Telcos should focus on "connected data"​ not just "edge computing"​

Note: A version of this article first appeared as a guest blog post written for Cloudera, linked to a webinar presentation on May 4, 2022. See the sign-up link in the comments. This version has minor changes to fit the tone & audience of this newsletter, and tie in with previous themes. This version is also published on my LinkedIn newsletter with a comments thread (here).

Telcos and other CSPs are rethinking their approach to enterprise services in the era of advanced wireless connectivity - including their 5G, fibre and Software-Defined Wide Area Network (SD-WAN) portfolios. 

Many consumer-centric operators are developing propositions for “verticals”, often combining on-site or campus mobile networks with edge computing, plus deeper solutions for specific industries or horizontal applications. Part of this involves helping enterprises deal with their data and overall cloud connectivity as well as local networks. (The original MNO vision of delivering enterprise networks as "5G network slices" partitioned from their national infrastructure has taken a back seat. There is more interest currently in the creation of dedicated on-premise private 5G networks, via telcos' enterprise or integrator units).

At the same time, telecom operators are also becoming more data- and cloud-centric themselves. They are using disaggregated systems such as Open RAN and cloud-native 5G cores, plus distributed compute and data, for their own requirements. This is aimed at running their networks more efficiently, and dealing with customers and operations more flexibly. There are both public and private cloud approaches to this, with hyperscalers like Amazon and disruptors such as Rakuten Symphony and Totogi promising revolutions in future.

As I've said for some time, “The first industry that 5G will transform is the telecom industry itself.”

This poses both opportunities and challenges. Telcos’ internal data and cloud needs may not mirror their corporate customers’ strategies and timing perfectly, especially given the diverse connectivity landscape.

If operators truly want to blend their own transformation journey with that of their customers, what is needed is a much broader view of the “networked cloud” and "distributed data", not just the “telco cloud” or "telco edge" that many like to discuss.

Networked data and cloud are not just “edge computing”

Telecom operators’ discussions around edge/cloud have gone in two separate directions in recent years:

• External edge computing: The desire by MNOs to deploy in-network edge nodes for end-user applications such as V2X, IoT control, smart city functions, low-latency cloud gaming, or enterprise private networks. Often called “MEC” (mobile edge computing), this spans both in-house edge solutions and a variety of collaborations with hyperscalers such as Azure, Google Cloud Platform, and Amazon Web Services.
• Internal: The use of cloud platforms for telcos’ own infrastructure and systems, especially for cloud-native cores, flexible billing, and operational support systems (BSS/OSS), plus new open and virtualised RAN technology for disaggregated 4G/5G deployments. Some functions need to be deployed at the edge of the network (such as 5G DUs and UPF cores), while others can be more centralised.

Of these two trends, the latter has seen more real-world utilisation. It is linked to solving clear and immediate problems for the CSPs themselves.

Many operators are working with public and private clouds for their operational needs—running networks, managing subscriber data and experience, and enabling more automation and control. While there are raging debates about “openness” vs. outsourcing to hyperscalers, the underlying story—cloudification of telcos’ networks and IT estates—is consistent and accelerating. The timing constraints of radio signal processing in Open RAN, and the desire to manage ultra-low latency 5G “slices” in future 3GPP releases are examples that need edge compute. There may also be roles for edge billing/charging, and various security functions.

In contrast, telcos' customer-facing cloud, edge and data offers have been much slower to emerge. The focus and hype about MEC has meant operators’ emphasis has been on deploying “mini data centres” deep in their networks—at cell towers or aggregation sites, or fixed-operators’ existing central office locations. Discussion has centred on “low latency” applications as the key differentiator for CSP-enabled 5G edge. The focus has also been centred on compute rather than data storage and analysis. Few telcos have given much consideration to "data at rest" rather than "data in motion" - but both are important for developers.

This has meant a disconnect between the original MEC concept and the real needs of enterprises and developers. In reality, enterprises need their data and compute to occur in multiple locations, and to be used across multiple time frames—from real time closed-loop actions, to analysis of long-term archived data. It may also span multiple clouds—as well as on-premise and on-device capabilities beyond the network itself.

What is needed is a more holistic sense of “networked cloud” to tie these diverse data storage and processing needs together, along with documentation of connectivity and the physical source and path of data transmission.

Potentially there are some real sources of telco differentiation here - as opposed to some of the more fanciful MEC visions, which are more realistically MNOs just acting as channel partners for AWS Outposts and Azure's equivalent Private MEC.

An example of the “networked cloud”

Consider an example: video cameras for a smart city. There are numerous applications, ranging from public transit and congestion control, to security and law enforcement, identification of free parking spots, road toll enforcement, or analysing footfall trends for retailers and urban planners. In some places, cameras have been used to monitor social-distancing or mask-wearing during the pandemic. The applications vary widely in terms of immediacy, privacy issues, use of historical data, or the need for correlation between multiple cameras. 

CSPs have numerous potential roles here, both for underlying connectivity and the higher-value services and applications.

But there may be a large gap between when “compute” occurs, compared to when data is collected and how it is stored. Short-term image data storage and real-time analysis might be performed on the cameras themselves, an in-network MEC node, or at a large data centre, perhaps with external AI resources or combined with other data sets. Longer-term data for trend analysis or historic access to event footage could be archived either in a city-specific facility or in hyperscale sites.

(I wrote a long article about Edge AI and analytics last year - see here)

For some applications, there will need to be strong proofs of security and data custody, especially if there are evidentiary requirements for law enforcement. That may extend to knowing (and controlling) the specific paths across which data transits, how it is stored, and the privacy and tamper-resistance compliance mechanisms employed.

Similar situations—with both opportunities and challenges—exist in verticals from vehicle-to-everything to healthcare to education to financial services and manufacturing. CSPs could become involved in the “networked cloud” and data-management across these areas—but they need to look beyond narrow views of edge-compute. Telcos are far from being the only contenders to run these types of services, but some operators are taking it seriously - Singtel offers video analytics for retail stores, for instance.

Location-specific data

As a result, the next couple of years may see something of a shift in telcos’ discussions and ambitions around enterprise data. There will be huge opportunities emerging around enterprise data’s chain-of-custody and audit trails—not only defining where processing takes place, but also where and how data is stored, when it is transmitted, and the paths it takes across the network(s) and cloud(s).

(A theme for another newsletter article or LI post is on enterprises' growing compliance headaches for data transit - especially for international networks. There may be cybersecurity risks or sanctions restrictions on transit through some countries or intermediary networks, for instance. Some corporations are even getting direct access into Internet exchanges and peering-points for greater control).

In some cases, CSPs will take a lead role here, especially where they own and control the endpoints and applications involved. Then they can better coordinate the compute and data-storage resources. In other cases, they will play supporting roles to others that have true end-to-end visibility. There will need to be bi-directional APIs—essentially, telcos become both importers and exporters of data and connectivity. This is especially true in the mobile and 5G domain, where there will inevitably be connectivity “borders” that data will need to transit. (A recent post on the need for telcos to take on both lead and support roles is here)

There may be particular advantages for location-specific data collected or managed by operators. For example, weather sensors co-located with mobile towers could provide useful situational awareness both for the telco’s own operational purposes as well as to enterprise or public-sector customers, such as smart city authorities or agricultural groups. 

Telcos also have a variety of end-device fleets that they directly own, or could offer as a managed service—for instance their own vehicles, or city-wide security cameras. These can leverage the operator’s own connectivity (typically 5G) as well as anchor some of the data origination and consumption.

Conclusion

Telecom operators should shift their enterprise focus from mobile edge computing (MEC) to a wider approach built around "networked data". Much of the enterprise edge will reside beyond the network and telco control, in devices or on-premise gateways and servers. Essentially no enterprise IT/IoT systems will be wholly run "in" the 5G or fixed telco network, as virtual functions in a 3GPP or ORAN stack.

They instead should look for involvement in end-point devices, where data is generated, where and when it is stored and processed—and also the paths through the network it takes. This would align their propositions with connectivity (between objects or applications) as well as property (the physical location of edge data centres or network assets).

There are multiple stages to get to this new proposition of “networked cloud”, and not all operators will be willing or able to fulfil the whole vision. They will likely need to partner with the cloud players, as well as think carefully about treatment of network and regulatory boundaries.

Nevertheless, the broadening of scope from “edge compute” to “networked cloud” seems inevitable. The role of telcos as pure-play "edge" specialists makes little sense and may even be a distraction from the real opportunities emerging at higher levels of abstraction.

The original version of this article is at https://blog.cloudera.com/telco-5g-returns-will-come-from-enterprise-data-solutions/

I'll be speaking on an upcoming webinar with @cloudera about "Enterprise data in the #5G era" on May 4, 2022 - https://register.gotowebinar.com/register/3531625172953644816

#cloud #edgecomputing #5G #telecoms #latency #IoT #smartcities #mobile #telcos

Edge Computing in the Network, or Network deployed at the Edge datacentre?

Warning: totally speculative “what-if” post…. 

Almost everyone assumes that MEC-type edge-computing will be *inside* 5G or converged fixed-mobile infrastructure. The idea is that telcos will host servers deep in their networks, for low-latency 5G NR radio, coupled to micro-datacentres a millisecond or so from a cell tower, or perhaps at a local fixed line exchange / central office. 

Many telcos and their vendors seem to think this could allow the industry to create quasi-AWS distributed #cloud services. I've written and spoken about the landscape of edge computing several times (see blog here and podcast here)

But I wonder if we could also see the exact opposite approach. Imagine a small/mid-size datacentre in an urban area as a hub for a localised mobile network. It could have a 4G or 5G base station on the roof, perhaps with links to relay sites in the surrounding area. 

Using #CBRS spectrum in the US, or 3.7-3.8GHz in Germany or various of the new UK shared bands, it could cover perhaps a 3-7km radius. As it will have plenty of fibre acceess, it could also run its own cloud-RAN network for its local region or city. 

This could give local businesses direct, one-hop-to-the-cloud connection for sites or mobile #IoT. Say a local firm doing drone-as-a-service for site inspections. Or buses for a smart city. No telcos required. Now there are various challenges, like poor outdoor-to-indoor coverage at 3.5GHz. But low-band MVNO deals, WiFi & neutral hosts could help fix that.

The cloud / DC provider would certainly need additional elements, such as a core network, and perhaps a way to issue SIMs/eSIMs. But that's increasingly possible - Amazon, for instance, already hosts various cloud-based core networks from third party vendors, while Google has its own that it uses for Fi and other purposes.

Unlikely? Yes. Disruptive? Certainly.

(If you really want to push this idea, I also suggested over two years ago in this post that Amazon's purchase of Whole Foods gave it a unique urban footprint for mini-DCs. Many of those also have suitable rooftops, as well as plenty of power)

This post was originally published on my LinkedIn page. It has had over 10,000 views and has created a great stream of comments and interactions. Link here.

3 Emerging Models for Edge-Computing: Single-Network, Interconnected & Federated

Summary

Edge-computing enables applications to access cloud resources with lower latencies, more local control, less load on transport networks and other benefits.

There are 3 main models emerging for organising edge-computing services and infrastructure:

• Single-Network Telco Edge, where a fixed or mobile operator puts compute resources at its own cell-sites, aggregation points, or fixed-network central offices.
• Local / Interconnected Datacentre Edge, where an existing or new DC provider puts smaller facilities in tier-2/3 cities or other locations, connected to multiple networks.
• Federated / Open Edge, where a software player aggregates numerous edge facilities and provides a single mechanism for developers to access them.

These are not 100% mutually-exclusive - various hybrids are possible, as well as "private edge" facilities directly owned by enterprises or large cloud providers. They will also interact or integrate with hyperscale-cloud in variety of ways. 

But there is a major issue. All of these will be impacted by even faster-evolving changes in the ways that users access networks and applications, such as "fallback" from 5G to 4G, or switching to WiFi. In other words, the most relevant "edge" will often move or blur. Superficially "good" edge-compute ideas will be forced to play catch-up to deal with the extra network complexity. 
 
(Also - this model excludes the "device edge" - the huge chunk of compute resource held in users' phones, PCs, cars, IoT gateways and other local devices).

Note: this is a long post. Get a coffee. 

There is also an accompanying podcast / audio-track I've recorded on SoundCloud that explains this post if you'd rather listen than read (link)

Background and Overview 

A major area of focus for me in 2019 is edge-computing. It’s a topic I’ve covered in various ways in the last two year or so, especially contrasting the telecom industry’s definitions/views of “in-network” edge, with those of enterprise IT and IoT providers. The latter tend to be more focused on “edge datacentres” in “edge markets” [2^nd-tier cities] or more-localised still, such as on-premise cloud-connected gateways. 

I wrote a detailed post in 2018 (link) about computing power consumption and supply, which looked at the future constraints on edge, and whether it could ever really compete with / substitute for hyperscale cloud (spoiler: it can't at an overall level, as it will only have a small % of the total power).

I’m speaking at or moderating various edge-related events this year, including four global conferences run by data-centre information and event firm BroadGroup (link). The first one, Edge Congress in Amsterdam, was on 31^st January, and followed PTC’19 (link) the week before, which also had a lot of edge-related sessions.

(I’m also collaborating with long-time WebRTC buddy Tsahi Levent-Levi [link] to write a ground-breaking paper on the intersection of edge-computing with realtime communications. Contact me for details of participating / sponsoring)


Different drivers, different perspectives

A huge diversity of companies are looking at the edge, including both established large companies and a variety of startups:

• Mobile operators want to exploit the low latencies & distributed sites of 5G networks, as well as decentralising some of their own (and newlyt-virtualised) internal network / operational software
• Fixed and cable operators want to turn central offices and head-ends into local datacentres - and also house their own virtualised systems too. Many are hybrid fixed/mobile SPs.
• Long-haul terrestrial and sub-sea fibre providers see opportunities to add new edge data-centre services and locations, e.g. for islands or new national markets. A handful of satellite players are looking at this too.
• Large data-centre companies are looking to new regional / local markets to differentiate their hosting facilities, reduce long-distance latencies, exploit new subsea fibres and provide space and interconnect to various cloud providers (and telcos).
  At PTC’19 I heard places like Madrid, Fiji, Johannesburg and Minneapolis described as “edge markets”.
• Hyperscale cloud players are also latency-aware, as well as recognising that some clients have security or regulatory need for local data-storage. They may use third-party local DCs, build their own (Amazon & Whole Food sites?) or even deploy on-premise at enterprises (Amazon Outposts)
• Property-type players (eg towerco's) see edge-compute as a way to extend their businesses beyond siting radios or network gear.
• Startups want to offer micro-DCs to many of the above as pre-built physical units, such as Vapor.io, EdgeMicro and EdgeInfra.
• Other startups want to offer developers convenient (software-based) ways to exploit diverse edge resources without individual negotiations. This includes both federations, or software tools for application deployment and management. MobiledgeX and Ori are examples here.
• Enterprises want a mix of localised low-latency cloud options, either shared or owned/controlled by themselves (and perhaps on-site, essentially Server Room 2.0). They need to connect them to hyperscale cloud(s) and internal resources, especially for new IoT, AI, video and mobility use-cases.
• Network vendors are interested either in pitching edge-oriented network capabilities (eg segment-routing), or directly integrating extra compute resource into network switches/routers.
• Others: additional parties interested in edge compute include PaaS providers, security companies, SD-WAN providers, CDN players, neutral-host firms etc

Each of these brings a different definition of edge - but also has a different set of views about networks and access, as well as business models.


Application diversity

Set against this wide array of participants, is an even more-diverse range of potential applications being considered. They differ in numerous ways too - exact latency needs (<1ms to 100ms+), mobility requirements (eg handoff between edge sites for moving vehicles), type of compute functions used (CPUs, GPUs, storage etc), users with one or multiple access methods, security (physical or logical) and so on.

However, in my view there are two key distinctions to make. These are between:

• Single-network vs. Multiple-network access: Can the developer accurately predict or control the connection between user and edge? Or are multiple different connection paths more probable? And are certain networks (eg a tier-1 telco's) large enough to warrant individual edge implementations anyway?
• Single-cloud vs. Multi-cloud: Can all or most of the application's data and workloads be hosted on a single cloud/edge provider's platform? Or are they inherently dispersed among multiple providers (eg content on one, adverts from another, analytics on a third, legacy integration with a fourth / inhouse system)

For telcos in particular, there is an important subset of edge applications which definitely are single-network and internal, rather than client-facing: running their own VNFs (virtual network functions, security functions, distributed billing/charging, and managing cloud/virtualised radio networks (CRAN/vRAN). They also typically have existing relationships with content delivery networks (CDNs), both in-house and third-party.

This "anchor tenant" of on-network, single-telco functions is what is driving bodies like ETSI to link MEC to particular access networks and (largely) individual telcos. Some operators are looking at deploying MEC deep into the network, at individual cell towers or hub sites. Others are looking at less-distributed aggregation tiers, or regional centres.

The question is whether this single-network vision fits well with the broader base of edge-oriented applications, especially for IoT and enterprise.

How common will single-network access be?

The telco edge evolution (whether at region/city-level or down towards cells and broadband-access fibre nodes) is not happening in isolation. A key issue is that wide availability of such edge-cloud service - especially linked to ultra-low-latency 5G networks - will come after the access part of the network gets much more complex.

From a developer perspective, it will often be hard to be certain about a given user’s connectivity path, and therefore which or whose edge facilities to use, and what minimum latency can be relied upon:

• 5G coverage will be very patchy for several years, and for reliable indoor usage perhaps 10 years or more. Users will regularly fall back to 4G or below, particularly when mobile.
• Users on smartphones will continue to use 3^rd-party WiFi in many locations. PC and tablet users, and many domestic IoT devices, will use Wi-Fi almost exclusively. Most fixed-wireless 5G antennas will be outdoor-mounted, connecting to Wi-Fi for in-building coverage.
• Users and devices may use VPN security software with unknown egress points (possibly in another country entirely)
• Not all 5G spectrum bands or operator deployments will offer ultra-low latency and may have different approaches to RAN virtualisation. 
• Increasing numbers of devices will support multi-path connections (eg iOS TCP Multipath), or have multiple radios (eg cars).
• Security functions in the network path (eg firewalls) may add latency
• Growing numbers of roaming, neutral-host and MVNO scenarios involving third-party SPs are emerging. These will add latency, extra network paths and other complexities.
• eSIM growth may enable more rapid network-switching, or multi-MNO MVNOs like Google Fi.
• Converged operators will want to share compute facilities between their mobile and fixed networks.

This means that only very tightly-specified “single-network” edge applications make sense, unless there is a good mechanism for peering and interconnect, for instance with some form of “local breakout”.

So for instance, if Telco X operates a smart-city contract connecting municipal vehicles and street lighting, it could offer edge-compute functions, confident that the access paths are well-defined. Similarly it could offer deep in-network CDN functions for its own quad-play streaming, gaming or commerce services. 

But by contrast, an AR game that developers hope will be played by people globally, on phones & PCs, could connect via every telco, ISP & 3^rd-party WiFi connection. It will need to be capable of dealing with multiple, shifting, access networks. An enterprise whose employees use VPN software on their PCs, or whose vehicles have multi-network SIMs for roaming, may have similar concerns.

 

The connected edge

I had a bit of an epiphany while listening to an Equinix presentation at PTC recently. The speaker talked about the “Interconnected Edge”, which I realised is very distinct from this vision of a single-telco edge.

Most of the datacentre industry tries to create facilities with multiple telco connections - ideally sitting on as many fibres as possible. This allows many ingress paths from devices/users, and egress paths to XaaS players or other datacentres. (This is not always possible for the most "remote" edges such as Pacific islands, where a single fibre and satellite backup might be the only things available).

And even for simple applications / websites, there may be multiple components coming from different servers (ads, storage, streaming, analytics, security etc) so the immediate edge needs to connect to *those* services with the easiest path. Often it’s server-to-server latency that’s more important than server-to-device, so things like peering and “carrier density” (ie lots of fibres into the building) make a big difference.

In other words, there are a number of trade-offs here. Typically the level of interconnectedness means more distance/latency from each individual access point (as it's further back in the network and may mean data transits a mobile core first), but that is set against flexibility elsewhere in the system. 

A server sitting underneath a cell-tower, or even in a Wi-Fi access point, will have ultra-low latency. But it will also have low interconnectedness. A security camera might have very fast local image-recognition AI to spot an intruder via edge-compute. But if it needs to match their face against a police database, or cross-check with another camera on a different network, that will take significantly longer.

But edge datacentres also face problems - they will typically only be in certain places. This might be fine for individual smart-city applications, or localised "multi-cloud" access, but it still isn't great for multinational companies or the game/content app-developers present in 100 countries.


Is edge-aggregation the answer?

The answer seems to be some form of software edge-federation or edge-broking layer, which can tie together a whole set of different edge resources, and hopefully have intelligence to deal with some of the network-access complexity as well.

I've been coming across various companies hoping to take on the role of aggregator, whether that's primarily for federating different telcos' edge networks (eg MobiledgeX), or helping developers deploy to a wider variety of edge-datacentre and other locations (eg Ori). 

I'm expecting this space to become a lot more complex and nuanced - some will focus on being true "horizontal" exchanges / APIs for multi-edge aggregation. The telco ones will focus on aspects like roaming, combined network+MEC quality of service and so on. Others will probably look to combine edge with SD-WAN for maximum resilence and lowest cost.

Yet more - probably including Amazon, Microsoft and other large cloud companies - will instead look to balance between edge vs. centralised cloud for different workloads, using their own partnerships with edge datacentres (perhaps including telcos) and containerisation approaches like Amazon's Greengrass.

Lastly, we may see the emergence of "neutral-host" networks of edge facilities, not linked to specific telcos, data-centre providers or fibre owners. These could be "open" collaborations, or even decentralised / blockchain-based approaches.

The "magic bullet" here will be the ability to cope with all the network complexities I mentioned above (which drive access paths and thus latencies), plus having a good geographic footprint of locations and interconnections. 

In a way, this is somewhat similar to the historic CDN model, where Akamai and others grew by placing servers in many ISPs' local networks - but that was more about reducing latency from core-to-edge, rather than device-to-edge, or edge-to-edge.

I doubt that this will resolve to a single monopoly player, or even an oligopoly - there are too many variables, dimensions and local issues / constraints.

 

Summary and conclusions

There are 3 main models emerging for organising edge-computing services and infrastructure:

• Single-Network Telco Edge
• Local / Interconnected Datacentre Edge
• Federated / Open Edge

These will overlap, and hybrids and private/public splits will occur as well.

My current view remains that power constraints mean that in-network [telco-centric] edge cannot ever realistically account for more than 2% of overall global computing workloads or perhaps 3-5% of public cloud services provision, in volume terms – although pricing & revenue share may be higher for provable lower latencies. Now that is certainly non-trivial, but it’s also not game-changing. 

I also expect that in-network edge will be mostly delivered by telcos as wholesale capacity to larger cloud providers, or through edge-aggregation/federation players, rather than as “retail” XaaS sold directly to enterprises or application/IoT developers.

I’m also expecting a lot of telco-edge infrastructure to mostly serve fixed-network edge use-cases, not 5G or 4G mobile ones. 5G needs edge, more than edge needs 5G. While there are some early examples of companies deploying mini-datacentres at large cell-tower “hub” sites (eg Vapor.io), other operators are focusing further back in the network, at regional aggregation points, or fixed-operator central offices. It is still very early days, however.

The edge datacentre business has a lot of scope to grow, both in terms of networks of micro-datacentres, and in terms of normal-but-small datacentres in tier-2/3/4 cities and towns. However, it too will face complexities relating to multi-access users, and limited footprints across many locations.

The biggest winners will be those able to link together multiple standalone edges into a more cohesive and manageable developer proposition, that is both network-aware and cloud-integrated. 

The multi-network, multi-cloud edge will be tough to manage, but essential for many applications.

It is doubtful that telco-only edge clouds (solo or federated) can work for the majority of use-cases, although there will be some instances where the tightest latency requirements overlap with the best-defined connectivity models.

I'm tempted to create a new term of these players - we already have a good term for a meeting point of multiple edges: a corner. Remember where you first heard about Corner Computing...

If you are interested in engaging me for private consulting, presentations, webinars, or white papers, please get in touch via information at disruptive-analysis dot com, or my LinkedIn and Twitter. 

I will be writing a paper soon on "Edge Computing meets Voice & Video Communications" - get in touch if you are interested in sponsoring it. Please also visit deanbubley.com for more examples of my work and coverage.