The investment that an organization makes in their virtualization or cloud initiative is significant, but so is the ROI (Return On Investment) that these projects deliver. The challenge is that the cost of providing the storage infrastructure to these initiatives can be expensive and can quickly eat into any ROI that was gained by the virtualization and/or cloud project...

1. Don’t Let Storage Eat Your Cloud ROI
Prepared by: George Crump, Senior Analyst
Prepared on: 5/17/2012

2. Don’t Let Storage Eat Your Cloud ROI
The investment that an organization makes in their virtualization or cloud initiative is significant, but so is
the ROI (Return On Investment) that these projects deliver. The challenge is that the cost of providing the
storage infrastructure to these initiatives can be expensive and can quickly eat into any ROI that was
gained by the virtualization and/or cloud project.
An investment in the cloud was not made as a justification to buy a more expensive storage system; it
was made to enable IT to be delivered as a service and to make IT nimble enough to meet the demands
of the business. New approaches to storage are needed to keep it from eating the cloud ROI.
In order to prevent storage from cutting into the cloud ROI it must provide the performance required by
the cloud infrastructure while at the same time providing the required capacities in the most cost effective
and efficient manner. The performance requirements of a cloud infrastructure are different from the
requirements of stand alone servers and performance demanding applications like databases. It must not
only handle peak and valley I/O (Input/Output) loads that will come from virtualized database applications,
it must also handle steady but random I/O loads that will come from the sheer quantity of virtualized
servers.
The storage infrastructure needs to provide various types of storage efficiency features in order to
minimize the amount of physical capacity required by the rapidly growing virtual environment. These
efficiency features typically include dynamic allocation of volume space (thin provisioning), writeable
snapshots so that virtual machines can stem from a common source (cloning) and space efficiency
techniques that reduce the capacity consumption of the actual data sets being deployed (deduplication or
compression).
The features added to the storage system to improve efficiency should not adversely impact performance.
The storage system has to strike the right balance between delivering high performance and using
storage capacity in the most efficient way possible. This requires a different approach to managing
storage where multiple storage technologies can be utilized and where the right efficiency technologies
are used for the right use case.
IBM Storwize V7000 is an excellent example of a storage solution that is up to the task. By leveraging
storage virtualization and applying a high degree of automation, it eliminates much of the burden of
managing performance and costs. Storwize V7000 is a key component in IBM’s Smarter Storage Strategy
which in turn is part of IBM’s Smarter Computing Strategy. Storwize V7000 delivers high levels of
automation or smarts to allow administrators to focus on other challenges.
Cost Effectively Providing Storage Performance
The cloud environment is a significant operational change from the days of single server / single
application deployment. Now each server is loaded with multiple virtual machines, all with different
storage I/O patterns. This means a steady stream of very random I/O which is a pattern that is particularly
challenging to rotating, hard disk media.
The deployment of higher performance, often solid state based, storage systems in the cloud
infrastructure promises to even more rapidly eat away at the ROI that was originally realized by the cloud
project. This requires a hybrid deployment of solid state and hard disk technology. However, these
storage systems, if not properly implemented, may require additional administration time and even lead to
the creation of a full time “Performance Specialist” who monitors the cloud environment and moves virtual
machines to different storage tiers as performance demands change.
The cost of flash SSD (Solid State Drive) storage also means that the flash investment needs to be used
to its fullest by using all available flash capacity. It cannot sit half empty like regular hard drive storage
can. Also, not just any random type of data can be stored on the flash device. It is necessary to store the
maximum amount of the most appropriate data types on the flash devices to ensure that their full capacity
is being utilized in the most efficient and cost effective manner possible.
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3. Storage Switzerland, LLC
It is possible to manually move data to a flash storage area and some hypervisor environments like
VMware allow for live migration of virtualized server images between disk storage types. But this process
is often not practical in the cloud environment because the data sets are too dynamic which would lead to
many cases of the wrong data being in the wrong location at the wrong time.
There may also be the cost of managing a separate system that is not integrated into the original storage
system. Many customers may choose to purchase a stand alone system from an alternative vendor to
meet the performance demand. These systems can’t integrate with each other and again, while some
hypervisors like VMware provide the ability to migrate virtual machines between disparate systems, there
are still challenges in proactively managing these independent devices.
IBM Storwize V7000 addresses both of these problems with IBM Easy Tier technology and storage
virtualization. This feature, also available in IBM DS8000 and SAN Volume Controller, will automatically
monitor data being stored by the hypervisor. As the access frequency of certain data sets increases they
can be automatically moved to the flash storage tier. Easy Tier will keep the flash tier filled with the I/O
intensive data so that it is served from the fastest performing tier.
The SSD investment is maximized because the flash tier is now filled with the most appropriate data
possible. Easy Tier will continue to dynamically analyze all the data so that as data on the hard drive tier
becomes more I/O intensity than data on the flash tier, it can be replaced. This process ensures that the
premium flash based storage is reserved for data that can take advantage of its high performance and
that the premium investment is used to its fullest.
There may be a mixture of storage device types that make up a given volume but both the cloud
infrastructure and the storage administrators are managing a single logical entity. Storwize V7000
seamlessly integrates the different media types behind the scenes and places data on the most
appropriate media to meet its performance requirements.
The Easy Tier process is designed to run automatically in the background. This allows the storage
manager to focus on other tasks instead of babysitting the performance requirements of demanding VMs
(Virtual Machines).
A tiering technology like this preserves the ROI of the virtual server deployment by freeing up human
capital and not requiring a “performance specialist” since Storwize V7000 becomes that specialist. The
ROI of the cloud implementation is further preserved by minimizing the amount of premium priced solid
state storage required to meet performance demands.
This automation does more than just preserve the cloud ROI, it can actually extend it. An automated data
placement technology also allows for even denser deployment of VMs per host since the performance of
the storage system can automatically react to the additional workloads. If more storage performance is
needed the Easy Tier technology provides information on how much additional solid state storage should
be deployed, thereby preventing over spending.
Cost Effectively Providing Storage Efficiency
Analysis of most cloud environments will show that the overwhelming majority of the data sets will be best
served from a mechanical disk tier because it is seldom being accessed. In fact as much as 90% of the
data is not active on a day-to-day basis. While hard disk technology is already inexpensive, further
optimization of that investment should be pursued to maximize that investment further. Not only does
increased storage efficiency save on capital outlay it also saves on the additional data center floor and
rack space along with increased power consumption that a never ending parade of new disk drives would
require. Even if disk drives themselves became free, the cost to house, power and cool those drives
would be significant.
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4. Don’t Let Storage Eat Your Cloud ROI
It is not just hard disk capacity that can take advantage of this efficiency though. If it can be optimized, the
solid state tier pays an even greater return on the investment since the dollar per GB ratio is higher. If the
investment to buy enough solid state to store 10% of the data can be stretched to actually house 20% of
the data, that will provide a significant performance boost to a broader set of data by virtually eliminating
access to data not in the solid state tier; an event called a “tier miss”.
The Efficiency Process
There is a three step process that a storage system like Storwize V7000 can provide for a cloud
environment. First, volumes can be thinly provisioned, then they can be cloned and finally the remaining
data set must be optimized. Ideally the storage system needs to be able to provide a complete stack of
these capabilities but the optimization of the remaining capacity is potentially the most important of these
steps.
Thin Provisioning
While the term has become universal its nuances need to be understood. Thin provisioning is the process
of allowing a physical host or virtual machine to “think” it has the capacity it requires but to only allocate
that capacity as it needs it. In short, disk space is dynamically allocated on the fly as the host or VM
needs it. This dynamic write operation requires that the storage system have enough performance to
allocate storage and write the inbound data with minimal impact to host application performance. Storwize
V7000 is an example of a storage system with that capability.
Another option is to use the hypervisor’s capabilities to do its own thin provisioning. The challenge is the
extra write activity that a dynamic allocation function will require and the load that this will place on the
cloud hypervisor and its file system. Much of this performance problem can be abated by using a solid
state storage tier and again a product like IBM Easy Tier would reduce much of the performance problem.
Cloning / Writeable Snapshots
The second step is to allow the use of cloning or writeable snapshots. Like thin provisioning, this can be
done either through the storage system or the cloud hypervisor with the same performance concerns
being relevant. This technique creates a master image of a virtual server and then uses that image
repeatedly. For example a collection of database servers may all have the same operating system and
database software. A master image can be created, then snapshotted and used to create each
subsequent server with specifics to each VM being maintained in the writable portion of each snapshot.
Capacity Optimization
Thin provisioning frees capacity that would have been allocated to a particular server or VM but wasn’t
being used. It is important because this is free space that can’t be operated on by another capacity
optimization technique. Cloning and writeable snapshots eliminate much of the redundancy that is seen in
a cloud infrastructure. Capacity optimization is supposed to lower the impact of the remaining data set.
Compression and deduplication are two common techniques used to optimize capacity. Compression
removes redundant information from within a file while deduplication removes redundant information
across all files. Compression can provide efficiency on every file while deduplication can only provide
optimization if there are identity matches between files.
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Deduplication has a significant role to play in enterprise backup techniques where the level of data
redundancy is purposely high. It would seem that it has the same value in the virtual environment except
when a robust storage system like Storwize V7000 is used. Systems like Storwize V7000 will have
eliminated much of the redundant data through the use of cloning and snapshots. Most of the data that
remains is unique unto itself. As a result compression technologies like IBM Real-time Compression can
provide a greater return on the investment because they can work on all files not just redundant files.
Real-Time Compression Ideal for the Cloud Infrastructure
IBM Storwize V7000 provides a fully integrated version of IBM Real-time Compression technology. This
technology is designed specifically for storage workloads and allows the optimization of high
performance, active, primary workloads. In the cloud infrastructure a large active data set is the norm. As
VMs and their hosts are highly active, any optimization strategy ideally should work on active data and
provide optimization without impacting performance.
In general, IBM Real-time Compression will conservatively deliver a 50% reduction in data storage
requirements. Recent tests in cloud environments have shown specifically that compression rations of
Linux Virtual OS’s are as high at 70% and Windows Virtual OS’s are as high as 50%. Even Microsoft
Office Documents that are pre-compressed still show an additional 20% gain in storage efficiency after
Real-time Compression. Most other storage efficiency technologies have a performance impact that users
need to live with or work around. Real-time Compression enables users to reduce storage costs, reduce
rack space and cooling requirements while maintaining performance.
Compression when done in real-time makes everything more effective. The SSD tier that was described
above can either store twice as much data or be reduced in size to save budget on the most expensive
tier of storage. Even the bandwidth between the storage shelves and the controller becomes more
efficient because twice as much data can be transferred across the same segment.
The Advantage of Real-Time
When storage efficiency like compression is accomplished in real-time, the management of data becomes
easier. The storage manager does not need to differentiate between optimized and non-optimized storage
areas. They also do not need to set up a special time to run storage optimization. Finally the net available
capacity is always reflected accurately up to the moment. There is no “back of the napkin” math that
needs to be done to see how much “real” capacity will be available after the compression process is
triggered.
Not only is IBM Real-time Compression more efficient than deduplication in a cloud environment it is also
more efficient than traditional compression algorithms which are all based on fixed sized segments that
are compressed to produce a variable sized output. The size of the segment will impact either
performance or compression ratios. For example if large segments are used, there is a better chance of
finding a compression opportunity but I/O performance is impacted because an entire segment must be
processed even for a small I/O. If the data is broken into smaller segments then I/O performance is less
impacted but the compression ratio is reduced.
IBM Real-time Compression on the other hand uses a variable sized input, which enables it to adapt to
workloads, compressing only the data that is written, which helps to improve performance for active
workloads that often include small writes. Real-time Compression also groups together several I/Os so
data that has been accessed together is compressed together. This approach allows for higher levels of
compression ratios while minimizing disk I/O and enabling random access to data for applications such as
database and email.
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6. Don’t Let Storage Eat Your Cloud ROI
Storwize V7000 Integration
Integration of Real-time Compression into IBM Storwize V7000 makes compression an easy option to
enable. When a volume is created there is an option to select that the volume be compressed. Once
selected the storage manager’s work is done. There is no tweaking or scheduling of optimization tasks.
This has to appeal to the overworked storage manager. Conversion from non-compressed volumes to
compressed volumes is as simple as creating the compressed volume then mirroring the old volume to it
and then breaking the mirror with the new compressed volume becoming the primary storage target.
Finally because Storwize V7000 can virtualize both the internal storage that it comes with and external
third party storage that is attached to it, the ability to extend the life of older arrays by using compression
exists. Not only will Storwize V7000 simplify their management, now it can also double their capacity.
Conclusion
The Cloud Infrastructure places a unique burden on the storage that supports it, one that demands very
high I/O performance and highly efficient utilization. Most storage systems tend to focus on one of these
(performance or efficiency) but not both. The storage system needs to be able to provide both the
required performance and efficiency to be able to allow the Cloud Infrastructure ROI to be maintained
and, with the right system, enhanced.
IBM Storwize V7000—through the use of its automated storage tiering combined with its efficiency
capabilities—delivers the combined response needed from the storage system while keeping the system
simple to manage. Easy Tier provides an automated, simple way to take full advantage of an SSD
investment and its unique delivery of Real-time Compression simplifies the storage efficiency process.
The ability of Storwize V7000 to deliver simplified, automated performance and efficiency qualify it as an
extender of Cloud Infrastructure ROI.
As the number of virtual instances within the cloud infrastructure continues to expand, the storage
complexities to meet those challenges also expand. Storage Systems need to provide high levels of
automation, becoming smarter so that Cloud ROI’s can be preserved. IBM’s Smarter Computing Strategy
—and, as a subset of that, Smarter Storage—are excellent examples of how technology can allow this
expansion to occur.
This document was developed with IBM funding. Although the document may utilize publicly available material from
various vendors, including IBM, it does not necessarily reflect the positions of such vendors on the issues addressed
in this document.
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