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TRADITIONAL STORAGE ARCHITECTURES 2
MODERN COMPLEXITIES: 3
VIRTUALIZATION, SCALE OUT, AND CLOUD
HYBRID ARRAYS 9
ALL-FLASH ARRAYS 10
HYPER-CONVERGED INFRASTRUCTURES 13
STORAGE ACCELERATION 14
INFINIO’S STORAGE ACCELERATION PLATFORM 15
A GUIDE TO MODERN STORAGE ARCHITECTURES
2
decade ago, the data center was a vastly different world. Traditional
storage arrays—configured as SAN or NAS—sat as centralized storage units
accessible by multiple physical servers. The rotational speed of the spinning
media created limitations in how fast data could be read and/or written and,
when a user needed better performance, they bought another tray of disks.
From an architectural standpoint, the major innovation at the time was whether
you had a native block device with file support layered on or a native file server
layered with block storage.
The storage industry was able to keep up—for a while. Spinning disks got
faster. Advances like unified block and file enabled users to achieve efficiencies
through centralized, common management and handle multiple hosts.
Tiering—although primitive and coarse-grained by today’s abstraction
standards—enabled improvements in speed and performance.
A
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BUT THE OLD WAYS JUST COULDN’T KEEP UP.
The demands placed on the data center continued to increase. Although memory
was getting more inexpensive, adding increasingly more trays of spinning disks
was taking up more space in the data center, which increased energy usage. With
10GbE access, the pipeline expanded further, and systems needed more processing
power to manage the flood of data in both primary and backup systems, or risk
slowing data access (and the applications it supports) to unacceptable levels.
Storage in particular began feeling the impact of these changes. Performance
and capacity began to emerge as separate storage resources shackled together
but with vastly different profiles with respect to both growth and economics.
Specifically, three trends in the data center began to put pressure on
traditional storage:
VIRTUALIZATION
consolidating more
I/O onto the same
storage resources
SCALE-OUT APPLICATION
ARCHITECTURESgenerating more work as
they scale-out into available
CPU and memory
FLASHsupporting orders
of magnitude greater
performance while
requiring special processing
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VIRTUALIZATION
Traditional SAN and NAS arrays were designed for a world without virtualization.
While not new, over the past few years virtualization has had a profound impact
on storage architectures and workloads.
Simply put, server virtualization means that a single physical server can be
shared by multiple, independent virtual machines. No longer are there dedicated
LUNs for each physical application; gone too are the optimizations built for that
architecture. It’s no longer efficient to employ simplistic mechanisms to improve
the ability of drive heads to access data from a specific location.
Most companies spend $2-3 onstorage for every dollar spent onserver virtualization projects.
“
” William Blair & Co.
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SERVER VIRTUALIZATION DRAMATICALLY
CHANGED THE EFFECTIVENESS OF THIS
APPROACH IN A RANGE OF WAYS:
• Generally, servers are running more
workloads on the same number of
drives, which negatively impacts
performance. This greater number of
VMs on a single system may compete
with one another for both storage
capacity and performance.
• However, VMs that share resources
can’t take advantage of optimizations
designed for individual access
patterns — all I/O is merged, causing
the so-called “Blender Effect.”
•
Multiple VMs may require the ability todynamically shift workload movement
an operation that adds further
complexity to the data center.
• Particularly in virtual desktop
environments, synchronization
peaks around time-oriented events
(like antivirus scans or workers’
morning log-in) may result in mass-
seek overload and dull the system’s
responsiveness.
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SCALE OUT APPLICATION
ARCHITECTURESSeveral trends around scalability and workload—
the advent of cloud storage and Big Data, in
particular—have imposed changes on the way
modern applications are built and how they
access storage.
From an architectural standpoint, this is a
fundamental change from overwriting datato appending it. Because these architectures
are distributed, they rely on copies for data
protection, rather than traditional RAID. As
a result, users have to contend with both
the explosion of storage, driven by machine-
generated data, along with a new multiplier:
copies used for data protection.
In the cloud, Amazon and others have found
ways to make storage outside the datacenter
economical and attractive. These web-scale
architectures, while most appropriate for the
Facebooks of the world, are finding their way into everyone’s datacenter at a smaller scale. For
example, VMware and Oracle both have scale-out designs that are well-known and familiar.
And those are the most traditional of applications.
When you have a lot of compute in a scale-out architecture (like you do with VMware and
Oracle, for example), storage is under significantly more pressure. The same spindles must
handle increased workload compared to when they were sized 1:1 for individual scale-up
applications. The goal of these systems is to evenly and automatically distribute the data
across multiple systems. However, this efficiency comes with a price: the cluster as a whole is
processing significantly more data, putting more performance pressure on storage. Similarly,
scale-out applications in the datacenter that are starting to use replicas rather than RAID for
data protection are driving a huge amount of data capacity requirements into storage.
Users have to
contend with both
the explosion of
storage, driven by
machine-generated
data, along with
a new multiplier:
copies used for
data protection.
“
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FLASH
Enter flash-based SSD devices. Flash is a core technology that can be deployed in several ways,
such as SSDs in hosts, PCI-e cards, and SSDs in arrays. Other new architectures like NV-based
DIMMS are also emerging in this space. Because it is orders of magnitude faster (without being
analogous orders of magnitude more expensive), flash is a huge disruption in the economics of
storage.
This puts pressure on existing storage systems in a few ways. First, flash’s additional
performance capabilities drive significantly more IOPS through existing controllers than
legacy systems were designed to handle. Equally impactful to existing platforms is that flash’s
architecture often needs special handling to address particular challenges.
In this illustration, we demonstrate the relative speed of different media in the data center.
1 MINUTE 2 WEEKS 1-2 MONTHS 10 YEARS
COMPLEXITIES TO CONSIDER
Like other technologies, individual flash devices (like SSDs) have some architectural
challenges that need to be addressed, either by storage controllers or by software.
For example:
Wear Balancing Over time, flash cells wear out. It’s desirable to have them wear out at about the same time, sosome storage controllers include the logic of special algorithms to spread wear evenly across cells.
Write AmplificationFlash only allows writes to an empty cell; if a cell has content, it must be erased before it can bere-written to. Further increasing overhead is that while writes might be at the block level, erasuresoccur at the page level.
Garbage CollectionBecause cells must be empty to be written to, a cycle of “clean-up” needs to occur in order todispose of outdated data. This background process can degrade both active read and writeperformance while it occurs.
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As is often the case in the lifecycle of technology, the drivers
of the challenges users face can also be the key to the
solution. Industry leaders have leveraged the disruptors that
inspired virtualization, flash and cloud—greater speed and
CPU—to develop several distinct, innovative approaches
to balancing cost and performance. We’ll discuss these
approaches in the sections that follow.
But first, let’s take a broad look at the ways in which users have
integrated flash into their systems.
In the early days before purpose-built hybrid arrays emerged, users
handled their need for speed and performance by adding SSDs to their
existing arrays, and developing tiering strategies (eventually these were
automated) to help them best use their mix based on the level/frequency
of data access.
Similarly, some users created “all-flash” arrays by purchasing legacy
architecture arrays filled with SSD drives. However, both of these
approaches fell short in delivering the promise of flash — they didn’tleverage flash in the most effective ways, and they fell victim to make of
the complexities of flash discussed earlier. The other critical thing about
both of these approaches is this: the architecture of the datacenter and of
the storage arrays stayed basically the same.
TRADITIONAL DATA CENTER ARCHITECTURE
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Hybrid arrays represent the next mainstream generation
of disk arrays, with controllers that are better-suited to
utilize flash resources. The latest hybrid arrays use flash for
more specific tasks: as a read cache and a write log buffer
for example.
These hybrid arrays access data from either flash or from its
disk pool, but flash is not exposed directly to applications.
The goal of this storage architecture is to present an optimal
mix of flash to optimize the array’s ability to handle increased
IOPS, and spinning drives to optimize capacity utilization.
Typically used in scenarios where there is a set of mixed
enterprise workloads, hybrid arrays offer mainstream users an
option for benefiting from flash when optimizing cost is more
important than occasional latency.
The hybrid landscape continues to rapidly expand and
develop. For now, the hybrid array approach of combining
SSDs and spinning drives seems to be the new “status quo”
for organizations purchasing new arrays.
HYBRID ARRAYS
WHY HYBRID ARRAYS?
Hybrid arrays are most effective in environments with amix of general workloads where a moderate price pointis more important that guaranteed performance for allapplications.
Many customers choosing hybrid arrays are doing sowhen their environments aren’t equipped to absorb majorchanges to datacenter architecture.
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ALL-FLASH ARRAYS
The all-flash trend began with putting SSDs into existing arrays, but a range of
the complexities sparked the emergence of a new generation of storage. As we
discussed earlier, controller functions like wear leveling become imperative in
arrays leveraging flash to avoid wearing the flash cells unevenly. Similarly, space
management can be a challenge, too, since flash only writes to empty cells.
And, cleaning up storage may incur slower cycles as multiple reads and writes
execute while blocks are being erased. The newest all-flash arrays are built with
controller logic that handle these technical challenges.
Essentially, an all-flash array is like tacking a single, high performance/high
cost tier onto your existing data center. It’s not just fast, but it’s a guarantee of
fast for everything connected to it – an SLA no other architecture has yet to
promise. But while the approach is ideal for handle a high level of mission-
critical applications, it may be too expensive for many organizations. The
deduplication that all-flash array vendors tout as the key to delivering spinning-
drive economics may represent a false promise: that same deduplication can be
applied to spinning drives as well to once again separate the costs of flash and
spinning drives.
Economics aside, the reality is that many organizations do not demand that
much speed for every application.
WHY ALL-FLASH ARRAYS? All-flash-arrays are best-suited for environments where a significant chunk of applicationsneed a guaranteed level of performance — and there is a budget to support this.
While hybrid arrays may offer low-latency access for 95% of workloads, AFAs guarantee thatlevel of performance for all workloads.
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One of the most disruptive—and wildly successful—innovations to
the data center architecture is the shift to a model where storage is
processed using resources on the server-side. Server-side storage has
been implemented in multiple ways: hyper-converged, software-defined,
software services, but of these, hyper-converged Infrastructure is the first to
be gaining mainstream acceptance in the marketplace.
The key point from a storage perspective is that processing is done on the
server side. Why? Because the server is loaded with memory and processor
cores; exploiting existing, underutilized resources is IT’s holy grail.
By contrast to the dedicated storage arrays we’ve just discussed,
server-side storage processes storage across one or more servers and
is co-located with the applications it services.
The forms of server side storage vary in presentation—although not really
in the technology itself. In hyper-converged infrastructure, customers
purchase integrated hardware and software building blocks that deliver
compute, memory, storage and network capacity as an integrated unit for
a specific workload. In software-defined solutions, the software that runs
those same functions in the hyper-converged model, is typically available
separately to run on any choice of hardware platform.
ARCHITECTING A NEW DATACENTER
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Architecturally, a hyper-converged system binds hardware—
typically a server with direct-attached storage and flash
cards—with the software needed to run virtual workloads,
including: a hypervisor, system management, configuration
and virtual networking tools. These technologies do not
connect to traditional storage stacks and instead offer next
generation storage services such as scale-out performance,
caching, encryption, deduplication.
But hyper-converged infrastructure has its limitations, not
the least of which is the reality that users have to change
their whole data center to implement it. While all-flash
and hybrid arrays have unique attributes, users still buy
and manage networking and servers the same way as they
always have, having a lesser impact on the architecture of
the data center. By contrast, hyper-converged infrastructure
requires users to buy into a new “building block” for their
environments, changing their management tools and
processes. Thus, these are typically deployed in small and
medium businesses or remote office environments.
OTHER CONSIDERATIONS INCLUDE:
• Storage Efficiency: The scale-out architecture of hyper-convergedinfrastructure has driven a data protection scheme based onreplication, rather than traditional RAID. While RAID for dataprotection might have a 10-20% overhead for capacity, thereplicas necessary to protect hyper-converged infrastructure
might see a capacity overhead closer to 300-400%.• Pre-defined Scaling: Compared to traditional IT, there is less
flexibility to throttle pieces of the infrastructure that you needmore or less of—expansion is done by buying another predefinedblock of all the resources.
• Multiple User Management Experience: In a hyper-convergedenvironment, silos of IT personnel may need to be reorganized tostreamline management. Familiar server and storage monitoring
tools are often replaced with different interfaces.
HYPER-CONVERGEDINFRASTRUCTURE
WHYHYPER-CONVERGED?
Enables simplified, unifieddesign, managementdeployment and support byintegrating the componentsof the IT infrastructure.
Provides predictablebuilding blocks that canbe aggregated together tomeet growth needs.
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Many organizations who understand the benefits of
leveraging server-side resources to improve storage
performance seek a solution that enables this without
massive disruption to datacenter architecture.
Enter storage acceleration.
Storage acceleration enables IT managers to improve
storage performance by aggregating server-side
resources. This approach creates a low-latency
performance layer, enabling organizations to purchaseor use lower-cost storage for capacity purposes. Whether
organizations are looking to improve existing storage or
design a new datacenter, storage acceleration enables
organizations to manage the resources of performance
and capacity separately without changing the
architecture or the operations of the storage side.
This architecture can deliver the lowest cost/IOPS by
using less expensive commodity-based resources on the
server side, and the lowest cost/GB by focusing sharedarrays on being optimized for capacity.
From a technology standpoint, this approach
enables organizations to separate the acquisition and
management of performance resources from that of
capacity resources.
From a business standpoint, it provides a way to add
performance to an existing infrastructure without a
rip-and-replace and its inherent cost—in hardware,software, IT time investment and downtime. These
resources can also be significantly less expensive than the
same hardware deployed within a proprietary package.
STORAGE ACCELERATION
WHY STORAGEACCELERATION?
Provides low-latency server-side
access to the fastest storageresources, at a low $/IOPS
Enables organizations tomaintain their existinginfrastructure investment inshared storage platforms,even reducing $/GB on newer
platforms
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Storage acceleration is still an emerging field,
but Infinio has been providing a solution in
this space since 2013. The Infinio solution is
highly efficient with resources, transparent to
existing storage operations, and non-disruptive.
All of these qualities enhance the benefits of
separating storage into its atomic qualities —
capacity and performance — including:
• 10x improvement in latency
• SSD-class performance withoutadditional hardware
• Reduced performance costs ($/IOPS)
• Scale-out I/O with application growth
• Reduced capacity costs for any array ($/GB)
INFINIO’S STORAGEACCELERATION PLATFORM
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INFINIO
STORAGE ACCELERATION FORTHE VIRTUALIZED DATACENTER.
At the core of Infinio’s solution to deliver storage performance separately from storage
capacity is an architecture built on the understanding that most datacenters contain
significant amounts of duplicate data, especially across VMware clusters. Infinio’s content-
based architecture exploits this fact, tracking content (rather than location) which results in
a performance layer with inline deduplication. It is this deduplication that enables Infinio
to deliver high performance (10X improvement in latency) on just small amounts of RAM -
starting at just 8GB per host. When this deduplication is combined with Infinio’s scale-out
global architecture, just 5 nodes of Infinio can have access to hundreds of GB of effective cache.
And it’s not just the efficiency that makes Infinio different. Core to the design of the product
has always been a commitment to seamless integration into an existing environment. As such,
Infinio can be installed in under 30 minutes with no downtime, disruption, guest agents, or
changes to storage configuration. Turning acceleration on or off is a single click, as is removing
Infinio entirely at the end of an evaluation.
Once implemented, Infinio enables you to continue using your familiar storage tools, like
snapshots, replication, and thin provisioning, as well as customizations you’ve made in your
environment around backup system integration or reporting.
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INFINIO ELIMINATES BOTTLENECKS ANDENABLES YOU TO SCALE-OUT TO ACHIEVE
THE PERFORMANCE YOU NEED WITHINYOUR EXISTING INFRASTRUCTURE.WITH INFINIO, YOU ENJOY:
WHAT YOUCAN EXPECT
• 10x improved response time
• 65-85% reduction of reads from storage
• Extended life for storage systems
• Lower TCO for new storage acquisition
“
• Deduplication to drive
high resource utilization
• Simple installation,
enabling you to evaluate
without downtime,
disruption, or changes
• Investment preservation,
since it co-exists with
your existing storage
system tools and reports
We noticed the results almost instantly, with a
visible reduction of storage latency on the VDIdesktops and decreased workload on our lers.Nathan Manzi, Systems Engineerat Minara Resources ”
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Attivio, one of Infinio’s earliest customers, has seen significant storage performance
improvements over the long term, including:
• Improved storage performance with no added hardware
• Sustained read offload of 88%; 93% of bandwidth offloaded
• Sustained 5x performance improvement over 16 weeks
• Installed with no downtime or service interruption
Why spend a lot of money on oneisolated shelf of SSDs when youcan get that benet across theenvironment for less with Innio?
Sean Lutner, VP of IT at Attivio
REAL-WORLD SUCCESS
“
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REAL-WORLD SUCCESS
When mobile workers complained about slow response and poor application
performance, Budd Van Lines deployed Infinio get business moving, achieving:
• Improved VDI performance (read response times decreased by 2.5x;
75% of requests offloaded)
• Eased network bandwidth by offloading storage requests
• Installed quickly without affecting production or users
“ If we had installed Innio earlier, we would nothave had to purchase 10Gb switches to supportour growth and prepare for busy season. Innio’s
read ofoad saves us enough bandwidth trafcthat we could have saved signicant money bynot buying those pricey switches.
Doug Soltez, Budd Van Lines, VP and CIO ”
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Storage architectures—and their users—have had to respond to
wave-after-wave of disruptive innovations over the past ten years.
Cloud. Virtualization. Scale Out Applications. From spinning disksto solid state, a mash-up of hybridized approaches that leverage
a mix of more than one—including server resources—the goal has
always been to simplify, to speed and to maintain predictable
performance. The moving target: the right size, for the right cost—
and never paying too much.
Storage acceleration may be the latest approach—but we don’tthink it’s just a passing trend. Infinio’s system obtains the ability
to accelerate I/O (with an average of 10X improvement in latency)
with just small amounts of RAM. And, what’s more, it provides
that kind of performance with your current architecture and
operations. Whether you are improving performance in an
existing environment or building a new one—that is a
game changer.
FOR MORE ON INFINIO’S APPROACH TO ACCELERATING
THE PERFORMANCE OF YOUR DATA CENTER,
CALL US AT 617-374-6500, OR VISIT WWW.INFINIO.COM.
© 2015 Infinio Systems, Inc. All rights reserved.