:11 experience on our network
4:13 you know one you had to stop your
4:14 controllers from crashing you know so
4:16 they wanted better software reliability
4:19 two they wanted me to keep up with the
4:21 uh their mobile
4:22 you know digital transformation projects
4:24 you know they were building mobile apps
4:26 every month
4:27 you know the network was still being
4:28 updated every year type of thing
4:30 so they wanted to keep a speed and
4:32 probably third more importantly
4:33 was i call the paradigm shift from we're
4:36 not here to help them manage
4:38 access points or routers which is what i
4:40 did at airspace right you know there the
4:42 paradigm is helping customers manage
4:44 these ap
4:44 switches and routers really the paradigm
4:46 shift is really helping customers manage
4:48 the
4:49 end-to-end user experience what we call
4:51 client-to-cloud
4:53 and it's really they wanted visibility
4:54 you know before they put a robot
4:56 or a mobile app onto their network they
4:59 really want to make sure they have
5:00 complete end in connectivity
5:02 and visibility you know all the way from
5:04 that client device to the internet
5:06 and that was really the big trans market
5:08 transition that you know really
5:10 drove miss you know it's one of the
5:11 reasons sujay and i left cisco right
5:13 and we really took a bet that you know
5:16 networking required both like cloud
5:18 and ai architectural change you know and
5:21 if you were going to do this
5:22 you're really easier to do with a blank
5:24 sheet of paper because it's really an
5:26 architectural change that's happening in
5:27 networking right now
5:28 when people think of mist uh people
5:31 think of you know in fact i'm looking at
5:33 the little background behind you've got
5:35 little wi-fi symbols on there
5:37 and when you launched you were a wi-fi
5:38 company you're part of gartner's
5:40 you know wi-fi you know wired fire
5:43 martin's land
5:44 uh magic quadrant but in fact um
5:48 give the people watching this on on an
5:50 e-week in my youtube channel a little
5:51 more detail on what this is it's not
5:53 really a wi-fi company as much as it was
5:55 a cloud ai company correct
5:58 no that's correct that's what i'm saying
5:59 if you look at the origin admits
6:01 it was really around the thesis of you
6:04 know cloud is this fundamentally a
6:05 better way to develop maintain software
6:08 you know and that's why people are
6:09 starting to move more and more of their
6:11 applications to cloud
6:12 you know one is the innovation speed you
6:14 know the fact that we can build
6:15 software more reliably and at scale on
6:18 the cloud
6:19 and then the second thing is this ai
6:21 transition right
6:22 and that was really kind of the other
6:24 part of mist is you know can we really
6:26 build something on par with a human
6:28 you know and when i saw i know if you i
6:30 don't know if you remember watson you
6:31 remember watson playing jeopardy
6:33 yes yeah you know that that was kind of
6:36 one of the inspirations is hey you know
6:38 if they can build something they can
6:39 play jeopardy on par with
6:41 you know a jeopardy champion you know we
6:43 should be able to build something that
6:44 can really
6:46 play jeopardy on par with a network
6:47 domain expert
6:49 and that was kind of that you know when
6:50 i started to realize that you know
6:52 technology was happening right ai was
6:55 really going from this marketing story
6:57 into something that was going to be
6:58 useful for all different industries
7:00 including network right and beyond just
7:02 cars
7:02 you know we're going to see aai actually
7:04 actually make a difference across all
7:06 our verticals
7:07 yeah so how close is it right now if
7:09 you're uh you know if you think of
7:11 the big leap that watson took you know
7:14 winning jeopardy uh
7:16 if you were to put missed head-to-head
7:18 um in a competition with the
7:20 the best network engineers out there is
7:22 it slightly behind is it on par is it
7:25 ahead
7:26 yeah so i would say one thing i found
7:28 also missed doing this
7:30 you know there was the architectural
7:31 change of the us making sure we actually
7:33 could build the right architecture and
7:34 pipelines to actually process this data
7:36 in real time you know build all these ai
7:38 pipelines
7:39 but interesting the other thing we found
7:41 is organizationally
7:43 you know and this is what i tell people
7:44 is you know when you see big companies
7:46 start
7:46 asking their different business users to
7:48 uh work together
7:51 that's usually a sign something changing
7:52 architecturally in the industry
7:54 you know in this case what i found is i
7:56 was able to tie the customer support
7:58 team
7:59 right up with the data science team
8:00 right and that is where
8:02 for every ticket right every customer
8:04 support ticket that comes into miss
8:06 today
8:07 we basically have marvis answering those
8:09 tickets right now and we're
8:10 at about 70 percent efficacy that means
8:13 that
8:14 you know and these are hard tickets
8:15 right these are tickets like you know
8:16 why are
8:17 why is having a connection problem why
8:19 is the zoom not working
8:21 right so right now we're at 70
8:23 championship what i call championship
8:25 level
8:25 you know where i can answer about 70 of
8:27 the questions that come in our way
8:29 um i want to get that to 90. for to be a
8:32 champion my
8:32 criteria is 90 it's like you know we get
8:35 close to 90
8:36 i feel like you know i'm playing i'm on
8:38 par with network jeopardy
8:40 well the good thing about that though is
8:42 that uh when marvis does it
8:43 and as a former network engineer i'm
8:45 saying this uh nicely
8:47 marvelous rolls eyes of the user for not
8:49 knowing what the user is doing right so
8:52 um at least you know it it doesn't uh in
8:54 a nicer way i suppose
8:56 hey um since um juniper required
8:59 yes uh i noticed there was two other
9:02 acquisitions one was
9:03 astra who's an intent-based networking
9:05 company and 128 technology
9:08 um which is an sd-wan company so explain
9:12 how
9:12 i would take missed abstract 128t with
9:15 juniper put those together
9:17 um you know tell me about that story
9:20 yeah
9:20 yeah so you know when you look like when
9:22 we started mist right
9:24 the question we were really trying to
9:25 answer is you know why are you having a
9:27 poor internet experience
9:29 uh it turned out that the access point
9:31 provided about 80 percent of the data we
9:33 needed to answer that question
9:35 and that's one reason when we started
9:37 this that i decided to build an access
9:38 point
9:39 was really to make sure i can get the
9:40 data and needed to answer that question
9:43 so since we've joined juniper our
9:45 mission is really to basically
9:47 extend marvis and ai ops across the
9:50 juniper portfolio
9:52 and we're really starting that with the
9:54 enterprise portfolio so that includes
9:56 the access points the switches
9:58 and the routers and interestingly what
10:00 2128t
10:02 brings to the party is it brings really
10:04 two things one is they have a very
10:05 unique way of doing
10:07 tunnelless uh routing so they bring a
10:09 unique way of actually creating these
10:11 tunnels back to uh
10:12 back to gateways but more interesting
10:15 with their session-based routing
10:16 is they bring more granular information
10:19 about each session
10:21 as opposed to just having visibility of
10:23 the ipsec tunnel
10:24 we actually get visibility into each
10:26 user so what ipt
10:29 128t allows us to do is now really
10:32 allows marvis to answer
10:33 more questions about applications right
10:36 in addition to connectivity
10:37 i can start answering questions about
10:39 why is your zoom not
10:40 behaving properly and it starts to let
10:43 me answer questions with more
10:44 granularity right if you're having a
10:46 connectivity problem
10:48 i can now go down into the lan interface
10:50 i can now figure out
10:51 you know is your problem due to some way
10:52 on interface you know so that is the
10:54 vision of really extending marvis across
10:57 the juniper enterprise portfolio and
11:00 then after
11:01 is really around the data center you
11:03 know that's kind of the ultimate last
11:05 piece of the puzzle right you know
11:06 somewhere you know if you're having a
11:08 problem from the client
11:10 the other end point is in the data
11:11 center somewhere that's pretty
11:13 interesting because that brings an
11:14 end-to-end
11:15 aspect to networking that we've never
11:17 really had before like historically
11:19 like is it prior to being an analyst as
11:20 a network engineer and we thought about
11:22 web engineering
11:23 wi-fi there's data centers campus
11:25 engineers
11:26 but you just have one network now since
11:28 you're able to apply that it's all just
11:30 possible
11:31 yeah and that is really the paradigm
11:33 shift this is you know in networking now
11:35 you know
11:36 in the past it's really been about
11:37 trying to manage network elements
11:39 uh but going forward the paradigm shifts
11:42 you really want to manage the indian
11:44 user experience device experience right
11:46 that is the problem that most businesses
11:47 are dealing with yeah well i've
11:49 described that sort of as a bottoms-up
11:51 approach to networking where we start
11:52 with the elements
11:53 and we try and infer user experience
11:56 right versus the other way around where
11:57 we start with experience and then
11:59 we work plot down to try and understand
12:02 how each individual component does
12:04 so that's uh that you're right that is a
12:06 kind of an interesting shift that's been
12:07 going on now
12:08 now if if um you know missed was one of
12:10 the first
12:12 maybe the first network vendor to talk
12:13 about artificial intelligence
12:15 uh since then if i go to google right
12:17 now and google network
12:19 ai i'm gonna get you know 100 different
12:22 things that come up from
12:24 you know every vendor out there some are
12:26 ai and some aren't so if i'm
12:28 watching this how do i really know that
12:31 your ai versus somebody ai you know is
12:34 better what
12:35 what's ai and what's not at here yeah
12:37 you know what i tell people about ai
12:39 ai is a concept right it's not a um it's
12:43 not
12:43 machine learning is the algorithms ai is
12:45 really the concept of doing something on
12:47 par with a human
12:48 and what you know i tell people is you
12:51 want to look at
12:52 marvis and go how close are we to doing
12:55 something on par with the human
12:56 there's a lot of different fancy math
12:58 that goes under the hood to actually
12:59 make that happen
13:00 you know to make that self-driving car
13:02 there's a lot of map that goes on to
13:03 make that car
13:04 autonomous same in the medical industry
13:06 right when you're trying to do cancer
13:07 diagnosis
13:09 so that's my analogy for people it's
13:11 like when you look at ai
13:13 you really want to answer the question
13:15 have they done something that's really
13:16 close or becoming close on par the human
13:19 in our case
13:20 you know our vision is really can we
13:22 really get marvis to be
13:24 a member of the i.t team you know can we
13:26 finally get
13:27 marvis to the point of it becomes a
13:29 trusted member
13:30 and a system of your i.t team that
13:32 actually can do something on par with
13:34 someone you would actually hire to help
13:35 you help you manage and answer questions
13:37 on your network
13:39 all right now you've um you've mentioned
13:42 marvis a couple of times can you just go
13:43 into a bit of detail
13:44 what marvis is we didn't want to define
13:47 it up front
13:48 i'm assuming that uh you know it's
13:49 planned jarvis like from iron man but uh
13:52 uh you know how what is it how does it
13:54 work does it replace an engineer does it
13:56 augment them
13:57 yeah it doesn't replace engineers i
13:59 think uh best way i would say
14:01 augments engineers and you know if you
14:03 look under the hood of marvis
14:05 what you'll find is a bunch of different
14:07 algorithms
14:09 that are there to answer different types
14:11 of questions right
14:13 you know to your point of you know we
14:14 use marvis ever for every support ticket
14:16 that comes in
14:18 you know we have different techniques
14:19 like you know if you look over my
14:21 shoulder here
14:21 things called mutual information mutual
14:24 information helps us
14:25 answer one type of question that comes
14:27 in uh we have other algorithms like lstm
14:30 to answer anomaly detection algorithms
14:33 like
14:33 are you having connectivity problems
14:35 beyond normal
14:36 in your network you know and then we
14:38 have different algorithms like graph
14:40 databases and temporal correlation
14:42 that helps us correlate user experiences
14:45 with configuration problems right
14:47 if someone misconfigures a router that
14:49 also
14:50 stops uh mtu packets from you know large
14:53 packets from coming through
14:54 that will screw up your authentication
14:57 those are very hard
14:58 problems to solve so when you look at
15:00 marvis it's really a collection of
15:01 different machine
15:02 learning algorithms that are really put
15:05 together
15:06 to really do something on par with a
15:09 i.t domain expert and then on top of
15:12 that
15:12 there's a conversational interface
15:14 because i think when we look going
15:16 forward
15:17 you know we saw the transition from kind
15:19 of the cli
15:20 you know moving to dashboards i think
15:23 the next transition we're going to see
15:24 in networking is really to these
15:26 conversational interfaces
15:28 becoming a better way to interact with
15:30 the network get data
15:31 and basically avoid you know
15:34 the swivel chair problem having swivel 3
15:37 hundreds of dashboards to get an answer
15:38 to something yeah that's uh
15:40 that that's an interesting challenge
15:41 because it's uh everyone's getting used
15:43 to this for the chair management style
15:44 where i just
15:45 look across the dashboards and correlate
15:47 the information in my head
15:48 now you've um you talked about the the
15:51 seventy percent
15:52 efficacy i'm curious to uh know you know
15:55 how
15:56 accurate is missed and marvelous right
15:58 we i think when it comes to artificial
16:00 intelligence
16:01 there's always a lot of skepticism um
16:04 even with castles and things every time
16:05 they have an accident people freak out
16:07 and things like that
16:08 so you know where was it where's it
16:09 going and where do you think you can get
16:11 to
16:12 yeah you know you know if you look at
16:14 the journey of ai ops and marcus and
16:17 where we started right now
16:18 i would say the first thing is around
16:20 data right we probably spent a good year
16:24 just making sure that we had the data
16:26 necessary
16:27 to answer customer support tickets right
16:30 and so
16:31 and this is the power of the cloud right
16:32 because you want to make sure
16:34 that when you're trying to build this
16:36 that the data you need to answer
16:38 questions is in the cloud you don't want
16:40 to have to go the device
16:41 ssh log in or do any of that so that is
16:44 the first step towards actually getting
16:46 to that
16:47 jeopardy championship level uh marvis
16:50 plane
16:51 that's where we started i would say the
16:53 second thing we started with rounds once
16:55 we got the data
16:56 in the cloud it really became efficacy
16:59 you know having marvelous answer support
17:01 tickets coming in
17:03 and that is really where we started
17:04 working our way and we probably started
17:06 10 20 percent
17:07 you know four or five years ago to a
17:09 point now we're up to 70
17:11 and interesting that's the same parallel
17:13 if you look at jeopardy how long it took
17:14 him to build something to play something
17:16 on par with the championship level
17:18 jeopardy player uh so i think we're on
17:20 par to you know i think in parallel with
17:22 that we're on part of that right now
17:24 we're at 70 percent headed to 90 percent
17:26 right now
17:27 what do you think you get to 90 uh i
17:30 i keep saying as we get closer and
17:32 closer it gets harder and harder you
17:33 know you get close to the last five
17:34 percent
17:35 so i think we're still a year or two
17:37 away from the 90
17:39 range where we will basically have
17:40 marvis answering 90 of all the tickets
17:42 coming into
17:43 coming into miss yeah it's like a golf
17:45 swing you get better fast and then all
17:47 this in your plateau right so
17:49 and by the way i will uh tip my hand to
17:52 the good folks who missed i as a former
17:53 network engineer i'd say there is
17:55 nothing
17:56 harder i believe the speaker there's
17:57 nothing harder in corporate id than
17:59 solving wi-fi
18:00 problems just because there's so many
18:03 variables it could be everything from
18:04 dhcp to radius to people not configuring
18:07 them properly it's on the client
18:09 access point so if you can do that i'm
18:12 fully confident that you can do
18:14 you know you know sd-wan is pretty hard
18:16 too but uh you know i'm pretty confident
18:18 so there's a lot of interest in
18:20 artificial intelligence and machine
18:22 learning
18:22 i i think it's been positioned as
18:26 really the next wave of where i t is
18:28 going and in fact i don't think there's
18:29 any question
18:30 that i think he's going to have a bigger
18:32 impact societally than
18:34 maybe every anything since we saw the
18:36 internet but
18:37 there is a bit of a skills gap here so
18:39 if i'm a network injury and i'm watching
18:41 this and i'm interested in ai
18:43 what do i do to get started you know i
18:46 think you know
18:46 the interesting thing we are putting a
18:48 ton of pressure on the it
18:50 teams right now right i mean you know
18:52 we're asking them to go from cli
18:54 you know becoming you know routing
18:56 switch ap
18:57 experts you know we're asking now that
19:00 for them become python programmers right
19:02 you know because we're basically moving
19:04 into this cloud api
19:06 paradigm uh which is really forcing i
19:09 you know the future i t person really
19:10 become a good programmer
19:12 um as we move to ai ops which is really
19:16 another form of automation right it's
19:18 basically another tool
19:19 now for helping them automate how they
19:21 manage these networks
19:23 we're really really asking the it teams
19:26 to start becoming somewhat data
19:27 scientists
19:28 you know we don't need them to program
19:30 them but they at least need to start to
19:32 understand the basics of
19:33 the different data science algorithms
19:35 what they're good for so those are kind
19:36 of the basic skill sets you know
19:38 and it's really happening with python
19:40 right now right most of those it teams
19:42 are just starting to wrap their arms
19:44 around programming for apis
19:46 and automating with python scripts and
19:48 such uh
19:49 aiops is kind of the next step in that
19:51 evolution
19:52 of taking fancier ai up data science
19:56 algorithms
19:57 to actually actually all help automate
19:58 some of the more complex problems
20:00 they're dealing with
20:01 yeah in fact um this is an interesting
20:03 trend i've been watching because a few
20:05 years ago if you look at what i've been
20:06 writing on you know our network world
20:09 you know sites like that it was it was
20:10 about help urging network engineers to
20:13 become programmers
20:14 but i think i've taken a step back from
20:16 that where it's not really a programmer
20:17 per se
20:18 as much it is as kind of a software
20:20 power user
20:22 and through the research i've done it's
20:23 actually been pretty remarkable that
20:25 three cores of network engineers i've
20:27 talked to have never made a single api
20:29 right so we're trying to advance our
20:32 systems but i think there is a bit of a
20:33 skills gap here so it's a
20:34 it's a good time to be a network
20:36 engineer i think the opportunities in
20:38 networking have never been greater
20:39 you just need to change your skill set a
20:41 little bit and then doing things the cli
20:43 way is probably
20:43 rapidly kind of depends yeah most
20:46 definitely
20:47 i mean i mean you're looking at right
20:48 now right i mean almost every it
20:50 person i know is trying to learn python
20:53 right they're all
20:54 the next step is how to basically uh
20:57 leverage all the apis that they're that
20:59 are becoming available
21:01 all right well bob uh you know thank you
21:03 very much for your time it was uh
21:05 great talking about ai missed wi-fi all
21:07 those things i think
21:08 you know one of the uh you know really
21:12 fascinating things about wi-fi
21:13 is it's become this foundational
21:15 technology right it used to be the
21:17 other network uh but now it's the
21:20 primary network for almost everything
21:21 in-store shopping
21:23 uh you know every hospital schools
21:25 everywhere you go if you don't have good
21:26 quality wi-fi
21:27 you don't have anything so um so you
21:30 know kudos to
21:31 the good work you've been doing over
21:32 there at juniper uh anyways i'm uh
21:35 uh thanks bob uh for joining me in the
21:37 stock this spot leadership video
21:39 i'm uh zeus caravallo from ck research
21:41 and on behalf of my partner ewik
21:43 thank you for watching
21:58 [Music]
22:01 you