Telco 5G Returns Will Come from Enterprise Data Solutions

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This blog post was written by Dean Bubley, industry analyst,  as a guest author for Cloudera. 

Communications service providers (CSPs) are rethinking their approach to enterprise services in the era of advanced wireless connectivity and 5G networks, as well as with the continuing maturity of fibre and Software-Defined Wide Area Network (SD-WAN) portfolios. 

Many previously consumer-centric operators are developing propositions for “verticals”, often combining on-site or campus mobile networks with edge computing, while integrating deeper solutions for specific industries or horizontal applications. Part of this emphasis extends to helping enterprises deal with their data and overall cloud connectivity as well as local networks.

At the same time, operators are also becoming more data- and cloud-centric themselves. They are using disaggregated systems, plus distributed compute and data, for their own requirementsrunning their networks more efficiently, and dealing with customers and operations more flexibly. As Disruptive Analysis has 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 they will be working with.

What is needed is a broader view of the “networked cloud”, not just the “telco cloud” that many like to discuss.

Networked data and cloud are not just “edge computing”

A prime example of this is seen at the edge of the network. In recent years, telecom operators’ discussions around the cloud have oriented on two key directions:

  • External edge computing: The intention by (mostly mobile) operators to deploy in-network edge nodes suitable for end-user applications, such as vehicle control, internet of things, smart city functions, low-latency cloud gaming, or enterprise private networks. Often using the term “MEC” (mobile edge computing), this spans both fully 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 (Radio Network) technology for disaggregated 4G/5G deployments. Some of these functions need to be deployed at the edge of the network, while others can be more centralised.

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

Numerous operators are now working with both public and private clouds for their own operational needsrunning their networks, managing subscriber data and experience, and enabling greater levels of automation and control. While there are still raging debates about the role of “openness” and outsourcing to hyperscalers, the underlying storycloudification of telcos’ networks and IT estatesseems to be consistent and accelerating. Certain functions need to be at the edge, for instance because of timing constraints of radio signal processing in Open RAN, or the desire to manage ultra-low latency 5G “slices”.

In contrast, the customer-facing cloud and data services offers have been slower to emerge. The focus on MEC has tended to mean operators’ emphasis has been on deployment of “mini data centres” deep in their networksat cell towers or aggregation sites, or fixed-operators’ existing central office locations. Usually the discussion has centred on “low latency” applications as the key differentiator for CSP-enabled 5G edge. The focus has also been hugely centred on compute rather than data storage and analysis.

This has meant something of 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 framesfrom real time closed-loop actions, to analysis of long-term archived data. It may also span multiple cloudsas 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.

An example of the “networked cloud”

Consider an example: video cameras for a smart city. There are numerous applications for these, ranging from public transit and congestion control, to security and law enforcement, to identification of free parking spots or 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, 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-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.

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 situationswith both opportunities and challengesexist 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 areasbut they need to look beyond narrow views of edge-compute.  

Location-specific data

As a result, the next couple of years may see something of a shift in telecoms’ discussions and ambitions around enterprise data. There will be huge opportunities emerging around enterprise data’s chain-of-custody and audit trailsnot 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).

In some cases, CSPs will take a lead role here, especially where they own and control the endpoints and applications involved and can 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 APIsessentially, 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.

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 servicefor 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. They should look for involvement in end-point devices, where data is generated, where and when it is stored and processedand 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.

Please watch Cloudera & Dean Blubley webinar replay Enterprise data in the 5G era to explore how telcos can capitalise on the opportunity of data in the 5G era and help drive the transformation of their enterprise customers.

By Dean Bubley, industry analyst and founder of Disruptive Analysis. You can read more of his work on his site.

Author: Subham

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