I D C
A N A L Y S T
C O N N E C T I O N
Jeff Janukowicz
Research Director, Solid State Storage
Matt Eastwood
Group Vice President and General Manager, Enterprise Platform Group
Storage Acceleration: Solving the I/O
Performance Gap Problem
September 2012
Advancements in server/CPU performance and increased use of virtual machines and computeintensive business applications are exposing a critical performance gap between enterprise servers
and storage systems. Data requirements and CPU processing power have grown rapidly over recent
years, but the performance of storage has not kept pace. Storage I/O is the bottleneck. A new class
of server-based storage acceleration is needed to address this bottleneck and bridge this important
performance gap.
The following questions were posed by QLogic to Jeff Janukowicz, research director of IDC's Solid
State Storage research, and Matt Eastwood, group vice president and general manager for IDC's
Enterprise Platform group, on behalf of QLogic's customers.
Q.
What applications, datacenter trends, and infrastructure initiatives are driving the I/O
performance gap problem?
A.
The growing number of diverse applications and the digitization of information are creating
increased demands on the infrastructure. An explosion of devices and users is making
organizations struggle to maximize performance at the system level. At the same time,
organizations are trying to lower their operational costs and maximize investment protection.
Most organizations have a complex legacy installed base, and they're faced with a shift in
how they deploy applications and consume resources. So they're virtualizing and
consolidating, which is putting more and more pressure on the datacenter and legacy
infrastructure. They're also looking at new classes of applications that can create a
competitive advantage by capitalizing on some of the macrotrends in the market, such as
mobile, Big Data, and analytics. They're trying to make a more impactful shift in their
business in terms of how they deploy technology, including clustered server architectures.
The compute power of CPUs has been growing in line with Moore's law over the past
decade, but the storage subsystem's performance has not kept up with the performance
needs on the compute side of the equation. As a result, we're seeing a performance gap
between what the processor can compute and what the storage I/O subsystem can deliver.
This performance gap is further exacerbated by the rapid growth in data volumes most
organizations are experiencing today. Virtual machine density is growing, as are I/O
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demands and workloads. In fact, IDC projects that data volumes in the digital universe will
grow by a factor of 44 over the next 10 years.
Q.
What are the business requirements driving applications to process more
transactions, lower latency, and increase response times?
A.
Businesses are being pressured to move faster than ever, and IT has historically struggled to
keep up with this shift. So you can look at this question from the perspective of both the
datacenter and the systems that live in the datacenter. If you look at the datacenter itself, a
lot of the focus is on rationalization and consolidation of facilities and on virtualizing
resources in the datacenter. Organizations are trying to implement best management
practices in their datacenters and embrace new types of automation tools, which affect the
layout of the datacenter.
But, really, it boils down to the workload. A number of workloads in the industry continue to
move into these virtualized environments, which require shared and managed storage. The
environments, in turn, are becoming much more dynamic as workloads move from one host
to another. This puts a lot of pressure on the storage ecosystem and the network. So there's
a need to start thinking more holistically about your IT resources and the various silos in your
datacenter spanning compute, storage, and networking. There's a huge focus on trying to get
better utilization out of resources as well as staff. On top of this, the world is heading toward
a future where new types of applications, such as Hadoop and Big Data analytics, are being
developed that exploit a virtually unlimited set of hardware resources available via the cloud.
This explosion in new workloads must also integrate with existing on-premises IT
applications.
Initially, the focus tends to be on performance, but there are real economic benefits to being
more balanced in your thinking around traditional compute, storage, and networking
infrastructure silos. If you can start to move these silos more in parallel, then that's a huge
competitive advantage. For example, in financial services and other markets where
technology is thought of as a strategic differentiator — even as a critical element of the
business itself — time to decision is crucial. Firms will always look at anything they can do to
move faster than the other guy because that's an advantage to their core business. More and
more customers consider time to value as part of their IT decision making, and time is
typically measured in terms of speed and flexibility.
Q.
How are companies addressing the I/O performance gap problem, and what are the
advantages/limitations of each method?
A.
Companies are looking at a number of different approaches to solve the I/O performance gap
problem. The difference in each approach depends on what issues companies are trying to
solve and where they want to implement those solutions in their infrastructure. For example,
one approach is tiering or caching with solid state technology in the storage array, which has
some advantages in terms of increasing performance. We're also seeing the emergence of
all-flash arrays, as well as some caching appliances that help mitigate the performance gap.
Yet, these solutions do not necessarily bring the most active data any closer to the CPU or
application.
More recently, there's been a movement toward a server-based caching solution. The idea
with this approach is to take advantage of the intrinsic benefits of solid state technology and
move the data onto higher-performance media of solid state closer to the processor. By
leveraging this method, you narrow the performance gap considerably by improving
performance and reducing latency.
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©2012 IDC
This approach typically adds some complexity and has limitations — deciding what needs to
be cached versus what doesn't need to be cached, managing multiple device drivers in a
virtualized environment (i.e., drivers in every guest OS to manage), and the lack of
coordinated caching across multiple servers in an application cluster. However, the
technology is evolving and the hardware solutions continue to mature. The reality is that flash
is the ideal technology to use in terms of the memory/storage hierarchy to solve the I/O gap
in a way that is nondisruptive to both the application and the underlying infrastructure. It fits
very nicely from a performance perspective and a cost perspective.
Q.
For architectures such as a clustered server configuration, what are the ways to move
beyond the limitations of current solutions while keeping current implementations in
operation?
A.
Clusters or grids are a fascinating area where typically the objective is to execute compute
functions as fast as possible. In many ways, they're a lot like what happens in the highperformance computing or technical computing space. It's all about throughput. So anything
that can be done to help the existing systems do their work faster is welcomed.
There are hybrid-type architectures to increase acceleration, such as offload engines that can
move data through the path faster. They free up resources on core processors to focus on
the compute functions and not become the bottleneck for other functions such as the I/O
path.
Organizations are constantly looking for ways to create more elasticity in their clusters so that
they can grow the cluster fairly uniformly with the output. In other words, as the workload
grows, the organization can add resources and see the benefit on the back side. Elasticity
and modularity are areas of focus.
Organizations are also focused on investment protection. They are always looking for ways
to maximize what they get out of the environment over its life cycle — and they're willing to
invest in that infrastructure to add capabilities and technologies that will actually help these
systems run faster and extend the useful life of their investment.
Q.
How do you plan and implement this type of latency-improving architecture, and what
are the benefits?
A.
In the past, to improve I/O performance and improve latency, datacenter managers looked to
using more DRAM memory, short-stroking their hard drives, or striping across multiple HDDs.
However, with solid state, flash-based SSDs become highly available and, more important,
become cost effective due to advancements in solid state technology. Organizations are now
looking at using solid state storage as a latency-improving architecture.
A server-based caching approach with a shared cache pool across multiple servers provides
a level of high availability in the form of a data cache. This approach also provides flexibility
to the hardware platform, which is key. Organizations want to deploy enhancements to their
infrastructure that don't require any touching of the application or the data itself. They're
looking for things that can be added to the core server, or added to the core storage array,
but that don't require any rewrite of the application. Clearly, anything that can be done in that
area will be seen as a huge benefit.
Ultimately it comes down to four key benefits: agility, elasticity, flexibility, and simplicity. It's
about taking an organization's existing investments and allowing a very seamless upgrade
path, which results in accelerating the overall system performance. These benefits extend to
applications that historically have been viewed as scalable workloads, such as databases or
©2012 IDC
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business process management, versus something that might be happening on a Web site or
in the analytic space. But both of those scenarios can benefit from server-side caching.
Moreover, when you consider the trends of consolidation, virtualization, and automation,
each area has the challenge of trying to get the compute, the storage, and the network to
behave better together. Virtual machines, for example, are growing at an incredibly rapid
rate, and that growth is putting new kinds of pressure on the datacenter. Organizations are
always looking for new ways to accelerate performance while making that migration path
simpler to absorb.
A B O U T
T H E S E
A N A L Y S T S
Jeff Janukowicz is a research director at IDC where he provides insight and analysis on the SSD and HDD component
markets. In this role, Jeff provides expert opinion, in-depth market research, and strategic analysis on the dynamics, trends,
and opportunities facing the industry. His research includes market forecasts, market share reports, and technology trends
for clients, investors, suppliers, and manufacturers.
Matthew Eastwood is group vice president and general manager of IDC's Enterprise Platform group. He leads a team of
analysts responsible for identifying and analyzing vendor strategies and technology, market, and customer trends affecting
enterprise platforms and datacenters worldwide. In this role, he is responsible for managing market analysis, forecasting,
and consulting for servers, workstations, server and client operating environments, virtualization/cloud software, systems
management software, datacenter trends, infrastructure channels, and IT leasing and financing worldwide.
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©2012 IDC