Unleashing the Potential of AI-Native Networking

0:00 hello my name is Patty and R from hyns and welcome to today's webinar thank you for taking the time to be here today we

0:06 have an exciting program for you but before we get started I would like to highlight a few things so you know how

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1:00 today's program unleashing the potential of AI native networking sponsored by Juniper Networks our speakers today are

1:08 Matt Roberts Healthcare lead andolini saram vice president of products at

1:13 Juniper Networks with that I'll hand it over to Matt andolini thanks Patty

1:19 welcome everybody today sunin and I are going to touch on a few Trends and challenges within what I'll calls the hls segment and how AI Ops is elevating

1:27 user experience and uh also overall it efficiencies in these particular IND

1:32 Industries so uh let's jump right on in here so as many of you likely realize

1:38 healthcare industry faces a large amount of challenges across the board today I'm probably uh putting up a few statistics

1:45 that you're all very very well familiar with at this point in time uh however you know not only are we concerned with

1:51 the bottom line here in healthcare more than ever there's so many moving parts to take into account as you look at

1:56 these particular segments cyber attacks continue to increase we've had over 133

2:02 million patient record breaches in uh 20 uh 23 which is an absolute record I

2:07 think it was 156% increase over 2022 nursing burnout unfortunately continues

2:13 uh you know it's significantly been uh ticking up if you will since covid due to a wide range of different factors

2:19 could be expanded duties uh increased patient workload uh also safety unfortunately comes into play here too

2:26 uh let alone the time and energy having to search for equipment uh which is not only annoying but it does have impact on

2:33 patient care that also has impact on morale within the facilities and you add in layer zero things and energy

2:39 challenges that continue to mount as the cost of power and cool buildings infrastructure all those things continue

2:44 to uh to take place and we have to be cognizant of that now if we add in the emergence of AI and I fully realize AI

2:52 it is a buzzword right with everyone having their own definition of what AI truly is but over 3ars of healthc Care

2:58 Professionals expecting widespread adoption over the next three years it's becoming very very real okay and so

3:04 there's some really yeah what I'll say is tangible benefits that I hope you get out of this today uh that can be

3:10 realized uh but we also have to be cautious when we talk about privacy we talk about governance we talk about

3:15 ethics and so if sunen and I uh do our jobs right today which I hope we do uh

3:20 we hope you come away with actually some several good use cases where AI is fundamentally making a difference in

3:26 these types of environments so a few more trends that we felt were interesting especially as it relates to

3:32 outcomes experience cost reductions they're all much needed in healthcare you'll see those I'm not going to read

3:37 each and every one of these uh you know on the slide here you'll see AI mentioned multiple times and I firmly

3:43 believe that you're going to continue to see this technology become more entrenched in all aspects of digital care okay and so if I'm being honest

3:50 it's also all about the data all systems obey the Golden Rule I think we remember

3:56 this uh if you took Computing classes garbage in G out so if you want good results you've got to feeded good data

4:03 and this is why the quality of what we like to say is the Telemetry data really really does matter and as we go through

4:09 the presentation today my hope is that you'll get a good understanding of the seven plus years that we've spent with

4:15 data science and training models that are in place to really produce solid results for our customers literally

4:21 changing the day-to-day operations for the IT staff now not only are each and

4:28 each of these three pillars uh they're fine it's a it's a fine delicate balance uh it's an absolute necessity in today's

4:34 Healthcare world uh I think we all understand the number of devices the number of users digital Solutions

4:40 they're not going down right it's only going up I think that's obvious probably to everyone listening in the plan is to digitize everything from high dep video

4:47 to robotic surgeries to AR VR uh 640 slice scanners you name it right the

4:54 technology just continues to be more advanced so it's either here today or

4:59 it's coming in your environment today so you have to be prepared for it right you've got to prepare accordingly and to do so it's a balancing act uh keeping

5:07 the lights on while planning for strategic growth right so that kind of fits right there in the middle now

5:12 migration without disruptions it's a necessity in healthcare uh we know this is a 247 365 environment um it is the

5:21 difference between also allowing patients to be admitted seamlessly and cleanly versus diverting patients to a

5:29 competitor because your systems are down we're fortunately we're seeing a lot of this stuff today and all this is

5:34 underpinned by the ability to safeguard the data uh when we start to talk about against cyber criminal activity okay and

5:42 so you've got to be able to do that at all costs and as mentioned on the last slide there cyber criminals are getting

5:48 smarter for organizations it's sadly no longer if uh but it's when a compromise

5:55 takes place and that's why it's also important to be able to detect and respond at a much much higher speed and

6:01 if you can build predictability into the infrastructure to do just that you're going to be in a much much better position right when those events

6:07 unfortunately do take place so while challenges continue to mount there is

6:12 light at the end of the tunnel it's critically important to also not lose sight of how everything is connected in this digital era right so this is why

6:18 we're here today and we're talking about this and it's been proven time and time again that connectivity is not the same

6:24 as experiencing a great connection and I'm sure most of you that are listening in today have never heard any of these

6:30 complaints that are put up on the screen you know we've got a great fast you know connection but the EHR is still slow why

6:36 what's wrong with my tele Health session why is it jittery why am I dropping packets or I'm getting half of a voice call working or I'm dropping as I move

6:43 around the facility from room to room or from hallway to hallway right A lot of these things that we hear and joking

6:49 aside we we we all hear them and we continue to hear them but let me ask a simple question to everybody if you

6:55 could take a big big Spotlight and shine it on the dark spots of your netor work would you try

7:01 it okay so as we go through this today I want you to think about that and I mentioned a spotlight for a good reason

7:07 so if you're you're in healthcare it operations you fully know that the environment is filled with blind spots

7:13 and it's a lot of this finger pointing between teams right and if the connection experience isn't measured you

7:19 absolutely have no idea what type of user experience is actually being had so

7:25 how do I know if my clinicians my staff my patients my guests they're having a good experience how do I know if my

7:31 applications are performing properly which may impact in user experience why do I rely on my network staff or my

7:39 users to report the issues back so that my network staff then has to jump in or my help desk to try to troubleshoot

7:45 something which can take not only minutes hours can take days and weeks to try to figure out the issue sometimes

7:51 things don't get figured out and we call that chasing ghost and you're continually chasing a ghost and then

7:56 also you know how do I reproduce issues much much faster because today it's like

8:02 digging sometimes in a needle in a hay stack and trying to find that needle and so again as we go through this presentation today you're going to find

8:08 different ways to leverage AI Ops to do just that to fix these these issues that are very very common and we'll call our

8:14 blind spots within the network um the good news is is that we're not asking you to be the first you know provider

8:20 life science company on the Block to try it and so what we do with AI um I'm going to keep it in really really simple

8:27 terms is we help our customers deploy netwk Works faster lower costs fewer

8:32 mistakes right those three these three pillars uh while we also provide day two operation advantages so

8:38 lowering uh and seeing 80 to 90% reduction in trouble tickets so again

8:44 how do you know if your clinicians are having a good experience on their on their devices uh on their applications

8:50 like z uh tomb excuse me if I could talk teams or Zoom barcode scanners well if

8:56 we can take the guesswork out of network experience and we can use reinforcement learning and AI technique all combined

9:03 with realtime feedback it's simply not possible in a traditional controller

9:08 based architecture so you've got to do something different through Modern microservices which soon ly will address here in a few minutes now we get

9:16 Telemetry data from teams and zoom so if your physician had a a zoom call it was

9:22 a bad Zoom call last Thursday and it was perceived to be the network let's say R AI would have told you just that okay

9:29 however with video conferencing it's not always the network even though it is the first thing that is oftentimes to blame

9:35 so now that we've got the Telemetry data from the endpoint on teams or zoom and those particular examples uh we're

9:41 finding out frequently something actually maybe on the user device that's pegging the CPU which was maybe impacting the user experience so again

9:48 getting down deeper into what the application is what's happening on the network and then triangulating all this

9:54 data and getting to the point and resolving in a much much faster time so that the end user can be uh much much

10:01 more advanced if you will and seamless as as we move along now how do we do all this soonly we'll talk a little bit more

10:07 in detail but we capture over 150 different state changes and data points on every client every minute uh we know

10:14 if somebody had a PO roome uh we know po rooms are very common in healthcare we

10:19 know if they you know if they or someone typed in a password wrong so we can't see the password but we can see that they failed the authentication step and

10:26 we can see why uh we signal to our cloud uh and we ask AI to do what your best

10:32 technician could do if they were sitting there 247 side by side with every clinician Walking The Halls with

10:39 sniffers really trying to watch The Experience okay so we're taking a lot of the manual work out of this additionally

10:46 our virtual Network assistant which we call Marvis continues to be what all also say is a huge cya for our Network

10:53 opy raters you know today so every day every week every month every year Marvis continues to get smarter continues to

11:00 learn continues to help really proactively identify resolve issues before they actually impact user

11:07 experience so with all that being said I'm going to turn this over tosini who's going to give you a little peek behind the curtain to actually how we make this

11:15 all happen thanks so much Matt really appreciate that overview so again

11:21 welcome all thank you for your time today and let me now tell you how healthc care providers are changing the

11:30 experience for the end users leveraging aops and specifically what we're doing

11:36 here at Juniper as we are transforming the networking industry by simplifying the day to operations not so much from

11:43 your managing your network and managing the boxes but it's all about delivering the best experience across the

11:50 Enterprise stack to deliver the best experience your end users your nurses

11:56 your clinicians your patients can have when they connect to the network and a key part of that um the

12:02 foundations of how we deliver that are all based on the client level visibility

12:07 so as Matt mentioned we create a state machine for every client now why is that

12:12 important why does that matter it matters because that's what allows us to know exactly what the prec connection

12:19 postc connection experience for every user Wireless or wired across the van is

12:26 and if the experience is not good more importantly be able to proactively notify the operators hey Marvis found an

12:35 issue it's impacting these users these users could be nurses these users could be devices that are being used by your

12:41 patients to access applications and not only do we tell you proactively hey here

12:47 are the clients's impacted we also tell you exactly why they're impacted and what do we need to go fix to resolve

12:53 those issues this all goes back into the aid driven support right as Matt said

12:58 you know no longer need to have people go on site when an issue happens to try and figure out what was the issue wait

13:05 for it to happen again set a packet sniffers to try and capture the problem

13:10 with the AI driven support mechanism where we're using AIML constantly in the back

13:18 end it's monitoring all the right Telemetry coming in through our Network

13:24 for the end clients we already will be able to to identify the experience of

13:31 the end users and be able to proactively notify you if there's an issue that's impacting the end user

13:37 experience all of this imagine the zettabytes and zettabytes of of

13:42 telemetry information coming into the cloud for every user connecting to the

13:47 network it's all possible and viable because of the microservices cloud

13:53 architecture that is the underlying Foundation that is essential to be a

13:59 able to provide the client level visibility to be able to measure the

14:04 service level expectations of every user as they connect to the network and

14:11 continue to use the network for accessing their applications and last but not least

14:16 critical to the end user experience also is digital engagement so as part of this

14:22 SAS platform solution and our Network portfolio we also are a able to enable

14:31 realtime engagement use cases for delivering better patient experiences to

14:36 navigate their way around uh the healthcare facilities as well as Drive

14:42 operational benefits by being able to find your assets leveraging again the

14:48 same infrastructure and the same Cloud platform end of the day it's all about

14:54 how we can deliver the best experience to the end users connected to the Network and also make it extremely

15:02 simple for Network operators to deliver that experience leveraging the aops

15:07 network stack that we have built as part of our platform and all of this is 100%

15:13 open API driven architecture it's all standards based again but the focus

15:18 again is all about delivering that best experience the key aspect the key

15:24 paradigm shift that we are driving like why is AI native networking important why do we care we care because we are

15:32 now moving towards managing the end user experiences and not managing the network

15:39 elements as Matt said earlier right making every experience count making

15:46 every connection a great experience where we are moving the needle where we

15:52 are changing the industry is and where we think it's absolutely critical especially in the Life Sciences

15:59 Healthcare segments is how do we ensure how do we assure that the experience

16:06 that every user has on the network is the best possible and that is where the

16:12 whole focus is it's all about client to cloud or client to Applications right as

16:20 your life sciences caregivers your nurses your clinicians access their

16:26 applications access patient records how do we make sure they have the right data available to them at their fingertips

16:33 within seconds how do we make sure that when a patient is is setting up an appointment uh with their caregiver that

16:40 they're able to navigate all the way from their home coming to the parking lot and then most importantly once they're in the parking lot how do they

16:47 navigate huge Health Care campuses to get to their appointments in time and get again the right information at the

16:54 right time VI digital engagement and that is where this a stack comes into

17:00 play removing all the blind spots what is critical here again is the Enterprise

17:05 blueprint what we are delivering with the microservices cloud architecture is

17:11 the ability for us to measure using AIML using unsupervised machine learning

17:17 using reinforcement learning in various aspects of the Telemetry coming in is

17:22 measuring first of all the end user experience as the end user's traffic pattern goes through Wireless the wired

17:29 the St van and we've also now extended it towards our routing stack as well as

17:35 pulling in anomalies from seen in the data center tied to that is the ability to securely on board devices both users

17:43 and iot devices but through this entire network stack how do we assure the end

17:49 user of the best experience possible and that's exactly where continuous learning comes in that is where the Marvis aops

17:57 framework comes in where we're able to measure the experience root cause or

18:02 identify whether it's good or bad and most importantly if it's bad why is it

18:08 bad we are out there every day every minute every hour finding the needle in

18:13 the haast stack problems across the full Network stack that are impacting end user experiences so

18:21 the new kpi of the network for us is not Network up time that's a given the new

18:26 kpi of the network for us is all about that end user client experience are they

18:32 having the best experience possible on the network and if not why is that and how can we then leverage our AIML

18:39 technology to go into a self-driving mode and tell you exactly where the issue might be that's impacting the end

18:46 user now how do we do that how does aops enable such a framework to give

18:53 this granular visibility on every user experience coming into the network and

19:00 that again is exactly where the microservices cloud architecture plays a great role with the

19:08 microsof cloud architecture we essentially have built a platform where we can consume a synchronous Telemetry

19:16 coming from the network for every Wireless and wired client and this is

19:22 where you see us looking at pre- connection metrics on the wireless side such as time to connect successfully

19:28 connects coverage roaming and also very clearly be able to identify hey first of

19:35 all is the experience good or bad so what you're seeing here is a huge Paradigm Shift it's not about just a

19:41 simple time series view of network up time this is about actually measuring

19:46 the network experience in terms of successful user minutes or unsuccessful

19:52 user minutes if we find a user who's not able to connect to the network

19:57 proactively the aops engine will notify you that hey 1 2 3 4 XYZ users are not able to

20:04 connect but also tell you exactly why is it a DHCP problem is it an authorization

20:10 issue is it because of a van circuit issue that we are seeing intermittent connectivity to the clients and most

20:17 importantly once they've connected our service level experience framework is also able to

20:24 identify is every user getting the coverage they need and and even more so

20:30 in today's world it's more about capacity is every user getting the

20:36 capacity they need on this shared spectrum that we call Wireless right today when things don't work the first

20:43 finger that is raised is the Network's not working right and obviously superlative terms in the negative have

20:48 been used to qualify that experience the goal for us is first of all even before

20:54 that first finger is raised on the network being an issue be able to qualify

20:59 is there a good experience or a bad experience happening on the network and then secondly very quickly be able to

21:05 qualify is it a network problem or something else and if it's a network problem exactly where it is so we

21:11 believe in something called meantime to innocence because as many times the network is the culprit it's it's as many

21:18 times also not the culprit um and that's where the meantime to innocence framework comes in with a

21:24 service level expectation so for every user why or Wireless we are creating a

21:30 state machine pre- connection post connection to give you this enormous visibility into what is the experience

21:37 of every user and if it's not a good experience proactively notify you with automatic root cause identification what

21:44 is the reason why and in this journey just like you saw uh you know saw me showing you the full Network stack we

21:51 also leverage Telemetry from third-party systems and that again is because of the fact that we have a microservices cloud

21:57 architecture we can consume Telemetry from zoom and from teams it's a cloud to

22:03 Cloud integration we have built so that we can now very clearly identify if you had a bad Zoom or teams call was it

22:09 because of a client issue was it because of a network issue was it because of a circuit issue on your on your vanite or

22:15 was it because of a blip on the zoom and teams application themselves no more

22:20 blind spots end to endend visibility for a user and the applications that they're

22:26 leveraging for productivity with then aop stack like that we offer and again

22:32 this is across the board this is across Wireless this is across wired you know free connection post connection

22:37 experience minutes for the full stack and on the STD van side as well if you extend our aops platform to the St van

22:44 with our portfolio you're able to see again the connectivity the availability

22:51 and the performance of the user experience whether it's a client issue a

22:57 network issue or something beyond the network like a van link problem or an application Health being the reason why

23:04 a user is not having a good experience so no more blind spots no more finger

23:10 pointing a second guessing with an a op stack that gets the right Telemetry into

23:16 the right Cloud architecture you're able to get full visibility on the end user

23:21 experience but then comes the point of hey it's great that you know an aop stack can give me such visibility

23:29 how can I get notified proactively of the issues that are found in the network

23:35 or outside the network let me now introduce you to Marvis your virtual Network

23:41 assistant Marvis essentially is again driving a lot of day to benefits for our

23:49 customers it is helping simplify the operations of the network so not only do

23:55 we make the Day Z day one deployment of Networks really fast with with our apis and our

24:01 automation but when the rubber hits the road when it's all about you've deployed the network great job but now you just

24:08 start connecting right your portable MRI machines your portable x-ray machines your IV pumps are connecting to the your

24:14 network you're deploying more and more iot devices um you're giving more and

24:21 more client devices to your caregivers to again deliver a better patient

24:27 experience um as end users all of those need connectivity and that's why the

24:33 service Le expectation framework comes in to give you that visibility but when there are issues that is where Marvis

24:39 comes in and proactively will notify you will proactively create a ticket for you your ticketing system because again it's

24:44 all API based to let you know hey there is a bad cable on this particular switch

24:49 on this particular Port that is impacting these Downstream end users there is a missing VLAN often times a

24:56 ticket will come and saying hey I went to this part of the building and my voice call dropped the Network's not working

25:03 there's a roaming problem or a coverage problem often times in fact nine times out of 10 it turns out that there was a

25:10 misconfiguration and the voice VLAN was not configured on that Port where the AP

25:15 was plugged in so when a user roam to that AP the traffic was black hoold it

25:21 was not a coverage issue it was not a capacity issue it was not a roaming problem with either the network or the

25:27 client it simple thing as a configuration Miss but now those can be

25:33 proactively caught and identified automatically with the AIML stack that we have as part of our Marvis

25:39 Engine things like um DHCP things like DNS things like radius when clients are

25:46 not able to connect or they were able to connect initially but you know the DHCP lease was not renewed for some reason

25:53 and now the user who was happy previously is not able to get a good connection all of those can be proactively identified via Marvis

26:01 actions framework to let the network operators know hey you are having an issue on your network that's impacting

26:07 these users and this is the exact reason why and that allows you to again do two things first of all meantime to inance

26:13 you know exactly that it's not a network issue from a wireless wired or van perspective but more importantly it's

26:21 lowering the meantime to resolution so identifying that the users having a bad experience and telling you exactly where

26:27 that KN in the h stack is you can get the issue resolved is again where the key benefits of an aop stack like the

26:34 Juniper uh Miss platform comes into play

26:39 now the other key aspect is how do we see network operators interacting with

26:47 the network right CLI and dashboards are becoming a

26:54 thing of the past just like you interact with your Alexa or hey Google that's exactly the way we see operators

27:01 interacting with the network by a conversation assistant so we had a conv

27:07 assistant that we launched back in 2018 which was able to provide documentation search which is able to provide troubl

27:14 shooting capabilities for your network so troubleshooting an application and you'll see more of this in my demos

27:19 troubleshooting users all that is part of the Marvis conversational assistant

27:24 interface Journey what we've also done recently is put this on steroid steroids by integrating a large language model

27:32 where now we can give you even more comprehensive summarized information on

27:39 complex questions like Hey how do I set up a campus fabric hey I see the aped blinking Amber green what's going on hey

27:46 how do I set up a new network how do I set up a secure connectivity for my iot

27:51 devices coming onto the network and this is where the Marvis conversation interface is able to give you a very

27:57 comprehensive answer and also give you the documentation that is relevant to achieve those use cases leveraging

28:03 llm and it also helps in ticket deflection before you even have to open up a ticket via the Miss portal you can

28:10 now actually ask Marvis right away if you have a question to say hey Marvis help me with this issue I'm seeing and

28:15 Mars will be able to give you an answer as to exactly what you're seeing and also give you an FAQ uh Links of what

28:21 could be additional resources available for you to solve that problem

28:28 where we took Marvis next was leveraging continual user experience learning data

28:36 so I spoke to you about zoom in teams what we built there was essentially the

28:42 ability for our Cloud architecture to ingest user label data from the zoom and

28:48 teams cloud and very quickly be able to identify if you're having a good team call or a good zoom call or a bad team

28:56 call or Zoom call and most importantly if it's a bad team call we have now

29:01 recently launched a predictability and explainability model of why your

29:07 experience is good or bad so essentially we are taking user label data from the

29:12 zoom and teams Cloud we are merging that up with the network tele data we already

29:18 have for every wired Wireless client so we have the state machine we merge the application data and again it's an optin

29:25 you as a network administrator have the full Authority to um authorize this

29:31 information exchange if you authorize it with the zoom and team credentials that's when the data comes into

29:37 your tenant in the Juniper Miss Cloud platform and all privacy is maintained

29:43 it is all data is all anonymized but the key benefit here is now you know proactively first of all how many Zoom

29:50 or team calls are happening within your network how many of them were successful this is again where it it all goes back

29:57 to the user experience we're able to zoom in on the bad user minutes for a

30:02 collaboration application and not only that we are then able to tell you

30:07 exactly where the issue is what capabilities of the network or the client or even van were probably

30:16 impacting that Endor experience what's the strongest correlation and that's where the explainability aspect comes in

30:22 so apart from having a wireless service level expectation metric per user or a wired service level expectation per user

30:28 user or van link uh SLE and application Health SLE we are now announcing an

30:34 application experience SLE especially for collaboration apps which comes in

30:39 you know especially in the Life Sciences model with your Telly Health that we are seeing a lot of now um this is critical

30:46 because you want to know that the users connecting to the network are having the best experience possible and if not

30:52 again Network it should know in their fingertips why that is with this prediction model we're able to not only

30:58 explain a bad Zoom call by identifying it but more importantly as you're rolling out collaboration apps in your

31:05 network we're also able to predict what the application

31:10 experience would be for voice or video right and here is again a quick demonstration where we've pulled in zoom

31:17 in teams data from uh the zoom in teams Cloud instances for your accounts into

31:24 the Marvis framework and we are now able to very quickly and proactively identify

31:30 bad user minutes and what is the reason why those user minutes are bad I'll now move on to Marvis minis

31:38 right everything I spoke to you before was all about client Telemetry coming

31:44 from our Network where we're building the state machine but often times the question

31:50 comes hey what about the time when I'm rolling out a new location I'm creating this brand new building or this creating

31:57 this brand new campus I'm going to deploy the network how can the network

32:02 assure me that I will have the best application and end user experience

32:07 possible before even the first client connects to the network I will now introduce you to

32:13 Marvis minis Marvis minis is the industry's first digital twin for user

32:21 experience we are now able to give you complete visibility into what the user

32:28 experience will be when a user comes in to connect to the network before there are any users on the network themselves

32:36 so here what we have done is essentially created because of our microsources

32:42 Cloud architecture we've created a cloud native minis framework again imagine we

32:48 talked about Marvis actions we talked about Marvis convers interface now you have Marvis watching over the network

32:55 and making sure that the end user experience is the best possible even before the first user connects to the

33:01 network it's always watching Always monitoring and always validating that

33:07 the services will be available when the users log on to the network proactively and that's how we call it the industry's

33:13 first digital twin for user experience the Maris Min framework is available on

33:18 the wireless as well as the wired and we also recently announced U on the van side so again putting it end to end and

33:26 most importantly it's able to test the availability reachability of the Network

33:32 Services as well as your applications and also it's able to predict what the

33:38 experience would be going back to the user learning model I just spoke to you about where we're looking at the loss

33:46 latency Jitter on the van side we're looking at any authentication issues on the wired side we're looking at all the

33:53 V lines being available all the applications being available for for the end users before they even connect to

33:59 the network with this Marvis Min framework but again the key problem statement was when I have clients

34:06 connected to the network I already get the Telemetry I need to be able to tell you what the user experience is but as

34:12 you roll out new sites how do you know that you'll have the same experience that you're seeing on other locations

34:18 without any uses connecting and that's where the marus minis framework comes into play it's always on it's always

34:26 validating the the network experience for the end users even before any clients are there so again as I

34:33 mentioned earlier it's available for both Wireless and wired and we recently just announced at an event um that we

34:40 did in June on the vanite as well so here you can see whether it's DHCP whether it's ARP whether it's DNS

34:47 whether it's application availability whether it's authentication on the wired side whether it's the speed test on the

34:53 vanite we are enabling this all dynamically there are there's nothing that you have to do or set up Marv is

34:59 running in this for you in the background all the time to make sure that from a connectivity perspective

35:05 from an authentication perspective from an application performance perspective the network is always available to

35:12 deliver on the application experience that we need for the end users to have

35:19 the best experience possible when they connect to the network right so the key part again is dynamic in nature it's

35:25 always running and it's able to validate for you what theer experience would be

35:30 proactively before the is connect it also has a role to play from

35:35 a brown field perspective so apart from new deployments how do we make sure the Network's always available how do we

35:41 make sure the experience is not impacted when you make configuration changes right or if by some reason

35:47 misconfiguration happens how can we cat that proactively Marvis Min is the answer

35:52 it's constantly learning your network it's constantly baselining the network it's constantly testing for availability

35:59 of the critical Network Services and applications no additional Hardware no

36:04 separate platform it's all part of our Juniper M Stack the same access point portfolio that's delivering these

36:11 capabilities for you and when Maris minis find an issue again you don't have

36:16 to look at the dashboard or ask Marvis hey is that a problem Marvis will

36:21 proactively notify you as part of a marus actions framework hey I found an issue I'm seeing latency law from this

36:28 application please expl to the application team or I found a DCP issue or I'm seeing a loss on this particular

36:35 internet circuit that's coming into uh your hospital or or Healthcare campus so

36:42 that you can take the appropriate action with the right teams to mitigate minimize remediate the problem right

36:49 away now we talked a lot about user experiences but the other key aspect is

36:56 what about on boarding devices and here I'll pivot towards our missed access Assurance solution right today there are

37:03 existing Solutions in the industry that enable secure on boarding be with be it the guest access use case be it the BYOD

37:09 use case your iot devices coming online um or even your critical corporate

37:15 devices with certificates coming online but the architecture that's available today to support that is extremely

37:22 monolithic it's extremely brittle it's extremely complex what we did did again by virtue

37:29 of our microsources Cloud architecture we essentially shattered that complexity so now again leveraging the simple Cloud

37:39 microsources framework we have launched since last year and it is now in

37:44 production for the last one year and we've done we have multiple customers who are using this um it's all about

37:52 leveraging secure on boarding with our access assurance

37:58 microservice no more appliances on site no more real estate that you have to

38:03 worry about to manage your a huge cluster of appliances it's a simple configuration in the cloud and more

38:10 importantly it's completely integrated with the same client visibility that I spoke about before from a wireless wired

38:17 van perspective so what when now when you us are you want to enable the secure authentication be it via you know ppsk

38:25 or be it via 1X or be it just a guest access solution you are fully assured of

38:32 the same Cloud platform delivering those sources for you at scale with a single

38:38 click of a button all you do when you set up a wireless land network is say hey authentication services use misto or

38:45 from even from a wired perspective for 1X authentication all you do when you do the setup is as part of the wired

38:51 Assurance configuration for templates at scale just put the authentication Service as use M off and you create a

38:57 very simple policy framework and now everything is available to you not just

39:02 connectivity not just the experience of users when they're connecting to Applications but as Matt brought up

39:10 before security is obviously a big big focus and parameter you are now assured

39:15 of the right devices connecting to the network in the right way at the right time accessing the right resources and

39:24 if those users are having an issue the uh the by virtue of this being in the

39:30 same Cloud platform as an additional microservice you have full visibility into that pre connection experience as

39:36 well whether it's a a bad password or an expired password or an expired

39:41 certificate now you have the full visibility in the access Assurance

39:47 module of the Juniper Miss stack in the cloud platform of knowing hey first of all which users are accessing Water

39:53 Resources in a very simple framework like you see here and more important if they're having a bad experience is it

39:59 because of authentication problem and what exactly is the problem it's right there for you at your fingertips again

40:05 the right data the right architecture at the right time but how do we make it even easier again when you're

40:13 troubleshooting a user and issues come in you want to be able to empower your level one right today what happens when

40:20 any network ticket comes in it goes straight to level three and the level one team say y i acknowledge you have a

40:25 collaboration issue problem a voice video problem or authentic or you're not able to connect to the network let me escalate to the level three what we have

40:33 done with the AIML framework and that this is what you should expect of your aops platform is leveraging a conversal

40:39 interface be able to very quickly troubleshoot complex problems but very

40:44 simply so now your level one help desks is a lot more productive they're not escalating every issue up to level three

40:51 and they're able to solve problems right away when a ticket comes in to know exactly what the issue is especially

40:57 it's tied to whether it's connectivity user performance application experience like Zoom or teams or even from an

41:03 authentication perspective again no more guesswork no more blind spots end to

41:08 endend visibility last but not least if you talk if you remember what I you know how I started my conversation was it's

41:15 all about the visibility end to endend it's all about the a driven support with Marvis it's all about the Microsoft's

41:22 architecture that makes it all possible but it's also about what else can we do

41:28 to enable engaging experiences for patients and visitors for the clinicians

41:34 for the nurses for the caregivers to ensure you're getting the best possible experience from the network and this is

41:41 where indoor location services comes in again part of the same Cloud platform not an overlay solution not a siloed

41:48 solution and no more overlay networks required so this is something again that you can deploy at scale it's part of the

41:54 same wi-fi system leveraging a standards based Wi-Fi and Bluetooth low energy technology to deliver for you the best

42:02 experience possible this is where again we're able to deliver asset visibility use cases

42:09 working with our ecosystem Partners we're able to deliver uh wave finding use cases with our ecosystem Partners we

42:16 essentially become the platform standards based technology on Wi-Fi and blle with differentiation built in so

42:23 all of our Flagship performance APS have this directional Bluetooth antenna array built in and the reason that's important

42:30 is it because gives you higher accuracy when you're looking to find an asset in room um you should be able to find that

42:37 very easily without deploying a proprietary stack or a silo system that's exactly where the jiper Miss

42:45 platform comes into play when you deploy a network you want to be able to leverage location services

42:52 part of the network offering and do that the day you deploy a network and that is

42:57 where again an AI op stack comes into play We leverage unsupervised machine

43:03 learning as part of our system to give you the best location services possible with the highest accuracy that

43:11 ble can provide converging with Wi-Fi last but not least all of this

43:19 also is available to you why what we' have done with integrating with a service now platform so the the

43:26 underlying fact for client visibility AI driven support um Microsoft cloud architecture

43:33 digital experiences also is all based on the entire platform being 100% API first

43:39 these apis help us integrating with partners for enabling the location services use cases these apis also help

43:46 from a network it perspective deploying the network and operating the network so every Mar action you saw can now be

43:53 leveraged as an auto ticket opening up in the now platform so if you have

43:58 service now as your key platform for it operation management this is where you

44:04 can Leverage The Integrations we already have for speeding up your deployments

44:10 with enabling the workflows wire service now interacting with our apis or even from a day two perspective leveraging

44:16 the service graph connector application we have built to deliver simplified day

44:21 to operations and make sure that these are part of your workflows that your it teams are already used to by leveraging

44:28 the best of breed of solutions with the aops combining that with the service now

44:35 solution and last but not least as part of our Enterprise uh blueprint we also

44:40 recently announced the ability for Marvis to now get information even from

44:46 anomal seen in the data center so for our abstra Control Data Centers Abri are

44:51 intent based networking solution for the data center we have now been able to

44:57 also build a full end to end view where if you have application sitting in the

45:02 data center that are having issues because of data center problems how can we very quickly from an endtoend user

45:09 perspective from the client to Cloud client to application give you that full view of if there's a problem if it's not

45:16 my wireless not my wired not my SD van but it's a data center how can your

45:22 Hospital campus Network operators know within the click of a button exactly where the problem is so the first thing

45:27 they get to now know is it's a data center problem secondly they can now enable Mars for the for the data center

45:32 and know exactly what the problem in the data center is that could be impacting Downstream users like your clinicians

45:38 like your nurses or even patients accessing applications and again getting to the view of what is my Ender

45:44 experience if it's bad why is it bad so proactively letting you know exactly what the problem is by pulling in data

45:51 center anomalies and Telemetry as well into a Mars framework engine so just to summarize all of that the zoom in themes

45:58 integration the integration with Z devices to full Telemetry to give you the full view of what's Happening how

46:03 does a client see the network how does a network to the client giving you a view of what the service level experience is

46:09 for every user wide or Wireless um the ability for us to securely onboard users

46:16 the right way at the right time with access to the right resources to ensure that your security postures maintained end to end the ability for us to deliver

46:23 indoor location services with our ecosystem Partners to make the are the possible come to life around asset visibility around wave finding around

46:30 push notifications and the ability for us to put an information even from now a

46:36 juniper AppStar data center into the Campus View so you know if an end user

46:41 impact is happening is it because of issues beyond your campus Network all of that is possible viable again because of

46:49 our foundation in an API based Microsoft architecture that is what allows us to

46:55 enable these services and with the agility that has not been seen in the industry so far but end of the day that

47:03 microservices architecture is what truly delivers the benefits leveraging aops

47:08 leveraging AIML AIML is not the end goal the goal is how have we been able to

47:15 leverage a IML to deliver iops to again deliver the best user experience

47:21 possible on the network as your devices connect on the network and continue to

47:26 use a network for the day-to-day services and with that Matt back over to you thanks unini I think everybody's

47:33 head is spinning so time for me to to bring us home so quick glance for those of you that may or may not know who we

47:39 serve right so standing behind our 5.5 billion in annual revenue you'll few see a few of segments that that are

47:45 mentioned here in particular uh based on what you've heard over the past half hour a couple of interesting facts so

47:51 we're the fastest growing Wi-Fi vendor in the market our campus business which soonly address very very nicely so think

47:58 wired and wireless it's the largest it's the fastest growing unit within the company we see uh rapid adoption across

48:04 all different Industries which you see listed right here including Healthcare where we've been growing at a double- digit clip annually so very very healthy

48:10 business pun intended and uh you know to gives you a little bit of an idea and a little bit of a peak on who we serve

48:17 right from a customer perspective next slide so uh what some of our customers

48:23 say about us just at a very very high level from radi children to AA Health to Island Health you'll start to see some

48:29 of the kpis that really kind of get extracted as soon said uptime you know typically is you know not good enough

48:35 anymore and slas and the metrics that are around Network up time are oftentimes obviously what we capture but

48:42 now we start to see really where AI where some of the simplistic nature of what we built in around automation can

48:49 be captured from a kpi perspective and the differences that can be made within these types of environments R Children's

48:55 Hospital perfect example deploying over 900 APS less than 6 weeks uh ztp Cloud

49:02 single click activation function and features right allow them to do this uh the important part here too Is Not only

49:08 was it fast but there was quality behind it so no no disruption zero trouble tickets have never experienced anything

49:13 like that before a direct quote that came from uh the chief technology officer uh to AA Health where now

49:20 because they've moved off of a controller based architecture to a more modern microservices Cloud architecture

49:26 they're saving over $1,400 a year not taking down and bringing back up those controllers right that have been a pain

49:31 point for a decade Plus in their environment uh which was equivalent to about 70% of an FTE to then Island

49:38 Health who's talked about basically allowing Marvis and allowing the technology to really inspect their

49:44 environment and seeing a dramatic drop so 90% drop in user generated trouble

49:50 tickets so just a few examples that are that are there for you all the next slide um Partners customers

49:58 prospects they put a lot of stock into the words of Industry analy so it' be remiss of me excuse me not to uh to

50:04 share this particular information on the le- hand side wir and wireless land magic quadrant it's a third year in a

50:10 row that we're in the very very top spot additionally we're also a leader in the indoor location services which is on the

50:15 right you're going to see that we are the only networking vendor that's up in that upper right hand quadrant and again

50:21 this is primarily due to again what I'll call is the Swiss army knife uh AP approach where we embed virtual

50:27 Bluetooth low energy we derive those location based services that sun Alini just talked about directly out of the

50:33 access points and then the next slide is one important item of note here I wanted to

50:40 put this in so the Gartner critical capabilities report some people pay attention to this um some people don't

50:46 know that it's available so I wanted to make sure that everybody was aware of this this one is for wir and wireless land you'll notice that Juniper achieved

50:53 the highest uh scores out of all vendors and all five out of five use cases uh

50:59 we're super proud of this accomplishment and honestly you know what this comes down to is really thinking our customers

51:05 uh especially for the feedback right that goes into these and driving the results out and so I'll wrap by just thanking

51:12 each and every one of you for joining us I hope the content was of value I know it was a lot of information uh please

51:18 reach out if we can be of assistance and we'd love to be part of your journey so all the best and thank you for for

51:25 attending thank you