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MAX KAMENETSKY: Hi, and welcome to the Google Cloud and Nokia
series on the cloudification of telecom provider networks.
Why now and how?
I'm Max Kamenetsky, group product manager
of Cloud Networking at Google Cloud.
JITIN BHANDARI: I am Jitin Bhandari,
chief technology officer for cloud and network
services at Nokia.
MAX KAMENETSKY: Jitin, in a prior conversation,
we talked about some of the consideration of what
it means to be cloud-native.
Maybe at this point we should talk in a little bit
more detail as to some of the design
and architectures for telecom workloads.
So specifically, there's Kubernetes.
There are a number of open-source technologies
that can reside on top of it.
How do we put all of this together
to enable high performance telecom workloads to function?
JITIN BHANDARI: What this time around the standards bodies
and the technology forums of 5G has done
is, fundamentally they have shifted the design
and principles to be more what I call network function
defragmentation.
Take the case of subscriber data management.
This time around, it's just not the subscriber data management
for your data and voice application,
but it's the subscriber data for end all, be all.
And if you look at the design and architectures,
it's been broken down into notification engines,
subscription engine, the backend.
The frontend is segregated from the backend.
The frontend can handle interfaces
like legacy interfaces, like LDAP,
and can take future interfaces, like HTTP,
and scale independently.
Take case in point the control user plane segregation
topic we keep talking about, both in the data space,
where workloads and application needs to segregate itself.
And you need to design architectures and principles
where the control plane is scaling at a different level
and the user plane can take those maximum line rate
performance all the way to one terabytes per second.
So if you look at it, the beautiful aspect of standards
this time around-- and it's evolving really fast--
is that they are promoting for that design and architecture
that goes for scale, that goes for reuse,
and that goes for microservices pieces.
But to your point, one thing that
always comes near and dear to our telco applications
is network acceleration.
So why don't you share some views about--
the scalers in the fintech industries and other parts
of the sector, how did you combat the hunger for bandwidth
for applications and then for network acceleration?
MAX KAMENETSKY: Oh, what a great question.
What's actually happening here is,
when you look at high performance
workloads, especially workloads that
need to reside at the edge, one of the great things that's
been happening in the industry is
we now have this separation of hardware and software.
No longer do you have these monolithic appliances
that you had in the past.
But when you do that, how can you actually
get the performance out of the hardware that you need?
And in fact out of the entire solution?
You need to have technologies that enable your application,
as an example, to communicate directly with the network
interface card, bypassing the kernel,
so you are able to process packets at the maximum rate
that that card permits you to do.
Or as another example, you need to have technologies
for processor affinity or memory access that really make
sure that the CPU or the memory are not the bottlenecks
overall in your architecture.
So ultimately, you are getting the value out of the investment
that you made.
Similar things can be said about the hypervisor.
At this point, a hypervisor is actually
a performance detractor, as opposed to a benefit.
So you need to look at technologies that enable
you to run on bare metal.
Again, it's all about, how do you make sure
that those workloads at the edge with the minimum latency,
with the highest performance, are actually
achieving what you need?
JITIN BHANDARI: Well, that's a fantastic point, actually.
We're just coming from the virtualization era ourselves,
and a lot of workloads are being deployed out there
on virtual platforms.
And one of the beautiful things we see very quickly when
we walk away from hypervisors theory
and go into bare metal, A, the acceleration
technologies and toolkits is becoming
richer and richer out there.
We know about data plane development kits.
We know about how we are doing acceleration and high packet
throughrate at line rate, especially
for applications which are data plane-sensitive.
And one thing we are seeing is there
will be slow migrations of workloads from virtual network
functions to Container Network Functions,
or what we call CNFs.
And then during these migrations,
it's just not about the ability of a workload
to perform, but also to manage, operate.
I'm talking about the lifecycle management of it.
And this is one piece which has got two layers of complexity
or challenges, if I may say.
One is, A, this time around, when we introduce workloads
into container applications, how do we
make sure the promise of lifecycle management
really holds true?
You're talking about upgradability, updatability,
heal and scale of applications.
So that's one challenge.
The second challenge is that we are actively thinking about,
there will a co-location of workloads
of both virtual functions and container functions.
How do you design lifecycle management that
handles both aspects of it?
MAX KAMENETSKY: Oh, what a question.
There's a couple things that I'd like to say about this.
The first is that you are completely right.
I would love to live in a world where all the workloads were
containerized today.
Unfortunately, that is not the case.
And I do believe they will be containerized over time,
but that will take a little bit of time.
Unfortunately, also what is happening today
is not sustainable.
Where you have infrastructure that
is dedicated to virtualized workloads
and separate infrastructure that's
dedicated to containerized workloads--
creates tremendous complexity, doesn't permit you to scale,
create stovepipes.
This is not what you want to have.
You want to have a single set of managed infrastructure,
Kubernetes running on top of that,
and the ability to seamlessly place
either virtualized workloads or containerized workloads,
and to orchestrate all of that.
So how do you do this?
One key piece to this is Anthos, because what we've found
is that many customers were running
not just separate virtualized and containerized sets
of infrastructure, but they were running it
across private data centers, across public clouds,
across the edge.
So now you have all these different sets
of tooling that you need to be aware of, that you need
to maintain, and your life then is focused on the tooling,
as opposed to the business applications
that you want to have, which are really deriving value
to your enterprise.
We strongly believe that when you
have a coherent, cohesive platform that
gives you lifecycle management, security, operations,
configuration, policy, and removes all that from you
having to manage that, you're then
free to focus on the things you do need to focus on.
JITIN BHANDARI: No, that's actually a very valid point,
because a large part of the discussion around 5G
is about value creation, which ties up
to the concepts of slicing, which ties up
to the concepts of creation of a service or a service intent
network.
And you're spot on.
So if you take what you're talking about, the platform
ability to lifecycle manage your application,
and then you take the chaining of the application
to creation of a service, and eventually creating
to a service intent network in a hierarchical order,
is actually the nirvana state for all of us.
So we are moving largely into a software world.
And we are saying that the networks aspects, the radio
aspects, the platforms aspects, the operations-- everything
is going to be software.
And we are talking about a huge landscape of software that are
being rolled into the network.
And Nokia started its software journey many years back.
And one thing we have been successful being able to do
is how do we evolve the transitions
of continuous integration and continuous deliveries in 4,
8, 12-weeks timelines?
As we provide very cohesive software applications,
every release over release is enriched
on more features and functionality,
but also be the capability of this continuous delivery
to our network operators.
Because when you go to the operators arena,
you're just not talking about introducing a new feature,
but also a new use case.
And how do you validate that new use case
from a network's perspective, not just from an application's
perspective?
So the challenge of today's telco networks
is, as you consume that new feature set
for that ultimate use case, how is that continuous delivery
pipeline being delivered?
And this is a new concept for telcos.
I must say, I would like to know your views of,
how is continuous delivery and integrations happening out
there in the platforms of GCP with other workloads?
MAX KAMENETSKY: Jitin, it's interesting
that you mentioned 4, 8, 12-week timelines, because when
you think about the word continuous delivery,
it actually calls for continuous delivery.
So how do we get there?
One thing to talk about is a change of mindset.
Rather than having very large upgrades that
happen infrequently, we should be
thinking about small upgrades that happen frequently,
because with small upgrades the changes are, by definition,
smaller, more incremental.
It's also easier to roll them back.
Another benefit of small upgrades
is that you're continuously delivering
that value of the new features to your users.
Now the good news is that there are principles and methods that
already exist for this.
Technologies, such as site reliability engineering,
which fundamentally change how your operations teams are
structured and how they think about the work
that they're doing, or automated testing and deployment
tools that really enable you to have this kind
of continuous innovation cycle.
Or whether some of the technologies that we've
actually introduced in Anthos, such as the Anthos service
mesh, which enables you very easily
to have a canary type of deployment,
where as you start deploying a microservice,
you first put it into a staging environment.
And then you can gradually start populating this
into your production environment.
If anything goes bad, there's an easy rollback path.
Otherwise, you deploy it into your entire environment.
JITIN BHANDARI: Oh, that's actually phenomenal.
You're using some words like canary testing.
And we at Nokia have been thinking
quite a bit about this for the last 12 months of our journey
as we are accelerating.
And the beautiful thing is, Max, and it so resonates,
because of our services experience and ability
to operate and manage telco workloads,
one thing that we are really, really looking at-- and this is
going to be fun to co-create with Google--
is around test automation frameworks.
And how do we create the concepts of digital twins,
as well?
So absolutely, this is one concept that has to come
to mainstream and requires some real cool innovations from both
chapters-- the telcos and the web scalers--
for sure here.
MAX KAMENETSKY: Jitin, thank you very much for this conversation
today.
Thanks for catching our discussion
on the cloudification of telco networks.
We'll see you next time in the cloud.
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