Cloud Infrastructure for Your Data Center

Cloud Infrastructure for Your Data Center 1
Copyright © 2016 by the Data Management Institute LLC. All Rights Reserved.
CLOUD INFRASTRUCTURE FOR YOUR DATA CENTER
By
Jon Toigo
Chairman, Data Management Institute
SUMMARY
Despite years of industry advocacy, cloud adoption in larger firms remains slow. There are
many logos for many vendors dotting the cloud technology landscape and many competing
architectures. But there are also few standards that guarantee the interoperability of different
approaches. The latest buzz in enterprise cloud technology is around “hybrid cloud data
centers” in which large enterprises “build their base” – that is, their core infrastructure,
possibly as a “private cloud” – and “buy their burst” – that is, obtain additional public cloud-
based resources and services to augment their on-premises capabilities during periods of peak
workload handling, for application development, or for business continuity. Ultimately, the
adoption of cloud architecture will be gated by how successfully organizations are able to
leverage emerging technologies in a secure and reliable manner and whether the resulting
infrastructure actually delivers in the key areas of cost-containment, risk reduction and
improved productivity.

INTRODUCTION
For nearly a decade, clouds have been touted as the next model for information technology
service delivery. Initially, cloud was an amorphous concept – a comingling of outsourcing and
web technology that seemed, more than anything else, to mimic the Application Service
Provider/Storage Service Provider (ASP/SSP) architectures of the late 1990s and early 2000s.
ASP/SSPs, like more contemporary clouds, appeared in the market as a response to a period of
economic recession that found many firms pondering whether IT was a “core competency” of
their organizations -- or an endeavor better outsourced to third party service providers. Such a
review and reconsideration of the value of “home grown” IT appears to recur with every
economic slow-down, with whatever arrangements that were entered into during lean years
often abandoned once economic growth rebounds.
However, in the case of clouds, the concept seems to have outlived the economic cycle.
Smaller and medium-sized firms have widely adopted public cloud services either as a lower-
cost replacement for or as an adjunct to the operation of their own IT infrastructure. Typically,
cloud technology works its way into the small and medium-sized company beginning with
convenient and user-deployed cloud-based services (such as file sharing or cloud-based mail).
Gradually, services such as data protection may be delegated to cloud-based backup-as-a-
service or disaster recovery-as-a-service providers. Ultimately, placing corporate servers in the
cloud may be seen as a one-time CAPEX and OPEX cost savings.
Larger firms with more complex infrastructure have been slow to warm to public clouds. In
general, the perceived savings from a wholesale relocation of operations environments to
managed hosting or outsourcing models is less compelling for larger companies. Furthermore -
frequent, well-reported, service outages and security failures affecting customers of public
cloud services also discourage adoption.
Another underlying reason for the slow adoption of public clouds in many companies and
organizations has been the challenge associated with storage infrastructure. It can be argued
that the original fascination with clouds was linked to the advent of virtual computing – that is,
the abstraction of computing workload away from commodity hardware using hypervisor
software or similar technology. Theoretically, this facilitated the more rational distribution and
allocation of physical resources to support application workload and provided a basis for
infrastructure-as-a-service (IaaS), a foundational architecture for clouds. If workload – whether
compute, network or storage – could be abstracted away from hardware components, the
latter could be provisioned rapidly, in building block fashion, to stand up infrastructure and
applications rapidly in response to business requirements. This would make the IT service
more agile and more responsive to user needs – inviting descriptions of clouds as “user-driven
IT.”

However, storage has proven to be a more complex and challenging target for abstraction.
“Storage clouds,” at the end of the day, have proven to be much more elusive. Storage itself
remains a significant percentage of annual hardware spending and provisioning storage
remains a challenge, made even more daunting by the proliferation of proprietary converged
and hyper-converged models.
Still, large organizations are seeking the promised efficiencies of on-premises private clouds and
the easy access to and integration of public cloud services and resources when these services
and resources will contribute to the four goals of performance, agility, availability and lowest
TCO. To get there, the concept of cloud storage – now referred to as software-defined storage
– needs to move beyond the limited definition provided by proprietary hardware and
hypervisor software and toward a more practical interpretation that enables
 Higher application performance, especially during peak load periods when there is a noticeable
latency when performing tasks such as opening email attachments, loading a webpage, or
receiving a response to a database query.
 The retention and use of so-called “legacy storage” where such storage makes sense
and the deployment of any storage gear, irrespective of the branding on the front of the
kit.
 The ability to spin resources up and down as needed.
 The ability to support workload of any type from any hypervisor or from non-virtualized
applications and databases.
 The delivery of a high degree of consolidation and efficiency.
 The delivery of a high degree of application and data availability for operational
continuity.
 Ease of management, with automation and orchestration
 Lowest possible cost of ownership.
In fact, the hybrid cloud model is enjoying considerable backing from leading technology
organizations. This model views the corporate IT endeavor as a mixture of legacy “systems of
record” (mainly transactional databases that are not virtualized) interfacing with “systems of
interaction” (mainly virtualized applications) providing the processing of customer transactions
received via “systems of engagement” (mobile apps, web apps, desktop clients, etc.), with
additional security and “upsell” functionality provided to users via the operation of “systems of
insight” (analytical databases consulting purchasing histories and other data defining a user
profile).
This hybrid data center ideal capitalizes on virtual and software-defined services and resources
where practical to meet changing business needs and to leverage external public cloud
resources and services when it makes sense to do so. It is generally well-received by
application development or “AppDev” elements of IT, who seek a development and test
environment with virtually limitless resources while, at the same time, appealing to those more
conservative operations or “Ops” who seek to insulate their infrastructure elements from

disruptive change and excess risk. However, achieving real performance, agility, availability and
lowest TCO with only legacy storage in the model is problematic because of the technology
limitation.
By definition, a hybrid environment suggests the integration of multiple models and storage. In
terms of storage, this means a mixture of “legacy storage” – including shared storage models
such as fabric SANs, and networked storage models like NAS – with “newer” models such as
converged and hyper-converged infrastructure storage. To achieve any sort of efficiency
requires single pane of glass management of storage resources.
In truth, the challenge of managing storage efficiently pre-dates discussions of clouds. In fact,
contemporary cloud service delivery models are more about process than technology. For
clouds to succeed, many layers of supporting technology are required that will:
 enable the virtualization of workload and the abstraction of software functionality away
from commodity hardware so that pools of software services and hardware resources
can be created and inventoried
 provide the necessary administration and orchestration functionality to rapidly allocate
services and resources in an agile manner and in response to business requirements,
and
 support the resulting infrastructure with dynamic status monitoring, automated load
balancing and scaling, automated performance tuning, and high availability failover to
provide a high level of elasticity and resilience.

Ideally, all of the above must be delivered in a workload-agnostic and hardware-agnostic
manner to avoid the creation of siloes and islands of data and infrastructure that limit
management efficiency.
GENERAL AND SPECIAL CLOUD STORAGE REQUIREMENTS
From the standpoint of storage, facilitating “new” cloud architectural models, such as the
hybrid, or public-private cloud, data center presents several general requirements (and many
workload specific requirements) for success. These general requirements would include:
1. The ability to fully leverage CPU cores, cache and flash to meet performance
requirement during peak hours.
2. The ability to pool storage resources in a manner that enables them to be provisioned
and scaled with minimal hurdles and delay to any workload,
3. The ability to provision storage efficiently from pools, including both capacity and data
protection services,
4. The ability to monitor provisioned storage resources to ensure that adequate capacity is
provided to workload on an on-going basis,
5. The ability to guarantee uptime by protecting against storage or datacenter failures.
6. The ability to tier storage to facilitate migration based on data re-reference rates
(performance requirements), capacity constraints, and storage media cost.
Just providing an infrastructure that is capable of meeting the six requirements enumerated
above would fulfill the basic goals of cloud storage:
 Performance: the ability to provision storage resources in a way that ensures that
applications will not be resource or performance “starved” during peak load period.
 Agility: the ability to provision storage resources (and services) “on the fly” (or, at least,
in a much shorter time following a service request) from an inventory of resources.
 High Availability: the ability to deliver a service consistently - giving enterprise the
confidence of a service that is resilient and reliably available.
 Lowest TCO: the ability to cost-efficient scale capacity and meet performance
requirement.
There are currently only three methods, in theory, for delivering such an infrastructure. One
method is to purchase all storage equipment and software from a single vendor, creating a
homogeneous infrastructure from which resources can be allocated and deallocated at will
using single pane of glass management from a single vendor. Unfortunately, few hardware
vendors boast a sufficiently deep “bench” of products to fulfill the specific requirements of
every workload. Those that have a panoply of products have often acquired or re-branded
products from other vendors that cannot be managed using the same management scheme or
software. Moreover, homogeneous infrastructure is fraught with cost and risk: cost, due to the

lock-in created with the vendor and the inability to leverage optional sources of technology as a
hedge against vendor pricing, and risk, because of the lack of alternatives should the primary
vendor no longer offer a specific product in the future.
The second theoretical method for delivering such an infrastructure is to “go 100% software-
defined.” Software-defined, which involves the abstraction of software-technology away from
the storage controller and its instantiation on a server as a stack of centralized software-based
storage functionality that can be deployed, separately or in combination, as a service or set of
services used with storage volumes created from raw media capacity, is a misnomer. All
storage is “software-defined.” What would make such a strategy capable of delivering on the
requirements for performance, agility, high availability and lowest TCO would be common
management of all resulting storage across all workload and data. Most SDS offerings to date
are dedicated to the workload of a single hypervisor, or to the workloads operating under two
or more different brands of hypervisor but using storage infrastructure dedicated to each
hypervisor. The preponderance of SDS solutions do not support the storage of data from non-
virtualized workloads that comprise, on average, approximately 25% of mission critical
workload overall. Moreover, such SDS offerings generally support only converged or only
hyper-converged architectures and offer no support for legacy storage SANs or NAS
whatsoever, increasing their upfront cost to install and their long term cost to manage and
administer the resulting bifurcated (or n-furcated) storage infrastructure.
The third theoretical solution is to operate storage itself as an application that aggregates,
optimizes, and provisions storage to workload automatically or on demand with an easy to use
interface and rock solid, behind the scenes, management and monitoring. This strategy
requires the virtualization of the entire storage infrastructure and in order to support its
expeditious allocation as a shared – or dedicated – resource to any application workload that
requires it. This solution is currently available from only one vendor in the industry: DataCore
Software. Other vendors have parts of the technology that would be required to deliver a
virtualized storage infrastructure (for example, IBM’s SAN Volume Controller (SVC), for
example, can be used to virtualize all connected storage kit, but they do not yet offer a robust
storage services stack on the SVC that can facilitate coherent and centralized service allocation
with virtualized volumes) or can deliver such infrastructure only in the form of a monolithic
storage array or array of nodal hardware that can only be purchased from a single vendor
source (see homogeneous storage above).
This third approach, which may be viewed by some as simply another version of software-
defined storage (or perhaps more appropriately as “true” software-defined storage), is actually
quite different from most current implementations of software-defined storage in several ways.
First, current SDS isolates storage behind application servers using unshared direct-attached
storage topology (by contrast, FC SANs are “shared” direct-attached storage). Unshared direct-
attached storage has the advantage of delivering dedicated storage to a specific workload or to
a specific virtual server running one brand of hypervisor software resulting in the capability for

more storage capacity to be managed (using server or hypervisor management tools) by a
single server administrator. Unfortunately, while increased RAW TB per administrator and
lower per RAW TB storage costs have been documented using this approach, the net effect
across all storage infrastructure is a net decline in storage utilization efficiency (that is, we
waste more storage capacity when measured across all infrastructure).
Source: Some data drawn from Gartner, IT Key Metrics Data 2016, 14 December 2015.
Such a strategy might realize the performance and agility requirements for cloud storage for
certain applications for a certain amount of time, but it becomes much more complex to
administer and manage as different hypervisors are installed and operated concurrently. Then,
multiple cloud strategies will likely be required for different hypervisors and their workloads.
Additionally, availability (predictability of service) will likely be degraded as IT struggles to
manage multiple clouds internally and multiple external providers in a hybrid data center
setting.
Virtualizing the underlying storage asset using technologies like DataCore Software’s Hyper-
Converged Virtual SAN and SANsymphony Software-Defined Storage Platform, which support
hyper-converged clustered storage deployments as well as converged server SANs and
virtualized legacy storage, provide what can be described as the industry’s only “true” or
universal cloud storage solution. The general needs for cloud storage are provided for all
applications, and the entire infrastructure can be managed centrally regardless of hypervisor
used or whether workload is virtualized or not – avoiding capacity utilization inefficiency.

Range of Deployment Alternatives
DataCore Hyper-converged
Virtual SAN
Combine compute and storage
for smallest footprint
SANsymphony Software-defined Storage Platform
Separate storage and compute
in one chassis
Source: DataCore Software.
Integrate, manage, and enhance
existing storage array(s)
Of course, general requirements do not fully describe the suite of additional, application
specific, requirements that cloud storage must honor. Special requirements range from the
accelerated performance of in-memory databases to the extension of high availability
architectures to off-premise targets such as branch office, secondary data center or cloud
service provider-based locations.
In the case of databases, in-memory is all the rage. Many start-up vendors are exploring the
implementation of both analytics and OLTP databases entirely in system memory as a method
for reducing the latencies created by data queries made to disk or flash memory. The result is a
feared "Uber effect" that is seeing most legacy database vendors working to convert their
RDBMS products for in-memory operation too. This strategy makes very particular demands of
"storage" in the broader sense: the processing of RAW 1/0 for performance and latency
optimization.
Virtually none of the current SDS solutions in the market today offer any mechanism for
expediting RAW 1/0 processing (where RAW 1/0 refers to that part of the 1/0 channel
associated with CPU to DRAM reads and writes rather than CPU to disk or flash reads and
writes or STORAGE 1/0). DataCore Software is unique in its offering of a software-based
mechanism for accelerating RAW 1/0 throughput and reducing RAW 1/0 latency via 1/0
parallelization. The latest independently-certified measurement of DataCore's Adaptive
Parallel 1/0 functionality has set industry records for I/Os per second, latency reduction and
lowest cost per IOPS.
In addition to throughput and latency optimization, some workloads also require seamless
integration of local high availability storage architecture with off-premises disaster recovery
architecture. Many SDS and homogeneous hardware solutions do not support this requirement
or do offer a solution - albeit, a costly one requiring the purchase of identical kit.

With virtualized storage infrastructure, “identicality” requirements for replication are a thing of
the past. DataCore’s virtualized storage can be replicated at will to any other storage share
created from a DataCore Software virtual storage pool. Plus, functionality in DataCore’s
software-defined storage stack includes the ability both to failover and to failback from
different instantiations of storage, enabling the elimination of the approximately 30% of
downtime usually attributed to equipment maintenance. Instead of taking storage off line,
simply failover to a redundant instantiation up to 100 kilometers away from the primary. Then,
perform the necessary equipment maintenance without interrupting data access at all – and fail
back to the original storage once maintenance is complete!
CONCLUSION
For the idea of cloud technology to move from the realm of interesting to a status of
operational in larger data centers, there must be no compromise in the performance and
availability of what organizations have today. Cloud must deliver greater agility to minimize
cost and maximize responsiveness to business needs, thereby improving business productivity.
Storage is the main obstacle to realizing cloud objectives. Organizations confront a need to
rationalize storage behind different application platforms with different requirements at
different physical locations, and to simplify and make seamless the ability to blend and leverage
on premises with public cloud-based services for maximum value to the organization.
Of the solutions that are available in the market today, only DataCore Software provides the
robust support for the diversity of storage requirements manifested by applications and
database workloads generated by organizations today. Worth a look.

Cloud Infrastructure for Your Data Center

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