Juniper Networks on Automation in the Workplace

0:00 this morning you announced a partnership

0:01 with a company called dragos which is

0:03 cyber security that's right uh could you

0:05 tell us a little bit about that i guess

0:06 i'm also curious sort of

0:08 the old uh adage about buyer bill that

0:10 seems like you've went to a partner

0:12 rather than buy or build uh just a

0:14 little bit about why you made that

0:15 choice yeah so the if you look at the

0:17 industrial control systems or what is

0:19 known as operational technology

0:21 environments like uh electric grid

0:24 those uh environments are subject to

0:27 attack cyber attacks right increasingly

0:29 from east west attacks those called that

0:31 means those originate within the system

0:33 that get compromised

0:35 so we are a leader in providing security

0:37 solutions like firewalls we provide a

0:40 cloud-based security director and all

0:42 that but dragos is a leader in providing

0:44 threat intelligence so if we can get the

0:47 threat intelligence from them

0:49 in real time then we can react in near

0:51 real time to all the cyber attacks and

0:53 protect the environment so that's the

0:55 value proposition that's why we are

0:57 partnering with who what what customers

0:58 are sort of asking for that

1:00 oh many customers as i told you the

1:02 energy great in this country is very

1:04 vulnerable lots of industrial control

1:06 systems in factory automation and all

1:08 they are also vulnerable to that

1:10 traditionally they were air gap systems

1:12 that mean they are separated from the

1:13 rest of the infrastructure but that's

1:14 not true because of internet now so

1:17 those systems are uh increasingly

1:19 vulnerable to attacks from all kinds of

1:21 things those attacks come from within

1:23 that's a real challenge so you're

1:25 traditionally known as you've been kind

1:27 of a customer or sorry a company that's

1:29 worked with the telco industry it sounds

1:31 like when when you joined around 2019

1:33 you've made quite a pivot uh there was

1:36 an acquisition of an ai company called

1:38 mist

1:39 you've moved into services and

1:41 enterprise talk to me a little bit about

1:43 about why uh what that's what's like

1:46 been the biggest challenge for that so

1:49 far so i think juniper traditionally was

1:51 a service provider company people may

1:53 not know approximately about 60 percent

1:55 of the traffic that you see on the

1:57 internet goes to juniper devices and

1:59 systems but the service provider market

2:01 has been flattening or declining

2:04 so the transition we made to

2:05 [Music]

2:07 cloud public cloud providers as well as

2:09 enterprise started with that so we have

2:11 acquired multiple companies starting

2:13 with mist then abstract and 128t the

2:16 idea is to be able to offer both

2:18 software and systems to enterprise

2:21 customers so we can increase that

2:22 revenue could you give some examples of

2:24 where that that pairing has worked it's

2:27 worked well for you multiple places for

2:29 one example is most enterprises manage

2:32 wi-fi networks manually using network

2:34 operation centers on-prem right and that

2:37 is very labor intensive and very slow in

2:40 terms of being able to detect the

2:43 problems and reacting to them

2:46 so what miss brought is that they're the

2:48 first company to do cloud managed uh

2:51 wi-fi uh network management which allows

2:54 them to collect data from all the

2:55 devices from your iphone uh phone ipad

2:58 macbook any of the devices access points

3:01 all that data gets fit to machine

3:03 learning model and machine learning

3:05 models correlate and self-diagnose so

3:07 you can go and start correcting the

3:10 problems before they start showing up as

3:12 alerts in some network operations

3:14 so reduces the amount of manual

3:16 intervention in the network by a

3:18 tremendous amount

3:20 some of our customers for example have

3:22 um one of the largest retailers has

3:25 stated that their troubleshooting

3:26 tickets went down by 90

3:28 so we call it self-driving network it

3:30 tries to self-resolve the problems

3:33 what was that ninety percent over what

3:34 the troubleshooting tickets that used to

3:37 resolve manually now they are getting

3:39 self-resolved by that over like a year

3:41 on year two yeah for three-year period

3:43 yeah yeah yeah and so and you're seeing

3:45 this in in retail as one of their other

3:47 industries retail healthcare education

3:50 lots of universities are using our

3:51 products more and more we are beginning

3:53 to see federal gov

3:55 the federal accounts also beginning to

3:57 see that that's one example the same

3:59 thing with data center we acquired a

4:01 company called abstra that does close

4:03 loop automation of network fabrics and

4:05 data center where the idea is to build a

4:07 model of the network and upper a a a

4:11 prior

4:12 before deploying the network and then

4:14 you constantly monitor it to check

4:16 against the model and if you see any

4:19 diversion from the model you try to

4:20 correct it

4:21 so what's changed starting in march 2020

4:25 and then

4:27 yeah what changed is i think

4:29 they're

4:30 good and bad i think the good thing is

4:32 the demand increased because a lot of

4:33 people started working from home so

4:35 service providers started ordering more

4:37 equipment

4:38 we saw a lot more demand for hybrid

4:41 workforce which means the broadband

4:43 connectivity to home became more mission

4:45 critical required more security so we

4:47 have seen a lot more increase in both

4:49 enterprise

4:50 cells as well as service provider side

4:54 what's been the biggest challenge for

4:55 you you think on the technical side as

4:57 for the pandemic i think the biggest

4:59 challenge has been that when this hybrid

5:02 workforce happened you want to deliver

5:03 the same experience to the home worker

5:06 that you do to the office worker so it's

5:08 no longer the hub and spoke model you

5:11 know that

5:12 the campus is the hub and the spokes

5:14 everything became distributed so that's

5:16 the scale has to increase so i think uh

5:19 anything we do in terms of automation

5:21 helps there

5:22 so you i mean you manage a team but you

5:24 probably can't share how big the team is

5:26 i mean

5:27 so my role is as a chief technology

5:29 officer to drive new products new

5:32 technology strategies so my team is not

5:34 more than 300 people but engineering

5:36 team is much larger so i work closely

5:38 with them yeah i'm curious what how you

5:40 think about the trade-offs and sort of

5:42 if

5:42 if you think about it as a trade-off i'm

5:43 sure sure it is and and sort of the

5:45 traditional networking business and then

5:48 and then some of the advances you're

5:49 doing and on ai and software like how do

5:52 you measure that and allocate yeah i

5:54 think the skill set modernization is the

5:57 one of the challenges right because we

5:58 have to bring more people with

6:00 experience in cloud native architectures

6:02 uh artificial intelligence machine

6:04 learning and that's the transition we

6:05 have been making both organically as

6:08 well as inorganically yeah um you

6:10 mentioned the cloud the the big

6:13 hyperscale cloud companies are customers

6:16 yes

6:17 um they're also

6:19 all of them in amazon microsoft google

6:21 are sort of building their own custom

6:23 silicon or talking about it

6:26 uh and sort of

6:27 investing and sort of owning

6:30 using vertical jargon here but like

6:32 vertical um they're owning a lot more of

6:35 the of everything uh how does that

6:37 change things for for your business so i

6:39 think uh where people are trying to

6:42 build ships is in my opinion commodity

6:44 market which is a very

6:46 very well defined functions where we are

6:48 focused on developing custom chips uh

6:51 which are very energy efficient i mean

6:53 generation to generation we reduce the

6:55 energy consumption of our routers by

6:57 thirty to forty percent they they say

6:59 thirty to forty percent by using custom

7:01 chips which are designed to be very

7:03 highly performant but also very energy

7:06 efficient what's the trade-off there

7:08 so i think uh

7:10 when we build the product if we use uh

7:12 those chips

7:13 we control our destiny right we are not

7:15 only providing performance we can

7:17 provide the highest possibility of the

7:19 performance allowed by the technology

7:21 curve and those products we sell to

7:22 hyperscale yesterday they are not

7:24 building those themselves they're buying

7:25 from us

7:26 what keeps them from building that

7:28 tomorrow i think eventually everyone

7:31 will try to tries to go up the

7:33 technology curve and our our opportunity

7:35 is to stay ahead of it as long as we

7:37 stay ahead of it uh they will not catch

7:39 them i got it i was talking to my

7:41 colleague who covers your industry more

7:43 closely and said well you know the cisco

7:45 is saying kind of the same thing

7:47 i guess i'm curious what you think and

7:48 i'm sure that not just cisco but but all

7:50 the competitors are moving in this

7:51 direction

7:53 um like how do you

7:55 stay out of the curve yeah so i think

7:58 some companies have been traditionally

8:00 focused on enterprise market so for us

8:03 that's a focus shift that we have made

8:06 and we're trying to take advantage of

8:08 our high-end products and bring them to

8:10 the enterprises so that we can

8:12 not only

8:13 grow but grow with differentiation both

8:15 in software and hardware systems that's

8:17 the strategy we are following yeah

8:19 um

8:20 supply chains kind of out of whack

8:22 uh what does that mean for you

8:25 so i think uh uh

8:26 whole industry is facing supply chain

8:28 but so far we have been able to manage

8:30 efficiency of the supply chain by

8:32 diversifying as much as possible so in

8:35 immediately we do see that we'll

8:37 continue to meet our demand

8:40 but our backlog continues to increase

8:42 which is good and bad for future but i

8:45 think uh so far so good

8:47 and you also i saw the most recent

8:49 earnings it seems like you're hiring

8:51 which just seemed to be the opposite

8:52 trend of a lot of companies around here

8:54 yes um do you are you how

8:58 what's your

8:59 outlook on sort of how long that lasts

9:01 is this

9:03 so we are hiding in two places like i

9:05 said in r d we need to hire for new

9:06 skill sets like cloud native

9:08 architecture artificial intelligence

9:10 machine learning that will continue but

9:12 also we are modernizing ourselves first

9:14 by having more in enterprise salesforce

9:16 so because our focus on salesforce as

9:18 long as our growth continues we'll

9:20 continue that path i think yeah i'm

9:22 gonna go back to to just just make sure

9:24 this like the the self self driving

9:26 driving self enough driving network for

9:28 for uh a quick

9:30 second like what um

9:32 are you seeing the sort of customers

9:34 that where where are you seeing like is

9:36 it sort of your existing customers that

9:38 are moving to this is it new customers

9:39 that you've never had before

9:41 uh kind of so when it comes to

9:44 self-driving networks especially in the

9:46 case of mystery one we have taken the

9:47 strategy to apply that principle to

9:50 wi-fi networks access

9:52 like security access and all as well as

9:55 campus branch

9:56 for that we're seeing new customers

9:58 because this is a completely new

9:59 approach where we are displacing

10:01 traditional vendors who are doing manual

10:04 intervention driven network operations

10:07 to automation so that's completely new

10:09 and that's where the growth is coming

10:10 yeah how do you stay up uh on the latest

10:13 in in ai and i know that hiring is

10:15 clearly like a huge challenge like

10:16 everyone's trying to hire ai engineers

10:19 two ways one is that inside juniper we

10:21 created what we call juniper university

10:23 where we brought the experts to start

10:26 building curriculum to

10:27 retrain our engineers and secondly we

10:30 focus on hiring new college graduates

10:32 because if you catch them young and

10:34 early you can develop them into

10:37 more experience not like poaching from

10:39 deep mind or something like that

10:43 yeah

10:45 and but that's the like that's a better

10:46 strategy you think there's like yeah i

10:48 think the better strategies to uh

10:50 invest for long term so i think juniper

10:52 university is a good way to retrain our

10:55 engineers who are hungry to learn new

10:57 skills and get the new college graduates

10:59 yeah i'm a quick one before we jump to q

11:02 a because i'm reluctant i'm not an

11:03 expert in like web 3 and and blockchain

11:06 but i'm sure you're thinking about it

11:07 yes

11:08 where

11:09 what are your thoughts

11:10 what's the how much how much time do you

11:13 spend thinking about it like so i think

11:14 that's one of the my areas is that what

11:17 comes next three to five years we have

11:19 to worry about is the web3

11:21 there's also a lot of hype around it but

11:23 of course the underlying technology so

11:26 called distributed ledger is

11:28 worthwhile it's going to allow us to

11:30 secure supply chains and other parts

11:33 that's what we're looking at how to

11:34 apply it to the places where it's

11:36 designed to be

11:37 uh but not necessarily go by the nft and

11:40 cryptocurrency

11:42 um okay

11:43 that we didn't prepare for my poor

11:44 eyesight

11:46 uh

11:47 how are you first one is how are you

11:48 trying to solve the cybersecurity talent

11:50 gap

11:51 uh with automation i'm not as familiar

11:53 with the cyber security talent gap but i

11:55 imagine you know what that means my i

11:56 think talent gap i think they're

11:57 referring to is that hiring people with

11:59 security expert is also hard because

12:01 there are only

12:03 rsa conference right now is full of them

12:05 you can go steal some of them but uh uh

12:08 i think the

12:09 the question

12:11 really

12:12 leads me to the same answer right that

12:15 by putting more automation that example

12:17 of dragos and juniper partnering today

12:19 will be taking the threat intelligence

12:21 feeding that into machine learning

12:23 models so that we can do threat

12:24 protection that doesn't require as many

12:26 cyber security security experts that you

12:28 would normally get

12:30 uh the next one's really interesting

12:31 into kind of a two part i think um

12:34 so the expansion of the remote workforce

12:37 uh and a lot more

12:39 wi-fi connections and devices

12:41 uh one i guess what does that mean for

12:44 for cyber security and and and two and

12:46 maybe well man that's more important but

12:48 what does it mean for network

12:49 reliability yeah uh and what have you

12:51 seen so far so i think that's what with

12:53 hybrid work model what happened was the

12:56 home became as much a mission critical

12:58 part of the network as your office

13:01 so you have to take the technologies

13:03 like sd-wan and

13:05 also make them available for home juices

13:07 so what we have done with the 128t

13:09 acquisition we combined our security

13:11 portfolio with sd-wan so that for branch

13:14 offices home offices we can provide

13:15 secure access

13:17 and that like do you feel like it's

13:18 straining like how much can you can you

13:21 give a sense about like

13:23 the strain is it sort of like continuing

13:25 this to strain or is it kind of reaching

13:27 i think it's not a strain for us which

13:28 is a it's a clearly growth opportunity

13:31 for us but i think the strain if you use

13:33 the traditional methods of network

13:35 operations if you're going to have a

13:37 bunch of people sitting at a network

13:38 operation center watching monitors

13:40 getting audio visual alerts that's not

13:42 going to scale so by using this ai

13:45 driven self-driving network approach we

13:48 believe that we make the problem simpler

13:50 and

13:50 you can tackle it very easily uh this

13:53 next question is really interesting

13:54 actually um

13:55 what do you think about open source ai

13:57 driven network monitoring solutions uh

14:00 the example was sort of like if if there

14:02 is and maybe it exists i don't know but

14:04 a tensorflow for network security from

14:07 um would that come out from juniper

14:09 yeah so the first of all the open source

14:11 solutions are not a threat

14:13 i really like the open source ecosystem

14:15 because it allows us to contribute but

14:17 also take from the contributions of the

14:19 other and have you been we have been

14:21 very actively uh participate in open

14:23 source but what we'd like to do is

14:25 somebody has to take that solution

14:27 harden it make it

14:29 accessible and usable by customers

14:32 that's what we can do so i think we can

14:34 take advantage of the open source in

14:35 both ways contribute but take it so

14:38 can you give me a sense about how much

14:39 you're contributing now so so for

14:41 example it's the kubernetes is one of

14:43 the most underlying cloud native

14:46 networking architecture from google

14:47 google put in open source we are active

14:49 contributors to that we now have our own

14:52 kubernetes-based cloud networking

14:54 solution that we make it available to

14:56 others uh

14:59 jumping off from web 3 speculation to

15:01 quantum computing speculation uh

15:04 but what worries do you have in a

15:06 potential quantum future about security

15:08 and encryption yeah so the quantum

15:10 computing one of the things we have done

15:12 and with this public information we

15:14 started using it for quantum key

15:16 distribution

15:17 in a secure channel you need a key

15:19 distribution and quantum

15:21 technology computing allows us to make

15:23 it more secure the question refers to

15:25 what happens if you start using quantum

15:27 computers

15:29 to decrypt the data by storing it i

15:31 think there are more post-so-called

15:34 post-quantum encryption algorithms

15:36 already being developed in academia and

15:38 we are looking at some of those to

15:39 collaborate with academia to evolve

15:42 those so by the time the quantum

15:43 computing starts getting applied to uh a

15:46 traditional encryption we should be the

15:48 post quantum era with respect to

15:50 encryption you should be this in the

15:52 post era with respect to encryption

15:54 algorithms and so on the guy because

15:57 right now i think the problem is the

15:58 following right if you

16:00 take the any of the encrypted data store

16:02 it and feed it to any quantum computers

16:04 maybe a day later you will have it

16:05 unencrypted so that's a big thread to

16:08 the traditional encryption algorithms

16:10 yeah so people are developing so-called

16:12 post-quantum encryption algorithms which

16:15 will not be

16:16 um decryptable by quantum computers

16:19 that's where we have to go

16:21 how much i'm i'm a quantum skeptic a

16:23 little bit but because people have been

16:24 talking about it for a long time

16:26 but do you how much of your time do you

16:27 spend thinking about that so we we have

16:30 done a one sort of uh pathfinding

16:32 project only poc where we try to use it

16:34 for key distribution that seems to work

16:37 we are working with the uk's department

16:39 of defense to try it out oh wow so it's

16:41 very early it's early but you have to

16:43 explore that before the things get there

16:45 all right i really appreciate it thanks

16:47 raj for your time thank you everyone for

16:49 very excellent questions

16:51 and i'm going to turn it back over to

16:53 janet