Ericsson hds 8000 wp 16

An Economic Study of the
Hyperscale Data Center
Ericsson Hyperscale Datacenter
System 8000 transforms the economics
of the enterprise data center, enabling
a new generation of hyperscale architecture
January 2016

An Economic Study of the Hyperscale Data Center
Copyright © 2016 Mainstay, LLC
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TABLE OF CONTENTS
Executive Summary 3
Welcome to the Networked Society 4
Transforming the Enterprise Data Center 4
Virtualization and Software-Defined Infrastructure 5
Hyperscale Pioneers 6
Ericsson Hyperscale Datacenter System 8000:
Hyperscale Data Center Architecture for
the Enterprise 6
Higher Utilization 7
Optimized Data Center Infrastructure Management:
From “Procure-to-Provision” to “Pool-to-Provision” 9
Business Impact and TCO Analysis 10
Operating Expense (OPEX) Savings 10
Capital Expenditure (CAPEX) Savings 12
Revenue and Other Strategic Impacts 13
5-Year TCO Impact for Enterprise Data Centers 13
TCO and ROI Summary 14
TCO Model Approach and Assumptions 15
The Journey to Hyperscale 16
About This Study 17
About Mainstay 17
Appendix 18
Endnotes 19

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EXECUTIVE SUMMARY
This paper examines the economics and performance of a new data center infrastructure solution
from Ericsson called Ericsson Hyperscale Datacenter System 8000 that is poised to reshape how
enterprise data centers are architected to meet the challenges of the hyper-connected Networked
Society. Based on the paradigm-shifting Intel®
Rack Scale Architecture, Ericsson Hyperscale
Datacenter System 8000 delivers a hyperscale cloud solution for enterprise data centers that
will enable quantum leaps in efficiency, infrastructure elasticity, and economics.
Our research found that companies implementing Ericsson’s hyperscale platform can capture
significant TCO savings compared to traditional data center infrastructures — generating CAPEX
savings of up to 55%, OPEX savings of up to 75%, and a return on investment (ROI) of up to
138% for large enterprise data center operators over a five-year period.
Ericsson Hyperscale Datacenter System 8000 generates these savings by delivering performance and
scalability on par with data center leaders such as Facebook, Google and Amazon in a commercially
available platform. By creating a pool of infrastructure components leveraging Intel’s new RSA
technology, SDI techniques, and optical networking, data center operators can better match infra-
structure capacity with application and network workload requirements, thereby improving utilization
of these resources. In this white paper we detail the range of value drivers that support these results
and estimate the impacts across different data center scale scenarios.
In an economy where companies face exponentially rising data traffic and demands for new cloud
computing capabilities, data center operators need to take a close look at new ways to provide IT
services that are more flexible, cost-effective and vastly more scalable than what they offer today.
Operators need to ask themselves whether they are ready for the Networked Society.

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WELCOME TO THE NETWORKED SOCIETY
We live in a world where five billion people are connected and where mobile, broadband, and cloud are
transforming the fabric of society. Ericsson calls it the Networked Society and it is impacting our everyday
lives in profound ways, not unlike the titanic shifts of the industrial revolution more than a century ago.
Today, Internet connectivity and mobile communications are taken for granted.1
And with the rise of
the Internet of Things, more products are becoming “smart” and connected with other things across an
expanding global cloud network. Meanwhile information streams from these networks are proliferating,
spawning opportunities to harness Big Data for competitive advantage as well as social progress.
The world’s data traffic is exploding as a result. Analysts estimate that global workload growth will
increase by 81% between 2015 and 2018, with the highest growth (113%) being cloud-based work-
loads. And Ericsson is currently forecasting compounded annual growth of mobile traffic of 45%
between 2015–2021.2
All of this is placing enormous pressure on businesses and data centers to keep
pace. Indeed, one of the most critical challenges facing enterprise data centers in the next few years
will be how to scale their computational capacity to meet exponentially growing digital workloads
in an economically efficient way.
To thrive in the Networked Society, businesses will need to seize fast-emerging digital business
opportunities that require immediate deployments of compute, storage and networking resources.
Demand can also recede or shift to new projects just as quickly, so enterprise data centers need to be
able to turn capacity on and off at short notice. This means data centers will need to provide business
stakeholders with the same “infrastructure on tap” capabilities that modern cloud-service providers
like Amazon Web Services have pioneered.
Indeed, as McKinsey & Company has observed, one of the top priorities for enterprise data centers
will be establishing a commercial-style business relationship with internal customers. This will require
an ability to standardize the data center’s service offerings, provide a solid “bottom-up” service cost
structure, implement robust infrastructure management solutions, and reinvent the way they serve
customers.3
TRANSFORMING THE ENTERPRISE DATA CENTER
The great majority of enterprise data centers today are ill-equipped to help businesses succeed in the
Networked Society. Designed primarily to deliver back-office applications to internal business users,
the traditional data center is burdened with an inefficient and costly architectural design that prevents
it from scaling and flexing rapidly to meet the changing workloads of a modern digital enterprise.
One of the biggest design inefficiencies of the conventional data center is the creation of separate silos
of hardware and software for each application workload. Because resources are not shared between
workloads, investments in capacity buffers (over-provisioning) and high availability need to be made
separately for each workload, adding to the overall data center cost burden.
CHALLENGES FACING
DATA CENTERS
TODAY
• Scaling to support
exponential growth of
application and network
workloads with minimal
additional costs to the
business (OPEX/CAPEX)
• Transforming service
capabilities from back
office operations to a
strategic revenue driving,
customer-facing asset
• Increasing flexibility and
speed of delivery of
infrastructure services to
meet the dynamics of
digital industrialization

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Figure 1. Traditional heterogeneous application workload management
Moreover, because traditional data centers typically follow a lengthy “procure-to-provision” process
tied to the business’s annual capital investment cycle, system architects will typically over-provision
the infrastructure to weather these lengthy procurement cycles. Enterprise architects we interviewed
said they typically design 30% over-capacity for a standard workload and up to 60–70% for mission-
critical workloads.
Adding to data center complexity and cost is the wide variety of proprietary infrastructure components
associated with each application stack. The bill of materials includes database appliances, storage
solutions, servers, and networking solutions — all procured on a per-application, per-department basis.
Heterogeneous environments like this always require more people to administer, adding to OPEX.
Virtualization and Software-Defined Infrastructure
To address these inefficiencies, the traditional data center is evolving. Server virtualization technology
has allowed system administrators to have more flexibility in provisioning infrastructure resources.
According to Forrester Research, 77% of x86 servers in enterprise data centers have been virtualized.4
Analysts estimate that virtualization has lifted x86 server utilization from 5–10% to over 30%.5
The success of server virtualization has opened the door to virtualizing other data center components,
such as network and storage, and leading to the next wave of enterprise data center optimization —
software-defined infrastructure (SDI) — which seeks to virtualize the entire data center infrastructure.
Accelerating the spread of this new architecture is an industry-standard technology blueprint developed
by Intel called Intel®
Rack Scale Architecture (RSA).
Intel RSA is a logical architecture that disaggregates compute, storage, and network resources and
introduces the ability to pool these resources for more efficient utilization of assets. It simplifies
resource management and provides the ability to dynamically compose resources based on
workload-specific demands.6
Required
CapacityLong Procure-to-Pay
Process per Workload
Creates Overprovisioning
Increases
hardware capital
expenses
Proportionally
increases operating
expenses
Reduces
resource
utilization
Application
Workload
for BU 1
Overprovisioned
Capacity
Required
Capacity
Application
Workload
for BU 1
Overprovisioned
Capacity
Required
Capacity
Application
Workload
for BU 2
Overprovisioned
Capacity
Required
Capacity
Application
Workload
for BU 2
Overprovisioned
Capacity
High Availability
Buffer
SOFTWARE-DEFINED
INFRASTRUCTURE
(SDI)
Software-defined infrastructure
is the definition of technical
computing infrastructure
entirely under the control
of software. It operates
independent of any hardware-
specific dependencies and are
programmatically extensible.

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Hyperscale Pioneers
Technology giants Google, Amazon, and Facebook were among the first to exploit the new architectural
paradigm, developing what are called hyperscale data centers — highly scalable platforms built to
handle the massively complex workloads of the Networked Society.
These pioneering hyperscale platforms have set the modern standard for performance, efficiency,
and manageability. In fact, our research found that these custom-built hyperscale data centers, when
compared to traditional data centers, deliver four times the level of CPU utilization, increase network
utilization by as much as 26%, and dramatically lift productivity by enabling a single IT administrator
to manage thousands of servers versus just hundreds, as shown in Figure 2.
These efficiencies have enabled large public cloud providers to drive down data center infrastructure
and management costs, making it economically feasible to accommodate the massive computing and
storage demands of the Networked Society. The next step in the evolution of the data center is to
make hyperscale cloud architectures commercially available to enterprises worldwide.
Figure 2. Hyperscale data center efficiencies
ERICSSON HYPERSCALE DATACENTER SYSTEM 8000:
HYPERSCALE DATA CENTER ARCHITECTURE FOR
THE ENTERPRISE
Recognizing the game-changing potential of Intel Rack Scale Architecture and software-defined
infrastructure, technology leader Ericsson developed a data center solution — Ericsson Hyperscale
Datacenter System 8000 — that brings the benefits of hyperscale computing to enterprises in a
commercially available solution. For the first time, enterprises can deliver cloud computing
performance and manageability on par with hyperscale leaders Google, Facebook and Amazon.
As discussed above, traditional data centers typically build dedicated infrastructures for each workload.
Server virtualization has helped break down some of these silos, but in practice this technique can only
be applied to a portion of enterprise workloads. Many enterprise applications, for example, are too
costly to virtualize, while other legacy applications can present performance and tuning challenges
GOING HYPERSCALE
Hyperscale is the ability of
an architecture to scale by
seamlessly adding compute,
memory, networking, and
storage resources to
accommodate increasing
volumes of data and work-
loads. Hyperscale computing
is often associated with
cloud computing and the
very large data centers
owned by Facebook,
Google and Amazon.
1.0
1.26
Network
Network Utilization1
(Traditional vs. SDN Indexed)
26% improvement in
Network Utilization
Sources:
1Juniper Networks & Wakefield Research Survey for 400 U.S.-Based IT Decision Makers, 2014
2Traditional DC benchmark based on 2014 Data Center Efficiency Assessment, NRDC; Google/Facebook benchmark based on extensive
Mainstay and Ericsson research (see endnote #7 for a full list of sources)
3
Delfina Eberly, Director of Datacenter Operations, Facebook
15%
Traditional DC Hyperscale DCTraditional DC Hyperscale DC
65%
CPU
CPU Utilization2
(Traditional vs. Google/Facebook)
4x improvement in CPU Utilization
(2x vs. virtualized workloads)
300
Traditional DC Hyperscale DC
5,000
Servers/Admin
Servers per Admin Resource3
(Traditional vs. Google/Facebook)
10x+ improvement
in Resource Scaling

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in virtualized environments. In addition, the performance of certain business-critical workloads —
particularly high-speed, revenue-generating, and customer-facing applications — can suffer from
the overhead latency effects of virtualization, and are excluded for that reason.
Ericsson Hyperscale Datacenter System 8000 overcomes these limitations by creating a pooled set of
physical layer infrastructure components to support the virtualized and application layers, enabling
businesses to flexibly support the dynamic demands of heterogeneous workloads. Administrators
use management software — the HDS Command Center portal (or via APIs to an existing enterprise
management system) — to define the optimal infrastructure components for each workload. Figure 3
compares a traditional data center architecture with the Ericsson platform, showing the advantages
of deploying a centralized and homogenous bare metal layer of resources managed by a centralized
software controls system (HDS Command Center) across all workloads.
Figure 3. Traditional data center vs. Ericsson Hyperscale Datacenter System 8000 higher utilization
Higher Utilization
The ability to rapidly match workloads with hardware components in a common pool of bare-metal
infrastructure enables data centers to increase the average utilization of components. Our research
indicates that system administrators could routinely maintain server utilization rates of approximately
60% across most workloads.7
Legacy
Workloads
OS
Network
Servers
Disk
OS
Network
Servers
Disk
Specialized
Workloads
Traditional Data Center Infrastructure Architecture
Virtualization
OS
Network
Servers
Disk
Virtualization
OS
Network
Servers
Disk
Business-Critical
Workloads
OS
Network
Servers
Disk
Legacy
Workloads
CPU
Pooled Hardware Components
Operating System Operating System
Memory Disk Network
IaaS (e.g., Openstack, VMWare)
Command Center Portal
Disk
Specialized
Workloads
Ericsson Hyperscale Datacenter System 8000 Infrastructure Architecture
Disk
Business-Critical
Workloads
• Siloed workload infrastructure
• Heterogeneous bare-metal complexity
• Virtualization only applicable for
select workload segments
• Pooled workload infrastructure
• Homogeneous bare metal components
• Utilization improved across workloads

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We found three critical drivers of utilization improvements. By replacing the “procure-to-provision”
planning process with a streamlined, software-defined “pool-to-provision” planning process (see next
section), system administrators can better match infrastructure to workload demands, removing the
overprovisioning allowance that is prevalent in current workload planning decisions. In our discussions
with data center experts, we found this driver could improve utilization by up to 60%. Another utiliza-
tion booster is the ability to dynamically allocate CPU resources across servers and racks, allowing
administrators to quickly migrate resources to address shifting demand. We found this can drive
100–300% greater utilization for virtualized workloads and 200–600% for bare-metal workloads.
Finally, HDS Command Center’s open platform approach allows data center operators to manage
their entire data center infrastructure (other vendor solutions as well as Ericsson) through a single
portal. This enables system administrators to identify opportunities to allocate infrastructure to multiple
workloads, improving utilization by up to 50%. For example, infrastructure used to support Workload A,
which experiences peak demand during the day, could be shifted to Workload B, which experiences peak
demand during the night. The visibility and reporting capabilities of HDS Command Center also allow
operators to audit all infrastructure components, enabling them to locate under-utilized “ghost servers”
(those not procured or managed by IT) and bring these resources under IT management. By leveraging
the management and reporting capabilities of HDS Command Center, data center operators could
improve utilization by up to 10%, our research shows. Figure 4 summarizes the range of utilization
improvements that could be achieved by implementing the Ericsson Hyperscale Datacenter System
8000 platform.
Figure 4. Summary of Utilization Improvements
Utilization
Improvement
Driver
Ericsson Hyperscale
Datacenter System
8000 Impact
Virtualized and
Bare Metal Workload
Improvement Improvement Driver Description
“Pool-to-
Provision”
Planning
Process
Impact
Up to 60% Virtualized Impact —
0.25X improvement
in utilization
Bare Metal Impact —
0.5X improvement
in utilization
Traditional “procure-to-provision” processes
combined with high availability and other per-
formance considerations drive overprovision-
ing for infrastructure. The Ericsson system
streamlines this process, creating a “pool-to-
provision” capability, including auto-provision-
ing, that better matches infrastructure
requirements with workload demands.
CPU
Re-provision-
ing and
Infrastructure
Tuning
1X – 3X for virtualized
servers
2X – 6X for bare-metal
(non-virtualized)
servers
Virtualized Impact —
1.5X improvement
in CPU utilization
3X improvement
in CPU utilization
HDS Command Center software-defined
infrastructure management enables simple
CPU re-assignment, maximizing the utilization
of available resources across workloads
(e.g., Workload A is not meeting planned
demand metrics so infrastructure is moved
to Workload B).
CPU Multi-
Provisioning
Up to 50% Virtualized Impact —
0.25X improvement
in utilization
0.5X improvement
in utilization
With the Ericsson system’s greater automation,
monitoring, and resource discovery capabili-
ties, ghost servers can be eliminated.
The hyperscale platform also allows for
re-allocation of resources across multiple
workloads that are migrated based on need
(e.g., Workload A during peak daytime hours;
Workload B during peak nighttime hours).
Ghost Servers
Discovery and
Avoidance
Up to 10%
AVERAGE 2X (virtualized)
4X (non-virtualized)
Based on the drivers above, we modeled the
median of each factor, which gets us to
approximately 2X CPU utilization improvement
for virtualized workloads and 4X CPU
improvement for non-virtualized workloads
*Please note that all these factors will vary
based on the unique operating practices of
the enterprise data center.

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By contrast, server utilization rates for traditional data center workloads typically range between 6%
and 15%, with hardware virtualization benchmarks averaging closer to 30%.8
Whether applications
are virtualized or running on bare metal, the ability to pool infrastructure at the component level
using the Ericsson Hyperscale Datacenter System 8000 platform creates a homogeneous data center
infrastructure across all workloads.
Optimized Data Center Infrastructure Management: From “Procure-to-Provision”
to “Pool-to-Provision”
Ericsson’s software-defined data center platform will modernize the way operators manage
infrastructure planning and procurement. The focus of planning cycles, for example, will move
from procuring infrastructure for individual workloads (“procure-to-provision”) to managing the
disposition and deployment of the data center’s entire of pool of hardware (“pool-to-provision”).
This shift to more holistic planning will eliminate traditional over-provisioning practices and enable
rapid reallocations based on actual usage patterns. To effectively manage the new planning approach,
operators may find they need to modify their organizational structures somewhat, relying less heavily
on individual component solution specialists (server, storage, and networking experts) and more
heavily on cross-component designers and SDI experts.
INSIDE THE ERICSSON HYPERSCALE DATACENTER SYSTEM 8000 PLATFORM
Ericsson’s new platform introduces unique capabilities to enable companies to build a software-defined
hyperscale data center.
• Resource pooling. Leveraging RSA, Ericsson’s platform reinvents the way system administrators
provision, manage and monitor data center infrastructure assets through the pooling of infrastructure
components. Resource pooling results in significant improvements in asset utilization.
• HDS Command Center. This system management portal gives IT administrators full visibility into all
data center infrastructure elements (including non-Ericsson system elements via APIs) and enables
composing a system using pooled resources that include compute, network and storage based on
workload requirements. Command Center also provides auto-provisioning, real-time performance
tracking, and triggers to adapt to workload shifts.
• HDS Optical Backplane. Ericsson’s state-of-the-art optical interconnect removes the traditional
distance and capacity limitations of electrical connections, enabling maximum pooling of resources
and flexibility in physical placement of data center assets, while increasing the lifespan of racking
chassis and cabling by 3-4x.

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BUSINESS IMPACT AND TCO ANALYSIS
What specific benefits and savings can businesses expect to achieve if they implement the Ericsson
Hyperscale Datacenter System 8000 platform? Our analysis, based on extensive discussions with data
center engineers and industry experts, estimated a range of impacts spanning three key business-value
categories, as summarized in Figure 59
:
Figure 5. Ericsson Hyperscale Datacenter System 8000 Economic Value Tree: Impact Categories
Estimates of TCO and business impact will vary depending on the existing maturity and operating
practices of the enterprise data center being studied. To simplify our analysis, we used third-party
benchmarks to estimate the current operating practices of data centers today. For example, virtualization
of enterprise data centers has helped to drive additional cost savings and higher efficiencies but our
research has found that the range of virtualization can vary from 25% to 75% of data center workloads.
Operating Expense (OPEX) Savings
Our analysis showed that the Ericsson Hyperscale Datacenter System 8000 solution offers clear
opportunities for reducing operating costs. These drivers of OPEX savings can be grouped into
five categories, as shown in Figure 6 and summarized below.
Figure 6. Ericsson Hyperscale Datacenter System 8000 economic value tree — OPEX savings
Capital
Expense
(CAPEX)
Savings
Benefit Category Benefit Description Business Impact
Workload efficiencies reduces
software license support costs
Optical Backplane simplifies deployment
and increases rack lifespan by 3x+
SDI scales key management activities
across all components
Increases utilization + improves data center
density, maximizing PUE
Reduced Software
License Support Costs
Data Center Reduced
Footprint OPEX
Deployment
Administrative Savings
Simplified System
Admininstration Processes
Reduced Cooling/Power
Consumption
Higher density and capacity utilization
reduces facility costs
Operating
Expense
(OPEX)
Savings
Increasing utilization of CPUs by pooling components
and advanced capacity management practices
Increased storage efficiency gained from erasure
coding storage dispersal management approach
Increased Capacity Utilization
of Server/CPU infrastructure
Increased Storage Efficiency
of Unstructured Data
Revenue and
Other Strategic
Impacts
Operating Expense
(OPEX) Savings
• System administration savings via Command Center workload lifecycle management
• Power savings from improved asset utilization, density, PDU architecture
• Optical backplane wiring and lifecycle cost savings
• Server/CPU consolidation and improved utilization reduces component costs
• SDN Architecture + Ericsson hyperscale networking solution reduces cost per port
• SDS Architecture + Ericsson hyperscale storage solution reduces total capacity required
• Facility infrastructure density improvement
• SDI agility to migrate infrastructure reduces total capacity requirements
• Enable revenue generating services
• Deliver Networked Society strategic opportunities
• Create “infrastructure on tap” or “AWS-like” asset nimbleness
• Improve “green” data center measures
Capital Expense
(CAPEX) Savings

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• Physical deployments savings. Ericsson’s innovative racking
system, combined with the efficiency improvements delivered by
HDS, can significantly reduce infrastructure physical deploy-
ment costs per year. Our analysis showed that these savings
could reach as high as 74% over traditional physical deployment
annual costs, as shown in Figure 7. The savings are driven by the
platform’s advanced optical backplane technology, as well as
greater CPU utilization which together dramatically reduce the
hardware and the labor required to build and maintain racks and
increases the average lifespan of racks from about 3 years to 10
years or more. Further, Ericsson’s high-utilization, component-
based architecture changes the traditional approach of re-racking
and re-cabling after each systems-replacement cycle (every 3 to
5 years). The Ericsson Hyperscale Datacenter System 8000
platform allows data center operators to maintain the existing
optical backplane rack and cabling and replace component sleds
into that racking system, reducing effort and minimizing costs.
• Simplified system administration. Companies, especially large
enterprise-scale data center operators, will realize significant
labor productivity savings using Ericsson’s command center
software to streamline the management of data centers. Common
system administration tasks such as monitoring, notifications,
quota management and resource allocation, ghost server discov-
ery, and provisioning across workloads are now automated and
orchestrated by HDS Command Center. Further, because the data
center is now managed as a homogeneous infrastructure, fewer
component and vendor experts are required. As a result, our
research indicates that large data center operators can expect to
reduce system asset management tasks and reduce FTE require-
ments by as much as 94% for managing storage, server and
networking environments, as shown in Figure 8.10
• Power and cooling savings. Our research shows that Ericsson’s high-utilization platform will enable
data centers to operate with substantially less physical infrastructure, as detailed in the section on
CAPEX savings. Based on these estimates, the average data center could reduce overall power and
cooling costs up to 72%.11
• Reduced software licensing and support costs. As organizations boost component utilization and
cut back on data center hardware — particularly CPUs — the cost of software licensing would fall
proportionally. Based on our earlier estimates, companies could realize as much as a 30% reduction in
ongoing virtualization software license costs.12 However, these savings are offset by software license
investments in HDS Command Center Software. Our analysis found that this TCO category would be
a net investment for operators.
• Lower real estate costs. In most cases, real estate cost savings will take the form of cost avoidance as
companies find they can accommodate growth more efficiently and thus use existing data center space
longer. Ericsson’s optical backplane also facilitates better space utilization, allowing for more flexible
Figure 7. Ericsson Hyperscale
Datacenter System 8000:
Physical deployment cost savings
Figure 8. System administration
management savings
1.00
Traditional Ericsson
Hyperscale
0.26
Physical Deployment Costs*
(60-Rack Data Center — annual spend)
* Assumes a 60-rack scale data center with
electrical, standard rack architecture;
Savings derived from: 1. Increased lifespan of
Optical Backplane; 2. Reduced footprint from
improved capacity utilization; 3. Reduced
footprint from less over-provisioning; and
4. Simplified cabling requirements.
35
Hyperscale
2
Infrastructure System Administrators*
(at 60-Rack Data Center)
* Assumes Ericsson system best practices,
unified infrastructure simplification, and
SDI benefits are achieved

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placement of racks. Our analysis estimates that by switching to Ericsson’s hyperscale infrastructure,
the typical enterprise could reduce its data center footprint by up to 50%.
Capital Expenditure (CAPEX) Savings
Ericsson’s hyperscale cloud solution can help companies significantly reduce or avoid data center
capital expenditures as each component of the data center becomes more efficient and easily scalable.
Figure 9 details the range of capital savings companies can potentially realize.
Figure 9. Ericsson Hyperscale Datacenter System 8000 economic value tree — CAPEX savings
• Server CAPEX savings. As enterprises shift workloads to Ericsson’s software-defined infrastructure,
they can expect to reduce capital expenditures on servers (CPUs) in line with our earlier 2-4x utiliza-
tion improvement estimate. In estimating the total savings potential for an enterprise data center with
75% virtualized workloads, we calculated a 65% TCO savings for server-related CAPEX spending.
Companies can also economize on CPU costs by optimizing how they are deployed in the hardware
pool. For example, as a CPU ages and newer components are brought online, administrators can
match older components to less critical workloads, extending the average life of a CPU from three
to five years, according to data center experts we interviewed. Many companies will see additional
savings in lower software license costs tied to CPU cores or sockets.
• Storage savings. By employing an advanced erasure coding storage
algorithm, Ericsson Hyperscale Datacenter System 8000 storage
minimizes the replication of unstructured data across the data center,
enabling cost reductions in disk storage by as much as 35% (Figure
10). In addition to lowering physical disk CAPEX, the enterprise
should also see reductions in storage-related software license costs.
• Network CAPEX savings. Ericsson’s software-defined networking
topology, combined with the physical advantages driven by its optical
backplane racking solution, will increase the overall efficiency and
effectiveness of the data center’s physical switch infrastructure,
enabling capital cost reductions in this area. In addition, our analysis
Figure 10. Traditional vs.
Ericsson hyperscale platform’s
unstructured data storage
3.6
Hyperscale
1.7
Amount of Storage Required for
Similar Workloads in Petabytes
Capital
Expense
(CAPEX)
Savings
Workload efficiencies reduces
software license support costs
Optical Backplane simplifies deployment
and increases rack lifespan by 3x+
SDI scales key management activities
across all components
Increases utilization + improves data center
density, maximizing PUE
Reduced Software
License Support Costs
Data Center Reduced
Footprint OPEX
Deployment
Administrative Savings
Simplified System
Admininstration Processes
Reduced Cooling/Power
Consumption
Higher density and capacity utilization
reduces facility costs
Operating
Expense
(OPEX)
Savings
Reduced CPUs per workload lowers operating
system license purchase requirements
Increasing utilization of CPUs by pooling components
and advanced capacity management practices
Increased storage efficiency gained from erasure
coding storage dispersal management approach
Reduced spend by moving to a fabric/SDN solution
increasing utilization with commodity components
Reduced Operating
System Licenses
Reduced Virtualization Licenses
(e.g., Hypervisor)
Increased Capacity Utilization
of Server/CPU infrastructure
Increased Storage Efficiency
of Unstructured Data
Reduced Network Costs by
Fabric-Based Approach
Reduced CPU per workload lowers the virtualization
software license purchase requirements
Strategic
Impacts

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shows that network-layer savings will increase exponentially as the scale and complexity
of the data center increases.13
• Power and cooling equipment savings. A side benefit of migrating to Ericsson’s streamlined
infrastructure is a corresponding reduction in the amount of power backup systems and cooling equip-
ment required. Since these savings are likely to represent only a small portion of overall cost savings,
they are documented here for completeness but not included the TCO calculations that follow.
Revenue and Other Strategic Impacts
Although the specific purpose of this study was to detail the potential TCO savings of the Ericsson
hyperscale platform, our research and discussions with data center and industry experts also uncovered
a range of strategic and revenue-generating opportunities that enterprises could capture when they are
equipped with hyperscale data center capabilities. Although the sheer diversity and unpredictability of
these opportunities makes it impossible to quantify for the average company, they may well represent
the greatest potential source of value for many enterprises, especially those seeking business transfor-
mation through digital initiatives.
For example, a hyperscale platform like Ericsson’s is ideally suited for enabling IoT and Big Data
initiatives, both of which require massively scalable compute, networking and storage capabilities.
McKinsey estimates that the IoT could have a total economic impact of $11.1 trillion per year by 2025,14
the equivalent of 11 percent of the world economy. However, to exploit IoT opportunities, data centers
will need to bring new capabilities into play, such as enabling interoperability and the ability to analyze
huge volumes of data. Ericsson Hyperscale Datacenter System 8000 makes all of this possible and at a
lower cost basis than the competition. For “hyperscale-enabled” companies, billion-dollar opportunities
become addressable markets.
Other capabilities enabled by the Ericsson hyperscale platform, such as rapid workload provisioning,
optimal hardware utilization, and better infrastructure visibility and manageability, will enable enter-
prise data centers to provide services comparable to what’s available from public cloud providers such
as AWS. Furthermore, by increasing data center density, conserving space, and improving power usage
effectiveness, or PUE, the Ericsson hyperscale platform will help companies meet environmental
sustainability goals, an important strategic priority for many companies.
5-YEAR TCO IMPACT FOR ENTERPRISE DATA CENTERS
What is the total economic benefit enterprises could gain from implementing Ericsson Hyperscale
Datacenter System 8000 in a typical data center? To estimate the impact, we created a total cost of
ownership (TCO) model, factoring in the range of value drivers described in the previous section. The
model analyzes operating scenarios for three sizes of data centers: small (1 rack), medium (6 racks),
and enterprise-scale (60 racks), recognizing that infrastructure components can vary greatly in each
case depending on industry, geographic coverage, the types of applications being run, and other factors.

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TCO and ROI Summary
The results of our TCO analysis are clear: Enterprise data centers that adopt the Ericsson Hyperscale
Datacenter System 8000 platform can expect to capture significant savings — as much as 55% in
CAPEX savings and 75% in OPEX savings for a 60-rack data center (see below for more details on our
TCO modeling), with an estimated overall TCO savings of 63%. This translates into an estimated ROI
of 138% over five years.
One of the key drivers of TCO savings is greater CPU utilization, which allows for the deployment of
fewer servers and CPUs, less network hardware, and less storage disk. The Ericsson platform’s ability
to transform the “procure to provision” process into a vastly more efficient “pool to provision” process
enables more frequent, collaborative planning efforts that help avoid over-investment in infrastructure.
For these utilization and labor efficiencies to be fully realized, however, organizational changes may
be required to facilitate collaborative planning across departments and optimize compute, storage and
network capacity.
Ericsson’s Optical Backplane solution drives more efficient cabling, resulting in fewer cables procured
and ease of physical deployment resulting in lower OPEX spending. The automation and orchestration
with HDS Command Center, results in being able to scale up the amount of infrastructure managed
per systems administrator. Less infrastructure additionally reduced power and cooling, software licenses
and hardware and software support costs.
Figure 11 summarizes the estimated magnitude of cost savings and ROI that could be achieved at
different scales of deployment. Figure 12 shows a more detailed breakdown of savings by data center
cost category.
Figure 11. Ericsson Hyperscale Datacenter System 8000: Summary of estimated savings and ROI (five years)16
Figure 12. Full comparison of TCO cost elements
Cost Element
Scale of Deployment
60 Racks 6 Racks 1 Rack
Hardware CAPEX 59% 57% 53%
Software CAPEX 30% 29% 29%
Hardware OPEX 44% 41% 35%
Software OPEX* 30% 29% 29%
System Administration OPEX 94% 75% 0%
Power, Cooling and Space OPEX 62% 62% 36%
*Software OPEX does not include investment in licensing costs for HDS Command Center software.
Financial Category
Scale of Deployment
60 Racks 6 Racks 1 Rack
CAPEX Savings 55% 53% 50%
OPEX Savings 75% 62% 0.4%
Total Cost of Ownership (TCO) Savings 63% 57% 26%
Return on Investment 138% 109% 29%

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Figure 13 shows the 5-year economic impact of moving to Ericsson Hyperscale Datacenter System
8000 at a hypothetical 60-rack data center currently operating in a non-hyperscale environment.
Figure 14 depicts the relative percentages of each type of savings. See Figure 15 in the Appendix for
additional notes and calculations on each category of savings and investment cost.
Figure 13. 5-Year TCO Impact Summary (60-rack data center)
Figure 14. Ericsson Hyperscale Datacenter System 8000: Savings by cost category
TCO Model Approach and Assumptions
To establish realistic assumptions and benchmarks used in the model, we worked closely with data
center and industry experts, including operators at Fortune 500 companies, and took a conservative
view of the potential cost savings of the Ericsson hyperscale platform. For example, wherever possible,
we have assumed a conservative basis for calculations, such as using discounted “market” prices for
hardware and other components.
MORE CAPACITY…
Assuming equivalent
hardware, Ericsson
Hyperscale Datacenter
System 8000 can deliver
double the compute capacity
of a traditional data center.
AND LESS TCO…
A 25% improvement in
data center asset utilization
can translate into a 10%
TCO savings.
Hardware Capital
47%
System Administration
39%
Software Support
<1%
Hardware Support
1%
Power, Cooling and Space
10%
Software Capital
3%
Current
(non-HDS)
TCO
Hardware
Capital
Cost Savings
Software
Capital
Cost Savings
Note: the Ericcson Hyperscale Datacenter System 8000 is abbreviated as “HDS” in this table.
Hardware
Support
Cost Savings
HDS
Investment
System
Administration
Effort Savings
Power, Cooling
and Space
Cost Savings
Ericsson
Platform
TCO
Savings Investment
$63,565,634
$19,878,060 $1,326,353
$2,205,000
$16,500,000
Software
Support
Savings
$84,887
$3,953,774
$23,551,384
$476,176

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For the same reason, we chose not to include the potential revenue or strategic benefits that might result
from providing the enterprise with greater agility, speed or environmental sustainability, as outlined in
the previous section. Although these benefits could be substantial, even exceeding the other categories
of benefits, we judged them to be too variable and unpredictable to include in the TCO model.
The relative percentage of virtualized vs. non-virtualized (or bare metal) workloads can vary on a case
by case basis. We chose to present a conservative view of the impact by assuming that 75% of the
workloads had already been virtualized, thus using a relatively efficient baseline for our analysis.
Based on our research, we set the average CPU utilization in non-virtualized environments at 15%,
and virtualized environments at 30%. Because of the Ericsson platform’s superior resource pooling
and disaggregation capabilities, its utilization rate was set at 60%, which is consistent with performance
levels achieved at leading hyperscale data centers.
The TCO analysis covers a 5-year period and factors in the depreciated costs of the infrastructure.
The following CAPEX elements were considered: server hardware, storage HW, network hardware,
cable hardware, physical deployment effort, virtualization software, management software. The
following OPEX elements were considered: hardware support, software support, HDS Command
Center software support, system administration, power and cooling, and space utilization.
Our analysis assumed a greenfield approach to implementing the Ericsson platform. In our model, the
compute-storage-network environment is completely converted to the Ericsson hyperscale platform on
Day One and compared to a traditional, non-hyperscale operating model. Since the infrastructure is
assumed to be fully-depreciated, there is no time-lag or phasing of impacts. A phased approach model
would need to be created for cases that are not greenfield implementations. Our recommendation is to
use the framework, benchmarks and research provided in this paper as a “starter kit” to develop a custom
ROI analysis that takes into account the unique features and opportunities of your individual data center.
THE JOURNEY TO HYPERSCALE
For most enterprise IT organizations, moving to an Ericsson hyperscale platform won’t happen overnight.
In reality, it will be more of a journey than a flip of the switch. Enterprise data center management will
be tasked with not only transforming the physical architecture of the data center, but also changing
work processes and job descriptions in order to maximize TCO savings — a process that will likely
take months, if not years.
EARLY RESULTS: GOING HYPERSCALE AT ERICSSON’S STATE-OF-THE-ART DATA CENTER
Ericsson is committed to being its first and best customer with its hyperscale data center platform. As part of its 2016 IT planning efforts,
Ericsson has prioritized its engineering systems infrastructure as the best place to start. In our interviews, IT executives explained that the
Ericsson Hyperscale Datacenter System 8000 solution was particularly well suited for the engineering systems environment given the very high
CPU demand of its application workloads.
Executives said that the platform’s HDS Command Center will help the IT team more effectively manage the infrastructure and meet the unique
requirements of its engineering applications. With Ericsson’s hyperscale platform, the IT team is expected to achieve an estimated 400%
improvement in system utilization across more than 30,000 servers.
The team expects to launch the hyperscale project in 2016 and then expand the platform’s capacity over several years. Results from the
project will be analyzed and shared widely within the company to help improve the product for internal users as well as Ericsson’s customers.

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In most cases, enterprises will be best served by following an incremental approach to hyperscale
transformation. That could mean starting with a pilot on a selected workload in order to demonstrate
the benefits of pooling resources and delivering “infrastructure on tap.” Another initial step, which
Ericsson itself took internally, is to leverage the audit capabilities of the HDS Command Center
to gain full visibility into the utilization of the existing infrastructure and find dormant or shadow
infrastructure that may be unknown or poorly leveraged. This activity can provide an early return by
eliminating dormant or underproductive assets.
After successfully proving the platform’s capabilities in the pilot, most organizations will be ready to
plan for a wider rollout. Ericsson, for example, decided to leverage the visibility gained from its HDS
Command Center audit to identify areas of the data center that could benefit most from the hyperscale
platform and then start the deployment there (See callout: “Early Results: Going Hyperscale at
Ericsson’s State-of-the-Art Data Center”).
Capital depreciation schedules will likely influence the pace of change, since most companies will
want to avoid write-offs of existing equipment and prefer to phase in the hyperscale platform only
when legacy hardware has been fully depreciated. This financial constraint would suggest a three-
to five-year journey for most enterprises.
Considering the comprehensiveness of Ericsson’s hyperscale platform and its potential for transforming
the business, companies should take advantage of Ericsson’s experts in their planning efforts. This
could include the development of a multi-year business case, a phased implementation approach, and a
technical design evaluation that explores the range of opportunities for leveraging this next-generation
data center architecture.
About This Study
Research and analysis for this study was conducted by Mainstay, the leading IT management
consulting firm focused on quantifying and communicating the business value of technology. This
study was based on reviews of primary research and interviews with business and IT executives at
Ericsson and numerous industry leaders, including experts from one of the world’s largest systems
integrators; a data center architect with experience in server and storage virtualization, provisioning
and networking, and storage management; and an executive from a leading gaming and entertainment
company with experience in data center virtualization and performance. TCO and ROI calculations
use industry standard assumptions regarding the time value of money. For more information about the
study’s methodology and model assumptions, see Figure 15 in the Appendix. Information contained in
the publication has been obtained from sources considered reliable, but is not warranted by Mainstay.
About Mainstay
Research and analysis for this study was conducted by Mainstay, a leader in quantifying and
communicating the value of business and technology investments. Mainstay serves as an independent
advisor to eight of the top ten global high-tech companies.

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Appendix
Figure 15. Comparison of non-HDS and HDS environments and cost calculation methodologies
(Note: the Ericcson Hyperscale Datacenter System 8000 is abbreviated as “HDS” in this table.)
Non-HDS Servers HDS Servers
Non-HDS environment has 60 racks, which have 900RU/servers
(and 3600 ports). Price per server is multiplied by total number
of servers and depreciated. During refresh cycle, 20% of the
server hardware can be reused, therefore 80% of new server
cost is applied to year 5.
CPU utilization improves by 2x for virtualized server workloads,
from 30% to 60% utilization. For non-virtualized the improve-
ment is 4X, going from 15% to 60% utilization. The weighted
average improvement is 2.5X for the 75% scenario modeled in
this analysis. The 900 legacy servers are reduced to 394RU.
For physical deployment efforts (racking/stacking), we considered
2 FTE x 10 hrs per server + installation + other hardware and
software deployment activities (e.g., testing: 2 FTE x 70 hours per
physical server). These costs are depreciated in the model.
Physical deployment of HDS requires 2 FTE x 5 hrs per server.
Installation plus other hardware and software deployment
including testing is estimated at 2 FTE x 40 hours per physical
server.
Non-HDS Storage HDS Storage
Centralized storage, 7.2k HDD (72 TB / 1 RU), 250W
Centralized storage, 10k HDD (24 TB / 1 RU), 250W
Centralized storage, SSD (40TB / 1RU), 250W
Total of 230RU make up 10 PB (i.e.,130 of SSD + 50
of 10K+ 50 of 7.2k)
Assuming that 70% of this storage environment is unstructured
data, HDS software-defined storage provides 50% reduction in
replication of unstructured storage, resulting in a 35% savings.
Non-HDS Network HDS Network
96 port fabric interconnect switches, 950W. Total of 80
switches, with an additional 8 routers for inter-rack routing.
44 Ericsson leaf switches, 800W per switch plus EAM.
Non-HDS Cables HDS Cables
Standard 10G electrical copper cables:
Compute-Network: Assumes 4 10G ports are connected.
90U x 4 port x price per cable
Storage-Network: 23 U x 2 ports x price per cable
Intra-Network: 8 U x 2 ports x price per cable
Ericsson optical cabling:
CSU-NSU: Per server price per cable, assuming 4 10G ports
are connected. 394U x 4 port x price per cable
SSU-NSU: 150U x 2 ports x price per cable
NSU-NSU: 44U x 1.5 ports x price per cable
Virtualization Software: Non-HDS Virtualization Software: HDS
Virtualization/Hypervisor Software (75% of the environment is
virtualized x 900 physical servers) priced per CPU.
75% of environment x 900 servers x 2 CPUs.
Number of servers reduced to 394RU; this expense is reduced
by fewer CPUs.
Management and Orchestration: Non-HDS Management and Orchestration: HDS
Assuming 15 virtual servers per physical server. Calculated at
price per virtual machine.
Expenses do not change (enterprise needs for the number of
virtual servers does not change). Note: HDS Command Center
costs are listed under OPEX.
Software and Hardware Support Costs: Non-HDS Software and Hardware Support Costs: HDS
Assumed at 8% per year (first year $0) for each hardware cost
above (server, storage, network).
Same calculation as non-HDS.
Additionally, HDS Command Center costs are considered at:
Price per box x (394U + 150U + 44 U) per year.
Systems Administration: Non-HDS Systems Administration: HDS
1 FTE per 300 virtual servers. This represents server, storage
and network administration composite resource estimation.
Ratio is increased to 5000 virtual servers per FTE.
Power, Cooling & Space: Non-HDS Power, Cooling & Space: HDS
Standard cost of power 10 c per KWH, 8736 hours total avail-
able hours per year x total wattage of servers, storage and
network. For space, each rack occupies 30 sq. ft. Data center
space cost is $310 per sq. ft. Assumes 60 racks are occupied.
Same calculation method, fewer server hardware and fewer
total number of racks reduces OPEX expenses for power,
cooling and space.
Sources for benchmarks: Recent research from Mainstay and Ericsson data center analysts and research publications from Gartner,
VMWare, Uptime Institute and IDC.

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Endnotes
1
Worldwide mobile data traffic is projected to grow at a compound annual rate of 57% for the next four years, reaching a throughput of
24.3 exabytes per month by 2019 (Source: Statistica: “Global data center IP traffic in exabytes per year, 2015).
2
“Ericsson Mobility Report: On the pulse of the Networked Society,” Ericsson, November, 2015.
3
“The enterprise IT infrastructure agenda for 2014,” McKinsey & Co, 2014.
4
“Strategic Benchmarks 2013: IT Infrastructure,” Forrester Research, May 2013.
5
Multiple sources: “The Economics of Virtualization: Moving Toward an Application-Based Cost Model,” IDC, Nov, 2009; “Chapter 20:
Data Center IT Efficiency Measures,” National Renewable Entergy Laboratory, US Department of Energy, Jan 2015.
6
Intel Rack Scale Architecture is a set of architecture guidelines and principles that are being implemented by
Ericsson and other vendors.
7
Based on interviews with leading SI data center experts, enterprise data center management, and publicly available Google and Facebook
benchmarks (see list of sources below). Administrators may choose to maintain some critical workloads at lower averages to manage spikes,
while maintaining higher rates for non-critical workloads. (Our research found that >65% utilization is possible for certain workloads.)
http://www.epanorama.net/newepa/2011/04/10/facebook-datacenter-secrets/comment-page-1/
http://www.datacenterdynamics.com/content-tracks/servers-storage/how-facebook-deals-with-constant-change/83715.fullarticle
http://www.singjupost.com/facebook-fb-presents-credit-suisse-2014-annual-technology-conference-transcript/
http://www.vmware.com/solutions/consolidation.html
http://www.slideshare.net/dellenterprise/forrester-the-economic-impact-of-server-virtualization
http://ieeexplore.ieee.org/document/6529276/?reload=true
http://www.slideshare.net/sgurnam73/server-virtualization-by-vmware
https://www.linkedin.com/pulse/grace-hopper-2015-jade-chu?articleId=6062981612944056320
https://turbonomic.com/blog/on-turbonomic/optimal-cpu-utilization-depends/
8
Based on the diversity of workloads in data centers, we are assuming (based on available research) that a best-in-class data center may have as
high as 60–75% of their workloads virtualized today. To be conservative, the analysis assumed 75% of the workloads are virtualized, leading to
a 69% improvement in server utilization across the data center.
9
Given that the solution has not been released commercially at the time of this paper, all quantifications of impact are estimates based on available
research and assumptions made in concert with the experts interviewed.
10
These savings are dependent on enterprise data center operators transforming the people, process and technology practices as described in this piece.
11
Assumes $0.10 per KWH @ 8,736 hours per year; wattage per component (storage, network, server) estimated based on available benchmarks;
assumes rack occupies 30 sq. ft. of data center space at $310/sq. ft.
12
Data center infrastructure TCO includes software license costs and annual support costs for operating system software, virtualization software,
disaster recovery software, and the like.
13
This is due to two major factors: (1) As the complexity and requirements for the network increase the costs of the switching environment grow
exponentially; (2) The fabric-based network environment, coupled with the fiber-based racking environment, allow for more flexibility in how
you physically deploy the network switches into the racking environment. Due to electrical connection limitations, typical top-of-rack switches
are required to manage very dense environments. With the Ericsson hyperscale platform, these physical switches can be better utilized because
of the distance and low-latency capabilities of optical connections.
14
Mckinsey Global Institute’s June 2015 survey.
15
Cost savings are estimates are based on full adoption the Ericsson Hyperscale Datacenter System 8000 solution as well as implementing new
organizational best practices discussed earlier, such as holistic infrastructure planning that reduces hardware overprovisioning.
16
CAPEX includes: server, storage, network, cabling, power and cooling equipment hardware costs, and virtualization and orchestration software
license costs.
17
OPEX includes: server, storage, network hardware support costs, virtualization and orchestration software support costs, system administration
labor costs, power, cooling and space costs.

Mainstay
764 Valderrama Ct.
Castle Rock, CO, 80108
www.mainstaycompany.com
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