Tag: data centre

Four goals for the data-driven telco

Becoming a data-driven telco

There have been many case studies over the last five years demonstrating the disruption caused by “data-driven businesses”, i.e. those using insights to understand customers, automate processes, change their business models and drive new revenues. In the future, this concept will become an integral part of what it takes to compete successfully, allowing organisations to understand and run all parts of their operations, work with their customers and partners and take part in external activities in new ecosystems. This applies to telecoms operators as much as any other industry.

This research builds on a range of reports STL Partners has previously published on strategic topics related to telcos’ use of data, including:

This research turns to the practical topics of delivering on these strategic goals. The diagram below offers an overview of the drivers and barriers affecting delivery areas such as telco data management and machine learning (ML) in the short and longer term.

Drivers and barriers to being a data-driven telco

Source: STL Partners

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What capabilities should telcos develop?

Telcos are reasonably sophisticated users of data, but their particularly complex web of legacy systems requires a good deal of work around data management and governance to enable the extraction of data sets to give 360-degree view of the customer – and increasingly to provide training data for algorithms.

In the mid-term, telcos that are successful in selling IoT and becoming ecosystem players will require new A3 to deal with the increasing number of services, devices, price points and parties involved in providing service to a customer. Our research suggests that there is a range of new A3 technologies that can provide the automation and intelligence for this, as well as for the underlying data management processes.

In the longer-term, A3 will speed up decision making, impacting company strategy, new product and service creation, and customer experience. Humans will increasingly be supported by AI-, ML- and automation-powered tools in their decision-making. A similar progression will occur among competitors in telecoms, and in adjacent markets, increasing the complexity and speed of doing business. Besides integrating A3 into human workflows, working at increasing speed will depend on getting richer insights out of the available data with techniques such as small data and creation of synthetic data.

Capabilities for a data-driven telco

Source: STL Partners

 

Table of contents

  • Executive Summary
    • Capabilities telcos should develop over the medium term
    • What will telcos focus on in the mid-term?
    • Next steps
  • Becoming a data-driven telco
    • Short term drivers
    • Barriers in the short term
    • Long term drivers
    • Barriers in the long term
  • Availability of data
    • Use of data fabrics
    • Better data labelling
    • Rise of synthetic data
    • More intelligent data selection
    • Telco strategies for cloud usage
  • Equipping people
    • Augmented analytics and business intelligence
    • Decision intelligence
  • Work on governance
    • Governance across the telco
    • Agility in governance
    • Governance for AI and machine learning
    • Ethical governance
    • Improved measurement of governance
    • Governance in ecosystems
  • Index

Forecasting capacity of network edge computing

Telco edge build has been slower than expected

Telecoms operators have been planning the deployment of edge computing sites for at least the last three years.

Initially, the premise of (mobile) edge computing was to take advantage of the prime real estate telecoms operators had. Mobile operators, in particular, had undergone a process of evolving their network facilities from sites which housed purpose-built networking equipment to data centres as they adopted virtualisation. The consolidation of networking equipment meant there would be spare capacity in these data centres that could easily host applications for enterprises and developers.

That evolution has now been accelerated by the advent of 5G, a mobile generation built on a software-based architecture and IT principles. The result will be a proliferation of edge data centres that will be used for radio access network and core network hardware and software.

However, the reality is that it has taken time for telcos to deploy these sites. There are multiple reasons for this:

  1. Cost: There is a cost to renovate an existing telco site and ensure it meets requirements common for world-class data centres.
  2. Demand: Telcos are hesitant to take on the risk of building out the infrastructure until they are certain of the demand for these data centres.
  3. 5G roll-out: Mobile operators have been prioritising their 5G RAN roll-out in the last two years, over the investment in edge data centres.
  4. Partnership decisions: The discussion around who to partner with to build the edge data centres has become more complicated, because of the number of partners vying for the role and the entrance of new partners (e.g. hyperscalers) which has slowed down decision-making

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Early adopters have taken significant strides in their edge strategy in 2021

2020 and 2021 have been seen as inflection points as a number of leading telecoms operators have launched edge sites: e.g. AT&T, Verizon, Cox Communications, SK Telecom and Vodafone. Arguably, this was triggered by AWS announcing partnerships on AWS Wavelength with four telecoms operators in November 2019, with more recently announced (e.g. Telstra in 2021).

Going forward, key questions remain on the trajectory of telco edge build:

  • How many edge data centres will telcos build and make available for consumer/enterprise applications?
  • How much capacity of telco edge computing will there be globally?
  • How much of telco edge computing will be used for distributed core network functions vs. consumer/enterprise applications?
  • What proportion of telco edge data centre capacity will be taken up by hyperscalers’ platforms?

This report seeks to forecast the capacity at telecoms operators’ edge data centres until 2025 and provide clarity on the nature and location of these sites. In other words, how many sites and servers will be available for running applications and where will these sites be located, both physically and logically in the telecoms operators’ networks.

Before reading this report, we would recommend reading STL Partners’ previous publications on telco edge computing to provide context for some of the key themes addressed, for example:

The report focuses on network edge computing sites

Edge computing comprises of a spectrum of potential location and technologies designed to bring processing power closer to the end-device and source of data, outside of a central data centre or cloud. This report focuses on forecasting capacity at the network edge – i.e. edge computing at edge data centres owned (and usually operated) by telecoms operators.

The initial version of the forecast models capacity at these sites for non-RAN workloads. In other words, processing for enterprise or consumer applications and the distributed core network functions required to support them. Future versions of the forecast will expand to RAN.

Forecast scope in terms of edge locations and workload types

The report covers two out of three scenarios for building the network edge

Table of content

  • Executive summary
  • Introduction
  • There are 3 key factors determining telco edge data centre build out
  • Logically, most network edge will be in the transport aggregation layer
  • Geographically, we will see a shift in the concentration of network edge data centres
  • The limited capacity at network edge DCs will largely be used for edge applications
  • Most telecoms operators are taking a hybrid approach to building their edge
  • Conclusions and next steps
  • Appendix: Methodology

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Telco edge computing: What is the operator strategy?

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Edge computing can help telcos to move up the value chain

The edge computing market and the technologies enabling it are rapidly developing and attracting new players, providing new opportunities to enterprises and service providers. Telco operators are eyeing the market and looking to leverage the technology to move up the value chain and generate more revenue from their networks and services. Edge computing also represents an opportunity for telcos to extend their role beyond offering connectivity services and move into the platform and the application space.

However, operators will be faced with tough competition from other market players such as cloud providers, who are moving rapidly to define and own the biggest share of the edge market. Plus, industrial solution providers, such as Bosch and Siemens, are similarly investing in their own edge services. Telcos are also dealing with technical and business challenges as they venture into the new market and trying to position themselves and identifying their strategies accordingly.

Telcos that fail to develop a strategic approach to the edge could risk losing their share of the growing market as non-telco first movers continue to develop the technology and dictate the market dynamics. This report looks into what telcos should consider regarding their edge strategies and what roles they can play in the market.

Following this introduction, we focus on:

  1. Edge terminology and structure, explaining common terms used within the edge computing context, where the edge resides, and the role of edge computing in 5G.
  2. An overview of the edge computing market, describing different types of stakeholders, current telecoms operators’ deployments and plans, competition from hyperscale cloud providers and the current investment and consolidation trends.
  3. Telcos challenges in addressing the edge opportunity: technical, organisational and commercial challenges given the market
  4. Potential use cases and business models for operators, also exploring possible scenarios of how the market is going to develop and operators’ likely positioning.
  5. A set of recommendations for operators that are building their strategy for the edge.

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What is edge computing and where exactly is the edge?

Edge computing brings cloud services and capabilities including computing, storage and networking physically closer to the end-user by locating them on more widely distributed compute infrastructure, typically at smaller sites.

One could argue that edge computing has existed for some time – local infrastructure has been used for compute and storage, be it end-devices, gateways or on-premises data centres. However, edge computing, or edge cloud, refers to bringing the flexibility and openness of cloud-native infrastructure to that local infrastructure.

In contrast to hyperscale cloud computing where all the data is sent to central locations to be processed and stored, edge computing local processing aims to reduce time and save bandwidth needed to send and receive data between the applications and cloud, which improves the performance of the network and the applications. This does not mean that edge computing is an alternative to cloud computing. It is rather an evolutionary step that complements the current cloud computing infrastructure and offers more flexibility in executing and delivering applications.

Edge computing offers mobile operators several opportunities such as:

  • Differentiating service offerings using edge capabilities
  • Providing new applications and solutions using edge capabilities
  • Enabling customers and partners to leverage the distributed computing network in application development
  • Improving networkperformance and achieving efficiencies / cost savings

As edge computing technologies and definitions are still evolving, different terms are sometimes used interchangeably or have been associated with a certain type of stakeholder. For example, mobile edge computing is often used within the mobile network context and has evolved into multi-access edge computing (MEC) – adopted by the European Telecommunications Standards Institute (ETSI) – to include fixed and converged network edge computing scenarios. Fog computing is also often compared to edge computing; the former includes running intelligence on the end-device and is more IoT focused.

These are some of the key terms that need to be identified when discussing edge computing:

  • Network edge refers to edge compute locations that are at sites or points of presence (PoPs) owned by a telecoms operator, for example at a central office in the mobile network or at an ISP’s node.
  • Telco edge cloud is mainly defined as distributed compute managed by a telco  This includes running workloads on customer premises equipment (CPE) at customers’ sites as well as locations within the operator network such as base stations, central offices and other aggregation points on access and/or core network. One of the reasons for caching and processing data closer to the customer data centres is that it allows both the operators and their customers to enjoy the benefit of reduced backhaul traffic and costs.
  • On-premise edge computing refers to the computing resources that are residing at the customer side, e.g. in a gateway on-site, an on-premises data centre, etc. As a result, customers retain their sensitive data on-premise and enjoy other flexibility and elasticity benefits brought by edge computing.
  • Edge cloud is used to describe the virtualised infrastructure available at the edge. It creates a distributed version of the cloud with some flexibility and scalability at the edge. This flexibility allows it to have the capacity to handle sudden surges in workloads from unplanned activities, unlike static on-premise servers. Figure 1 shows the differences between these terms.

Figure 1: Edge computing types

definition of edge computing

Source: STL Partners

Network infrastructure and how the edge relates to 5G

Discussions on edge computing strategies and market are often linked to 5G. Both technologies have overlapping goals of improving performance and throughput and reducing latency for applications such as AR/VR, autonomous vehicles and IoT. 5G improves speed by increasing spectral efficacy, it offers the potential of much higher speeds than 4G. Edge computing, on the other hand, reduces latency by shortening the time required for data processing by allocating resources closer to the application. When combined, edge and 5G can help to achieve round-trip latency below 10 milliseconds.

While 5G deployment is yet to accelerate and reach ubiquitous coverage, the edge can be utilised in some places to reduce latency where needed. There are two reasons why the edge will be part of 5G:

  • First, it has been included in the 5Gstandards (3GPP Release 15) to enable ultra-low latency which will not be achieved by only improvements in the radio interface.
  • Second, operators are in general taking a slow and gradual approach to 5G deployment which means that 5G coverage alone will not provide a big incentive for developers to drive the application market. Edge can be used to fill the network gaps to stimulate the application market growth.

The network edge can be used for applications that need coverage (i.e. accessible anywhere) and can be moved across different edge locations to scale capacity up or down as required. Where an operator decides to establish an edge node depends on:

  • Application latency needs. Some applications such as streaming virtual reality or mission critical applications will require locations close enough to its users to enable sub-50 milliseconds latency.
  • Current network topology. Based on the operators’ network topology, there will be selected locations that can meet the edge latency requirements for the specific application under consideration in terms of the number of hops and the part of the network it resides in.
  • Virtualisation roadmap. The operator needs to consider virtualisation roadmap and where data centre facilities are planned to be built to support future network
  • Site and maintenance costs. The cloud computing economies of scale may diminish as the number of sites proliferate at the edge, for example there is a significant difference in maintaining 1-2 large data centres to maintaining 100s across the country
  • Site availability. Some operators’ edge compute deployment plans assume the nodes reside in the same facilities as those which host their NFV infrastructure. However, many telcos are still in the process of renovating these locations to turn them into (mini) data centres so aren’t yet ready.
  • Site ownership. Sometimes the preferred edge location is within sites that the operators have limited control over, whether that is in the customer premise or within the network. For example, in the US, the cell towers are owned by tower operators such as Crown Castle, American Tower and SBA Communications.

The potential locations for edge nodes can be mapped across the mobile network in four levels as shown in Figure 2.

Figure 2: possible locations for edge computing

edge computing locations

Source: STL Partners

Table of Contents

  • Executive Summary
    • Recommendations for telco operators at the edge
    • Four key use cases for operators
    • Edge computing players are tackling market fragmentation with strategic partnerships
    • What next?
  • Table of Figures
  • Introduction
  • Definitions of edge computing terms and key components
    • What is edge computing and where exactly is the edge?
    • Network infrastructure and how the edge relates to 5G
  • Market overview and opportunities
    • The value chain and the types of stakeholders
    • Hyperscale cloud provider activities at the edge
    • Telco initiatives, pilots and plans
    • Investment and merger and acquisition trends in edge computing
  • Use cases and business models for telcos
    • Telco edge computing use cases
    • Vertical opportunities
    • Roles and business models for telcos
  • Telcos’ challenges at the edge
  • Scenarios for network edge infrastructure development
  • Recommendation
  • Index

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