Huge Gulf Between European, North American Telcos on 5G

Rarely does one see such wide variations in telecom executive views of coming technology as now seems to be the case for 5G. In a recent survey, McKinsey found 100 percent of European execs citing the business case as the biggest 5G challenge. Just 11 percent of North American leaders though the business case was the "biggest" challenge.

source: McKinsey

Kinetic Edge Alliance Aims to Build Infrastructure Edge Capabilities in 30 U.S. Metros

The Kinetic Edge Alliance now is targeting the top 30 U.S. metro markets, representing which almost 50 percent of the US population, for infrastructure edge computing facilities.

In 2019, the Alliance will focus on Chicago, Pittsburgh, Atlanta, Dallas, Los Angeles and Seattle.

Alliance members include Vapor IO, Federated Wireless, Linode, MobiledgeX, Packet and StackPath and technical partners Alef Mobitech, Detecon International, Hitachi Vantara, New Continuum Data Centers, Pluribus Networks, and Seagate Technology.

Linode supplies cloud computing infrastructure. MobiledgeX will provide developers with automated workload orchestration.

Packet supplies bare-metal infrastructure. StackPath will supply edge computing services including containers and virtual machines.

Vapor IO supplies the “buildings.”

Key deployment partners include Alef Mobitech, which supplies Mutli-Access Edge Computing applications. Detecon International: Detecon International, a subsidiary of Deutsche Telekom will supply consulting services.

Hitachi Vantara, a wholly-owned subsidiary of Hitachi Ltd., delivers data center and IoT expertise including analytics. New Continuum will cross-connect its West Chicago data center with the Kinetic Edge to provide local colocation capacity as well as a software-enabled Internet Exchange Point (IXP).

Pluribus Networks will supply management. Seagate will provide technical blueprints and deployment support for end users and partners related to storage.

Service Providers Cannot be Everything to Everyone, Anymore

The greatest opportunity for connectivity service providers over the next five years is getting right the balance of wholesale and retail operations, says Dean Bubley of Disruptive Analysis. What he means is that service providers cannot do everything, anymore, and must make choices.

Most telcos will have to pick one to five areas where they can be viable platforms and then partner for everything else, Bubley argues.

And though many have tried some way to mimic the app provider business model, that mostly has not worked. App providers hope to earn 50 cents a year from billions of customers; telcos have to hope to earn $30 to $35 a month from possibly millions of customers, says Benoit Felten, Diffraction Analysis principal. Those models are almost mutually exclusive.

“Telcos have been in a weird place for 10 years, between pipes and platforms, and they have to decide which they want to be,” says Felten. “You can’t be everything to everybody.”

One example is new revenue generated by enterprise services, ranging from new internet of things use cases to new forms of indoor access infrastructure. “But the revenue might not go to traditional telcos,” says Bubley.  

The greatest opportunity is that infrastructure can be deployed in lots of ways, and not just by service providers, says Felten.  In fact, it likely is no longer possible to say with complete certainty when and where network infrastructure must be owned.

“If you are AT&T today, do you need to own your own infrastructure?” Felten asks. “Maybe owning the pipe is not strategic anymore.”

There is something nonsensical about owning lots of popular content and putting it behind a walled garden, when you’d really rather sell it to everyone. In other words, strategies that make sense for a major content owner (sell more things to everyone globally, on any network) are not necessarily those of a major connectivity provider (sell more things on my network, to my customers).

Dr. George Ford Talks About What Regulators Get Wrong

Telecom and Internet regulators often create policies that have effects opposite of what they intended. They want more competition and then create policies that lead to less competition. They want more investment in next-generation networks and produce less. Good intentions produce harmful policies.

Dr. George Ford, Phoenix Center chief economist, discusses a number of key examples, examining policies on competition, investment, network neutrality, broadband deployment, and sponsored data access. He will also discuss how measures of success can be very misleading.

What are the Biggest Opportunities and Threats in the Connectivity Business?

Dean Bubley and Benoit Felten tackle a variety of big telecom issues, lightning fast.

Where are the greatest opportunities and biggest threats to the connectivity business model? Where are the big new revenue sources; the new values to be monetized? Who are the new competitors and platforms? How do incumbents respond? What are the key technologies, and why? How do service, app, platform, and device suppliers maximize their chances of success? What does 5G, edge-computing, and IoT mean for the wholesale and connectivity players? How might thinking about owning or operating infrastructure change? 

Does Zero Rating Cause Price Increases?

Correlation is not causation, in communications markets or anywhere else.

A study conducted recently by epicenter.works reports that, between 2015 and 2016, “in markets where zero-rating offers had existed in oth years, prices increased by two percent , whereas in markets with no zero-rating offers in both years, prices dropped by eight percent.”

Of course, methodology always matters. There is no practical way to compare prices across countries without picking some benchmark, whether that is the “lowest cost” retail price, the “average” price or some other common metric. So the report’s price changes refer only to changes in the lowest-priced tier, not all other tiers.

Also, such data only compares the tariffs; not the actual prices actually paid by most consumers, because consumption behavior is outside the analysis parameters. The point is that posted retail prices for specific products only matter if “most people” buy those products. Posted retail prices also matter to the degree that people actually pay those prices, and not some other promotional or bundled prices.

In markets where bundling is prevalent, it can be difficult to determine the actual price of internet access services.

Nor does the study consider price changes in markets that might be plausibly explained some other way. It is perhaps an intuitive assumption that zero-rating and differentially-priced offers are more attractive where data volume is expensive. If that is the case, then retail prices in such markets are almost, by definition, “more expensive” than markets where data costs are lower.

It is a bit of a tautology: zero rating is offered where data costs are high, and therefore we find that markets with zero rating have higher data costs. In other words, prices in Portugal, Spain or Germany are high, relative to France, Denmark or Sweden. It does not seem self evident that zero rating changes those dynamics.

source: epicenter.works

On the other hand, it seems logical enough that zero rating, if not offered by every major operator in a market, could increase customer loyalty, and thus confer some additional pricing power, which would again lead to higher prices where zero rating is offered.

“We assume our findings can ae explained in part by the fact that zero-rating distorts the normal competition between IAS providers based on data volumes and speeds,” the researchers suggest.

Others might argue that retail packaging and pricing are not a “distortion” but part of the fundamental pricing and packaging backdrop. The analogy would be seeing the introduction of the Apple iPhone as a distortion of the smartphone market, or simply an innovation.

source: EU

Zero rating may be correlated with mobile internet access price changes. But that does not mean zero rating causes prices to rise or fall.

Scripts, Coding or Autonomous Behavior?

Artificial intelligence includes a number of approaches, some more akin to “automation,” others more like self-learning that leads to system autonomous behavior. The intended benefits can be very practical, though.

Consider the alarm resolution process. Quite often, one fault generates multiple alerts on multiple systems, even when they have the same root cause. So an applied AI capability would recognize redundant alerts and take preventative action, while suppressing alerts related to a single fault, so the alerts do not cascade, said Bhanu Singh, OpsRamp SVP.

Bhanu Singh, OpsRamp SVP

Controversial though it might be, the key ultimately is autonomous behavior. The whole point is to avoid having humans code or create scripts, said Taly Dunevich, Ayehu global business development VP.

Taly Dunevich, Ayehu VP

Also, contrary to some opinion, AI “does not require algorithms.” The systems should learn by themselves, without human intervention. Enterprise software systems these days are complex and highly dynamic; too complex for a limited number of humans to manage, said Frank Yue, KEMP Technologies solutions architect. “AI has to identify the problems, know what has to be done, and then do it,” Yue said.

Frank Yue, KEMP Technologies

There simply is too much data to make sense of.

“It doesn’t work if you only extrapolate from past events,” noted Will Houston, GAVS Technologies VP. “You have to auto-discover everything.”

“AIOps is about extracting actionable data insights and then applying those insights to information technology operations,” said Will Houston, GAVS Technologies VP. “By 2023, 30 percent of large enterprises will use AI for IT operations, where today perhaps two percent do so.”

“AI used to about rule-based systems, while machine learning is statistical,” said John Byrnes, SRI International senior computer scientist. “Both are used today.”

In a practical sense, AI use cases often are about automating existing processes such as handling trouble tickets, said Dunevich. In other cases, applied AI can be used to configure and maintain competing Wi-Fi networks, said Marcel Chenier, KodaCloud CTO.

Applied AI is diverse because it includes a range of intelligent capabilities related to autonomous infrastructure, that  “sense, think, act and learn,” said Katie Fritsch, HPE product marketing lead. Observation is what the sensors do. Learning is what the servers do when they look for patterns. Prediction is how the patterns are applied to identify abnormal behavior.

As applied to information technology operations, experts say to start small, with simple processes. “Automate the easy things first,” said Dunevich. “Eliminate the smaller problems first,” advised Houston. That might mean using AI to “keep trucks in lanes” at first, and not moving to full autonomous driving,” said Byrnes.

And people--not technology--are key parts of the journey, said Yue. “What is the incentive for the ops team if AI replaces their jobs?”

Paul Brittain, Metaswitch

“If the ops team doesn’t trust the new solution, they won’t support it,” noted Paul Brittain, Metaswitch VP.