Applying Cloud Principles to Transforming Metro Networks
Know your options: Juniper Cloud Metro networking
With expanded security threats, talent shortages, and new ITU standards for reducing carbon emissions, cloud operators must be prepared to adapt. Watch for an in-depth look at your possibilities for implementing and simplifying network deployment and operations—despite the high complexity involved.
You’ll learn
How foundational Cloud Metro concepts, such as AI-driven closed-loop automation, can blend with existing metro architectures
Ways to create highly scalable, sustainable, and converged multiservice architecture that enables both users and operators to thrive
Who is this for?
Host
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Transcript
Introduction
0:03 hi everybody and welcome to our Cloud
0:07 Metro session now and uh probably going
0:09 to talk about a little boring thing old
0:11 school networking no more applications
0:13 and services but though those networking
0:16 are pretty much driven by requirements
0:19 which are coming from those new class of
0:22 applications and yeah I'll try to stick
0:24 with the with the title of this
0:27 presentation we'll talk about the cloud
0:28 principles which can be applied to the
0:31 metro to transform it which is
0:33 um under pressure of those 5G
0:37 Razer 5G and actually
0:40 um the influence of
0:42 different types of new class of
0:44 applications and content which are
0:46 placed in the
0:47 locations in the matter where it never
0:49 have been before and
Cloud Principles
0:53 in general that requires to transform
0:56 the traditional Metro where it is just a
0:58 maybe dump pipe
1:00 created in the first place to transfer
1:03 traffic north south so into something
1:05 more sophisticated more organism which
1:08 allow us to serve more complex traffic
1:11 Partners importantly sustain the huge
1:14 traffic growth which is uh
1:18 um driven by the 5G to large extent and
1:21 also which is another important thing to
1:23 connect applications or maybe okay we
1:26 can have Services which provide
1:27 applications at any literally location
1:30 of those Metro infrastructure so that's
1:33 one Trend the second trend is actually
1:35 virtualization of the network functions
1:39 of the
1:41 transport infrastructure itself of the
1:43 network itself and this is uh something
1:45 we see that happening all across the
1:47 place and 5G is the brilliant example
1:50 with all the virtualized she used to use
1:53 virtualized evolve packet core which in
1:56 the context of the x-hole will be placed
1:58 all across the network from access to
2:00 the more Central Central locations and
2:03 in fact it happening in other places uh
2:06 cable is another example so those guys
2:09 are trying to digitize their R5 function
2:12 also virtualize cmts
2:15 traditional Broadband aggregation so
2:18 that's where the former monolithic BNG
2:22 transforms slowly towards the newer caps
2:25 models with disaggregated BNG control
2:28 and BNG
2:31 um data plane right and now we can take
2:33 it and drop it in any place of the
2:35 matter at least that's the that's the
2:37 intent
2:38 and
2:40 um
2:41 the point here that many of those
2:43 virtual functions already now coming in
2:46 the form of the cloud native
2:47 applications and of course they're
2:49 coming with the with the thought behind
2:52 that okay so we can move them freely and
2:54 orchestrate them as flexible as we do
2:56 orchestration of the services and
2:58 applications in the cloud and even so
3:00 where are we moving application from One
3:02 Cloud to another
3:04 around and and if we think about the why
3:08 the concept works so well for the cloud
3:10 is it's pretty much for the fact that
3:13 the cloud is based on the very well
3:15 thought
3:16 um data center fabric whereas well
3:19 separation between the undelay and
3:21 overlay tunneling which in its turn
3:24 based on the closed-like topology which
3:26 is relatively simple or at least well
3:27 understood right and that's what creates
3:30 the foundation for freely moving those
3:33 applications all across my
3:35 infrastructure so the first concept
3:38 which we can actually Implement for the
3:40 Metro is about this converting the
3:43 highly segmented and solid Metra
3:47 infrastructures towards the end-to-end
3:50 IP service fabric right so here we
3:53 probably not talking about the
3:55 converging the metro into gigantic close
3:59 topology so the material will have still
4:02 lots of inertia and there's some
4:05 economical reasons why all types of
4:08 topology will be will contain to stay in
4:11 mattress or rings partial mesh Etc but
4:14 the key building block of the mattress
4:16 of the routing system
4:18 which independently or what size
4:21 in an amount of terabytes it's it's
4:24 capable to uh to put through it so it
4:28 should provide the same set of
4:29 networking capabilities which allows to
4:32 enable the function of the
4:36 IP service Fabric in any at any location
Example
4:40 and if we double click on probably on
4:44 more or less common example of how the
4:47 metro metro Network looks like for the
4:50 service provider so we see this kind of
4:53 layers access aggregation Metro services
4:56 and services on the top so there's a
4:59 multi-service edge of the talk with
5:01 access which interconnects our terminals
5:04 that might be cell towers business
5:07 customers some residential customers and
5:10 at the very top that's where the Metro
5:12 means the other part of the network
5:14 infrastructure of the service provider
5:16 would be when internet public and
5:18 essentially Telco Cloud so that's that's
5:21 the type of network which we can see
5:24 today and the transformation
5:27 would happen with the first step on
5:29 Telco Cloud moves closer to the to the
5:33 access right so with that we're also
5:36 transforming
5:37 the aggregation layering to something we
5:40 call the lean Edge so the lean Edge
5:42 function will be provide all the same L2
5:45 L3 vpns which we know for now so it will
5:49 enable immediately the East-West traffic
5:51 pardons it will enable the low latency
5:54 Services the application can be placed
5:56 on this Telco Cloud infrastructure
6:00 with respect to the existed multi-store
6:02 research we believe it it stays where it
6:05 is for quite some time it allows a
6:08 smooth transformation from the older to
6:10 the new network architectures
6:12 and it will serve for some Corner cases
6:15 where we need to teach some VPN Services
6:18 which are not or not stitchable just
6:21 with the use of the lean Edge platform
6:23 because lean Edge is a lineage so it
6:25 still comes with some restrictions right
6:27 and on the next step what will happen is
6:30 just we'll need to scale out the Telco
6:32 Cloud infrastructure by placing more
6:35 applications by terminating more traffic
6:37 streams at this location
6:39 and also to scale to scale the part of
6:44 the aggregation Network and here as a
6:46 matter of fact we'll see the Rays of the
6:48 type of a close approaches because they
6:51 say scale out approach is very much
6:54 applicable for this for this one but
6:56 still will be restricted by the by the
6:59 location of a particular Central officer
7:01 or maybe a point of presence in the
7:03 network
7:04 and the very last step
7:06 is moving the compute Edge to the very
7:09 down in the axis right and and here we
7:12 see a couple of interesting applications
7:14 specifically coming from the area of the
7:17 5G networking and specifically a
7:20 virtualization of the salesite router
7:23 function of the network infrastructure
7:25 itself and placing it to the compute
7:27 node sitting next to the next to the vdu
7:30 for example so we believe there are
7:32 really advantages from the toll cost of
7:35 ownership in some dense 5G 5G
7:41 uh
7:42 deployments
7:44 and
7:45 the statement here is
7:49 we can see that the Metro meets the
7:51 element of the Telco Cloud practically
7:53 in every point of this network
7:54 infrastructure and here what what where
7:56 are we talking about that the Metro
7:59 becomes the new service edge of the
8:01 service provider Network
8:04 and so far so good so we've built our IP
8:08 service fabric uh the only the only
8:11 drawback of this thing is the relatively
8:13 High complexity of the network which we
8:15 facing over here it is higher than what
8:18 we would expect some simplification of
8:21 this of this designs will come through
8:23 decreasing amount of protocols so we're
8:26 migrating towards the sar from mpls and
8:28 then to this rv6 there will be some
8:31 hierarchical designs which also simplify
8:33 the implementation and troubleshooting
8:35 of this network infrastructure but
8:38 another thing which I want to talk here
8:40 which relates to this enabling
8:42 simplification is actually the network
8:43 slicing is the another concept which
8:46 we're proposing within the cloud Metra
8:49 vision
8:50 and probably in the 5G world the network
8:53 slicing raises relatively naturally so
8:56 for example there is a case we need to
8:58 stitch the 3gpp slices to the slices and
9:00 network infrastructure in the broader in
9:03 the broader use cases may not so obvious
9:06 but if we take some retrospective view
9:09 back into the some dark times when the
9:12 operator may may
9:14 be in possession of the multiple
9:17 physical infrastructure one
9:19 infrastructure to use to provide some
9:21 particular use case a particular type of
9:23 connectivity so this thing
9:26 used to be
9:28 simple but very costly and at those
9:31 times the industry passed through
9:33 transformation towards the single single
9:36 physical infrastructure which where the
9:38 old type of connectivity Converge on top
9:41 of the same packet switch Network and
9:43 well that's pretty much the stage where
9:45 we are right now so the total cost of
9:47 ownership or the the high total
9:49 consumption problem have been solved but
9:52 that's where the complexity uh was
9:55 introduced and from this perspective
9:57 they're introducing
9:59 the set of abstract layers might be a
10:03 very natural natural step
10:06 to be implemented to be implemented
10:08 deployed in the network so it preserves
10:10 the all the concept of of having this
10:12 single physical infrastructure uh with
10:16 the virtualized layers of networking
10:19 which also introduces the ability in a
10:22 simple weight or in a simpler way to
10:25 provide a differentiated class of
10:26 service to different types of traffic
10:29 flows and traffic flows belongs to the
10:31 engineerative by different applications
10:32 of course right
10:35 so this is about the network slicing and
10:39 we need to jump to the automation
10:41 and actually the network slicing by
10:43 itself is not the feature or function of
10:45 the transport infrastructure only and
10:47 it's probably not possible to deploy it
10:50 without
10:52 the automation complex and here we
10:55 prefer to talk about the closed loop
10:57 automation which is another another
11:00 principle inherited heavily from from
11:03 the cloud networking right which in most
11:06 cases are highly automated who automated
11:08 is a different question actually so for
11:12 now we're able to demonstrate very
11:13 practical examples of closed loop
11:16 automation which is based on collecting
11:18 and analyzing data from the from the
11:21 network comes which comes from the whole
11:22 different source and then Loop it back
11:25 through the actions of changing some
11:26 traffic engineering policies like in
11:28 this example but um
11:31 maybe the the actual the actual value of
11:36 this closed loop automation concept will
11:39 come when we introduce also as a I
11:44 algorithm as working as part of those
11:46 closed loop automation story right and
11:49 the whole Loop starts with the
11:51 provisioning or intent based
11:53 provisioning which is just the beginning
11:55 the real value is actually of AI comes
11:58 as per our opinion when it comes to
12:00 troubleshooting right so the formula for
12:04 the future networking in this concept
12:06 has continuously measure the user
12:09 experience continuously measure the
12:11 network service quality through the
12:13 embedded service Assurance mechanism and
12:16 compare it with the other patterns and
12:20 anomalies which the EI can derive
12:23 through analyzing of big data and
12:25 finally come up with the recommendations
12:27 about the root cause problem yes and
12:31 we believe that it will happen a way
12:34 faster than in certain cases we have to
12:37 spend on troubleshoot our networks as of
12:40 today and that would be the true and
12:42 very powerful step towards the as a more
12:44 sustainable operations in this space
12:48 all in all this is part of the concept
12:51 and part of the vision for this uh
12:53 metric Cloud Metro
12:56 um all in all we are pretty much in the
13:00 stage of the honeymoon with the eye
13:02 when the world is Rosy and everything is
13:05 possible at some point in time we
13:07 probably will see how the closed loop
13:09 automation will try to will allow to fix
13:12 us directly the problem in the network
13:15 but
13:16 yeah we'll see so the AI is powerful in
13:19 fixing things as creating harmful to
13:21 your network definitely uh but
13:24 definitely we can level we can leverage
13:26 for it's for some analysis in the
13:29 network sorry
Conclusion
13:31 okay and just the last slide to conclude
13:36 on
13:37 um a little bit expanding the concept of
13:40 the cloud Mentor Vision uh Beyond only
13:43 those Concepts which can be inherited
13:45 from the cloud so it comes to us to
13:47 three major areas operations systems and
13:51 architecture automated and programmable
13:54 operations and they P service fabric as
13:56 I said were inherited from the cloud and
13:58 when it comes to the systems or routing
14:00 system which actually consists you the
14:02 network so that's obviously one of the
14:05 most important component here and to
14:08 transform to the newer Metra infra with
14:12 new and new set of platforms which are
14:14 cost optimized which are feature Rich
14:15 which are power optimized and which can
14:19 sustain the traffic growth in this
14:21 segment of the network for a very very
14:23 long time so the longevity all those new
14:25 platforms being placed in the network
14:27 should spend up to the 7 on 12 years
14:30 according our idea and this is way
14:33 higher than what we saw in the past in
14:35 the same segment
14:37 and probably once again to repeat the
14:41 the major goals here for this Cloud
14:45 Mentor is to implement and simplify the
14:49 network deployment and network
14:50 operations because the level of
14:52 complexity is really really high and
14:54 that's something that will allow us to
14:56 enable new types of a better experience
14:59 for two major stakeholders in this
15:02 picture which is the end user and
15:04 service provider
15:06 for sure and just by the way since their
15:09 sustainability goes as a red line
15:12 through the through the all they all the
15:15 event I should say that the steps in
15:18 this diagram represent the
15:21 every one step brings you closer to the
15:25 uh to the cloud matter and also
15:27 contributes in into one
15:30 into one aspect of the sustainable
15:32 operational sustainable sustainable
15:34 Network which would be either a business
15:36 growth or people or trying to build a
15:40 more Greener company or more Korean
15:42 Network
15:44 so all in all
15:45 this is everything I have for for you
15:48 today
15:49 thank you very much great attention
15:56 [Music]