But first a bit of disclosure,  I currently work for a storage reseller that sells NetApp as well as other storage. The information in this blog posting is derived from NetApp documents, as well as my own personal experience with the technology at our customer sites.  This posting is not intended to promote the technology as much as it is to explain it. The intent here is to provide information from an independent perspective. Those reading this blog post are, of course, free to interpret it the way they choose.

How NetApp writes data to disk.

First lets talk about how the technology works.  For those who aren’t familiar with how a NetApp array stores data on disk, here’s the key to understanding how NetApp approaches writes.  NetApp stores data on disk using a simple file system called WAFL (Write Anywhere File Layout).  The file system stores metadata which contains information about the data blocks, has inodes that point to indirect blocks, and indirect blocks point to the data blocks. One other thing that should be noted about the way that NetApp writes data is that the controller will coalesce writes into full stripes when ever possible. Furthermore, the concept of updating a block is unknown in the NetApp world. Block updates are simply handled as new writes, and the pointers to the updated blocks are moved to point to the new “updated” block.

How deduplication works.

First, it should be noted that NetApp deduplication operates on a volume level.  In other words,all of the data within a single NetApp volume is a candidate for deduplication. This includes both file data, and block (LUN) data that is stored within that Netapp volume.  NetApp deduplication is a post-process that occurs based on either a watermark for the volume, or on a schedule.  For example, if the volume exceeds 80% of it’s capacity a deduplication run can be started automatically. Or, a  deduplication run can be started at a particular time of day, usually at a time when the user thinks the array will be less utilized.

The maximum sharing for a block is 255. This means that if there are 500 duplicate blocks,there will be 2 blocks actually stored with 1/2 of the pointers pointing to the first block and 1/2 of the pointers pointing to the second block. Note that this 255 maximum is separate from the 255 maximum for snapshots.

When deduplication runs for the first time on a NetApp volume with existing data, it scans the blocks in the volume and creates a fingerprint database, which contains a sorted list of all fingerprints for used blocks in the volume.  After the fingerprint file is created, fingerprints are checked for duplicates, and, when found, first a byte- by-byte comparison of the blocks is done to make sure that the blocks are indeed identical. If they are found to be identical, the block‘s pointer is updated to the already existing data block, and the new (duplicate) data block is released. Releasing a duplicate data block entails updating the indirect inode pointing to it, incrementing the block reference count for the already existing data block, and freeing the duplicate data block.

As new data is written to the deduplicated volume, a fingerprint is created for each new block and written to a change log file. When deduplication is run subsequently, the change log is sorted, its sorted fingerprints are merged with those in the fingerprint file, and then the deduplication processing occurs as described above.  There are two change log files, so that as deduplication is running and merging the new blocks from one change log file into the fingerprint file, new data that is being written to the flexible volume is causing fingerprints for these new blocks to be written to the second change log file. The roles of the two files are then reversed the next time that deduplication is run. (For those familiar with Data ONTAP usage of NVRAM, this is analogous to when it switches from one half to the other to create a consistency point.)  Note that when deduplication is run an an empty volume, the fingerprint file is still created from the log file.

Performance of NetApp deduplication.

There has been a lot of discussion about the performance of Netapp deduplication. In general, deduplication will use CPU and memory in the controller. How much CPU will be ustilied is very had to determine ahead of time, however in general you can expect to use from 0% to 15% of the CPU in most cases, but as much as 50% has been observed in some cases. The impact of deduplication on a host or application can very significantly and depends on a number of different factors including:

•    The application and the type of dataset being used
•    The data access pattern (for example, sequential versus random access, the size and pattern of the
•    I/O)
•    The amount of duplicate data, the compressibility of the data, the amount of total data, and the
•    average file size
•    The nature of the data layout in the volume
•    The amount of changed data between deduplication runs
•    The number of concurrent deduplication processes and compression scanners running
•    The number of volumes that have compression/deduplication enabled on the system
•    The hardware platform—the amount of CPU/memory in the system
•    The amount of load on the system
•    Disk types ATA/FC, and the RPM of the disk
•    The number of disk spindles in the aggregate

The deduplication is a low priority process, so host I/O will take precedence over dedupllication. However, all of the items above will effect the performance of the deduplication process itself.  In general you can expect to get somewhere between 100MB/sec to 200/MB/sec of data dedupication from a NetApp controller.

The effect of deduplication on the write performance of a system is very dependent on the model of controller and the amont of load that is being put on the system. For deduplicated volumes, if the load on a system is low—that is, for systems where the CPU utilization is around 50% or lower—there is a negligible difference in performance when writing data to a deduplicated volume, and there is no noticeable impact on other applications running on the system. On heavily used systems, however, where the system is nearly saturated, the impact on write performance can be expected to be around 15% for most models of controllers.

Read performance of a deduplicated volume depends on the type of reads being performed. The implicit on random reads is negligible. In early versions of ONTAP the impact of deduplication was noticeable with heavy sequential read applications. However with version 7.3.1 and above NetApp added something they called “intelligent cache” to ONTAP specifically to help with the performance of sequential reads on deduplicated volumes and were able to mitigate the performance impact of sequential reads nearly completely. Finally, with the addition of FlashCache cards to a controller, performance of deduplicated volumes can actually be better than non-deduplicated volumes.

Deuplication Interoperability with Snapshots.

Snapshots and their interoperability with deduplication has been a hotly debated topic on the internet lately. Snapshot copies lock blocks on disk that cannot be freed until the Snapshot copy expires or is deleted. On any volume, once a Snapshot copy of data is made, any subsequent changes to that data temporarily require additional disk space, until the snapshot is deleted or expires. The is true with deduplicated volumes as well as non-deduplicated volumes. Thus the space savings from deuplication for any data held by a snapshot prior to a deduplication run will not be recognized until after that snapshot expires or is deleted.

Some best practices to achieve the best space savings from deduplication-enabled volumes that contain Snapshot copies include:

•    Run deduplication before creating new Snapshot copies.
•    Limit the number of Snapshot copies you maintain.
•    If possible, reduce the retention duration of Snapshot copies.
•    Schedule deduplication only after significant new data has been written to the volume.
•    Configure appropriate reserve space for the Snapshot copies.

Some Application Best Practices

VMWare

In general VMware deduplicates well, especially if a few best practices in laying out the VMDK files are considered. The following best practices should be considered for VMware implementations:

•    Operating system data deduplicates very well therefore you should stack as many OS’s  onto the same volume as possible.
•    Keep VM swap files, pagefiles, user and system temp directories on separate VMDK files.
•    Utilize FlashCache where ever possible to cache frequently accessed blocks (like those from the OS).
•    Always perform proper alignment of your VM’s on the NetApp 4K boundaries.
•

Microsoft Exchange

In general deduplication provides little benefit for versions of Microsoft Exchange prior to Exchange 2010. Starting with Exchange 2010 Microsoft has eliminated single instance storage and deduplication can reclaim much of the additional space created by this change.

Backups (NDMP, SnapMirror and SnapVault)

The following are some best practices to consider for backups of deduplicated volumes:

•    Ensure deduplication operations initiate only after your backup completes.
•    Deduplication operations on the destination volume complete prior to initiating the next backup.
•    If backing up data from multiple volumes to a single volume you may achieve significant space savings from deduplication beyond that of the deduplication savings from the source volumes.  This is because you are able to run deduplication on the destination volume which could contain duplicate
•    data from multiple source volumes.
•    If you are backing up data from your backup disk to tape consider using SMTape to preserve the deduplication/compression savings.  Utilizing NDMP to tape will not preserve the deduplication savings on tape.
•    Data compression can affect the throughput of your backups.  The amount of impact is dependent upon the type of data, compressibility, storage system type and available resources on the destination storage system.  It is important to test the affect on your environment before implementing
•    into production.
•    If the application that you are using to perform backups already does compression, NetApp data compression will not add significant additional savings.

Conclusions

In general, NetApp deduplication can help drive down the TCO of your storage systems significantly, especially when combined with FlashCache in a VMware or Virtual Desktop environment. If best practices are followed carefully, the performance impact of deduplication is negligible, and the space savings for some applications can be considerable. Some careful planning and testing in the customers environment are necessary to ensure that maximum advantage is taken of deduplication, however the ability to schedule when the operations take place combined with the ability to turn on and off deduplication provide significant flexibility in to tune the environment for a customer’s particular application profile.

© Joerg Hallbauer for Gestalt IT, 2011. | NetApp Deduplication An In-depth Look
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The Micron RealSSD P320h is more than a new form-factor for the company; it also introduces their RAIN technology

This morning, Micron announced their “RealSSD” P320h SSD, bringing them into the PCIe storage market for the first time. Already a leading supplier of both consumer and enterprise SATA SSDs, as well as the world’s leading supplier of NAND flash in partnership with Intel, this move puts Micron in direct competition with existing suppliers like media darling Fusion IO.

Introducing the RealSSD P320h

The RealSSD P320h SSD can be seen as a PCIe companion to the existing P300 series of enterprise SSDs, but it is much more than that. Micron brands their entire SSD line “RealSSD”, from the consumer grade C300 and C400 (which Crucial sells as the M4) to the enterprise P300. All include Micron’s own SSD controller ASICs and flash memory modules, offering greater levels of integration and profitability for the company.

The P320h seems similar to the recently introduced P300 in terms of componentry, but the PCIe interface puts it into a different realm of performance. Although Micron’s RealSSD line is lauded for its 6 Gb SATA interface, an internal PCI express card like that P320h blows the doors off any disk interface. Micron’s presentations show the P320h delivering over many times the IOPS of their already speedy P300! As demonstrated already by numerous competitors, there is no substitute to the low latency I/O performance of a PCIe card.

The RealSSD P320h will initially be offered in two models, both in the full-height half-length PCIe form factor. The 350 GB model offers slightly lower random write performance than its 700 GB big brother, but both boast massive performance numbers. Both use 34 nm SLC flash chips and are built on a 32-channel design.

Massive Performance

The P320h delivers astonishing performance, at least in Micron’s PowerPoint illustrations. My own C300 can push 250 MB per second of sequential writes, and the enterprise class P300 is maybe a bit faster. But the P320h is rated at 2 GB per second sustained sequential write performance, nearly an order of magnitude faster. It would be difficult find an application, let alone a server, that could sustain this kind of throughput for long.

Micron boasts industry-beating throughput

Even more important than throughput is I/O performance. SSDs like my C300 excel at servicing I/O requests, and are rated at 30,000 to 45,000 random 4K write IOPS. Again, the P300 is able to match this level of performance while providing five-year reliability for enterprise applications. But the P320h delivers nearly 350,000 4K write IOPS, besting the fastest and most expensive enterprise storage arrays in existence.

Micron’s IOPS claims are astonishing

Note that all numbers in these charts are from the manufacturers’ own specification sheets: Micron P320h, Fusion I/O ioDRIVE DUO, TMS RamSan-70, LSI WarpDrive SLP-300, OCZ Z-Drive R2 e88, Virident tachIOn. I have included two of Micron’s RealSSD SATA drives for comparison purposes: Micron P300, Micron/Crucial C300.

Benchmarks should always be taken with a grain of salt, and manufacturer spec-sheet claims are doubly dubious. But Micron makes these claims, and it won’t be long before these devices are independently benchmarked.

Digging Deeper Into the Hardware: RAIN Reliability

The P320h is a first for Micron in a number of ways. Along with being their first PCIe card, it also is the first SSD to feature Micron’s so-called RAIN architecture and RealSSD Manager software. The P320h includes optimized drivers for Windows and Linux to further improve performance, but Micron is leaving it to partners to integrate the SSD with operating systems, hypervisors, or applications.

RAIN is Micron’s answer to concerns about SSD reliability in the enterprise. Although already using ultra-reliable SLC chips, the P320h introduces a raid like technology Micron calls Redundant Array of Independent NAND, or RAIN for short. Reminiscent of SandForce’s Redundant Array of Independent Silicon Elements (RAISE), RAIN arranges flash memory chips in a 7+1 arrangement to improve reliability and recoverability in the event of a failure.

Micron claims that this combination of intelligent controllers, RAIN, and SLC memory chips delivers top-notch reliability. The company measures reliability in terms of the number of full drive fills that can be sustained per day for five years. They claim that enterprise customers demand SSDs that can sustain 30 fills per day for five years, or an incredible 54,750 drive fills. That’s 25 PB of data written for 350 gig unit or 50 PB for the big 750 GB P320h!

Putting things another way, if the 700 GB P320h was pounded with sequential data at its rated maximum of 2 GB per second, it would take over nine months to wear out this drive. Just in case the customer expects to hammer on the drive constantly, they may use the RealSSD Manager software to throttle performance and ensure reliability to a given date.

Stephen’s Stance

PCIe SSDs like Micron’s new P320h offer mindbending performance and enterprise class reliability. Although expensive, these devices are in an entirely different league from any other storage option. Micron promises to bring the PCIe P320h to market at nearly $15 per gigabyte, a substantial discount over other PCIe SSD competitors. But the card will still cost more than $5000, making it an expensive add-on for most servers.

The challenge in enterprise storage is not delivering absolute capacity or performance any longer. Today’s challenge is making that capacity and performance available to applications and, ultimately, and users in the form of improved satisfaction or profitability. Micron is moving the ball forward on the hardware front, but my focus remains on software providers that will deliver this performance in a usable form for applications, hypervisors, and operating systems.

And what’s next from Micron? I expect a SAS HDD-form factor SSD shortly, and perhaps a line of PCI Express Mini Cards or “Blade” SSDs might follow.

© Stephen Foskett for Gestalt IT, 2011. | Micron Bursts Into the PCIe SSD Market
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EMC FAST

EMC FAST (Fully Automated Storage Tiering) is actually a suite made of of two different products. the first, called FAST Cache operates by keeping a copy of “hot” blocks of data on SSD drives. In effect it acts as a very fast disk cache for data that is currently being accessed while the data itself is being stored on either 15K SAS or 7200 RPM NL-SAS (SATA) drives.

FAST Cache provides the ability to improve the performance of SATA drives, as well as to turbo charge the performance of fiber channel and SAS drives as well. In general, this kind of technology helps to divide performance from spindle count, which helps drive down the number of drives required for many workloads, thus driving down the cost of storage, and the overall TCO of storage.

The other product in the FAST suite is FAST Virtual Pool.  This is the product that most people associate with FAST since it is the one that leverages  three different disk technologies, SSD, high speed drives such as 15K RPM SAS, and slower high capacity drives such as 7200 RPM NL-SAS. By placing only data that requires high speed access on the SSD drives, data that is receiving a moderate amount of access on the 15K SAS drives, and putting the rest on the slower, high capacity disks EMC FAST is able to drive the TCO of storage downward.

NetApp FlashCache

NetApp approaches the overall issue of improved performance while simultaneously driving down the TCO of storage in a different way. NetApp believes that using fewer disks to store the same amount of data is the best way to drive down TCO. Therefore NetApp has spent a significant amount of time developing storage efficiency tools to help their customer’s store more data in less space.  For example, they developed a variant of RAID-6 called RAID-DP which provides the protection and performance of RAID-10, while utilizing significantly less space. NetApp has also developed block level de-duplication which can be utilized with primary production data.

However, as with many technologies of this type there could be a performance penalty paid for it’s utilization. Therefore, Netapp needed to develop a way to improve the performance if it’s arrays while also supporting it’s storage efficiency technology. With the advent of Flash memory, Netapp found a way to do this without any need for significant changes in the architecture of it’s arrays. Thus was born FlashCache.

FlashCahce provides a secondary read cache for hot blocks of data. This proves a way to separate performance from spindle count,  and thus not only allows workloads intended for Fiber Channel or SAS drives to potentially run on SATA drives, but it also addresses some of the performance issues with the storage efficiency technologies that NetApp developed. For example, with FlashCache utilized in a virtual desktop environment Netapp de-duplication allows many individual Windows images to be represented in a very small footprint on disk. However a problem arrises when a large numer of desktops all try to access their Windows image at once. However with the addition of FlashCache, most, if not all of the Windows image would end up being storage in Flash memory, thus avoiding the performance issue of a boot storm, virus checking storm, etc.

Conclusion

Both EMC and Netapp have developed ways to help both improve the performance, and drive the TCO of storage downward. the two vendors approached the problem is somewhat different ways, but in the end they have both solved the problem in unique and effective ways.

The NetApp technology requires that the user buy-in completely to the NetApp vision of storage efficiency. If the user ignores the advantages of de-dupication in particular, or has data or workloads  that simply don’t allow for the application of the NetApp storage efficiency technology then the TCO saving that NetApp promises will not be achieved. Utilizing FlashCache to seperate performance from spindle count is also critical in maintaining the performance of the array. This separation of performance from spindle count also in and of itself drives dwn the number ofd drives needed to support a workload, and thus also drives down the TCO.

The EMC technology requires a very good understanding of your application workloads, and careful planning and sizing of the different tiers of storage. EMC could do more to make the two sub-products work together so that a single solution could provide both the TCO and the performance improvements at the same time. However, EMC FAST is a product that provides the TCO improvement promised, and doe it with a clean and elegant solution.

Finally, a little on the future. With the cost of Flash memory coming down 50% year over year, it will soon reach the same price point that we currently see 15K HDD’s at. Once that happens one has to wonder what role 15K HHDs will fill? If 15K HDDs are, indeed, squeezed out of existence by this reduction in the price of Flash memory, what purpose will 3 tiered automated storage tiering fill? Or, will the future simply be 2 tiers of storage, one that provides bulk capacity, and one that accelerates the performance of this bult capacity? if that predication is correct, then FAST VP will have a limited life, and FAST Cache and FlashCache will be the longer surviving technology.

© Joerg Hallbauer for Gestalt IT, 2011. | EMC FAST and NetApp FlashCache a Comparison
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Enter the concept of tiered storage again. The idea was to place only that data which absolutely required the very high performance of Flash on Flash, and to leave the remaining data on spinning disk. The challenge with tiered storage in the way that it has been defined in the past was that it meant that too much data would be placed on very expensive Flash since traditionally an entire application would have all it’s data placed on a single tier. Even if only specific parts of the data at the file, or LUN level were placed on Flash, the quantity needed would still be very high, thus driving the costs of for a particular application up. It was quickly recognized that the only way to make Flash cost effective would be to place only the blocks which are “hot” for an application in Flash storage, thereby minimizing the footprint of Flash storage.

The issue addressed by automated storage tiering is that you no longer need to know ahead of time what the proper tier of storage for a particular application’s data needs to be. Furthermore the classification of the data can occur at a much more fine-grained block level rather than the file or the LUN as with some earlier automated storage tiering implementations.

Flash has changed the landscape of storage for the enterprise. Currently, Fash/SSD storage can cost 16-20X what Fiber channel, SAS, or SATA storage can cost. The dollars per GB model ends up looking something like the following:

However the IOPS per $ model looks more like this:

The impact on the tiered storage architectural model of Flash storage has been, in effect, to add a tier-0 level of storage where application data is placed that requires extremely fast random I/O performance. Typical examples of such data are database index tables or key lookup tables, etc. Placing this kind of data, which may only be part of an application’s data, on Flash storage can often have a dramatically positive effect on the performance of an application.  However, due to the cost of Flash storage the question is often raised, how can data centers ensure that only data that requires this level of performance resides on SSD or Flash storage so that they can continue to contain costs? Furthermore, is there a way to put only the “hot” parts of the data in the very expensive tier-0 capacity, and leave less hot, and cold data in slower, less expensive capacity? Block based automated storage tiering is the answer to these questions.

Different storage array vendors have approached this problem in different ways. However, in all cases, the object is to place data at a block level, on tier-0 or Flash storage only while that data is actually being accessed, and then to store the rest of the data on lower tiered storage while the data is at rest. Note that this movement must be done at the block level in order to avoid performance issues, and to truly minimize the capacity of the tier-0 storage.

One approach used by several storage vendors is to move blocks of data between multiple tiers of storage via a policy. For example, the policy might dictate that writes always occur to tier-0, and then if that data is not read immediately it is moved to tier-1. Then if the data isn’t read for 3 months that data is then moved to tier-2. The policy might also dictate that if the data is then read from the tier-2 disk then it is placed back on tier-0 in case additional reads are required and the entire process starts all over again. Logically this mechanism provides what enterprises are looking for, minimizing tier-0 storage and placing blocks of data on the lowest-cost storage possible. The challenge with this approach is that the I/O profile of the application needs to be well understood when the policies are developed in order to avoid accessing data from tier-2 storage too frequently and generally moving data up and down the stack too often since this movement is not “free” from a performance perspective. Additionally, EVT has found that for most customers, data rarely needs to spend time in tier-1 (FC or SAS) storage, that most of the data ends up spending most of it’s live on the SATA storage.

Therefore as the cost of Flash storage continues to come down, the need for the SAS or Fiber Channel storage will continue to decline, and eventually disappear leaving just Flash and SATA storage in most arrays.

Another approach that at least one storage vendor is using is to avoid all the policy based movement and to treat the Flash storage as a large read cache. This places the blocks that are most used on tier-0, and leaves the rest on spinning disk. When the fact that the sequential write performance of Flash, SAS/FC, and SATA is similar is taken into consideration along with a controller that orders its random writes, this approach can provide a much more robust way to implement Flash storage.  In some cases, it allows an application that would not normally be considered a good candidate for SAS or Fiber Channel storage to be able to utilize SATA disks instead. In general, this technique de-couples spindle count from performance thus providing more subtle advantages as well.  For example, applications which has traditionally required very small disk drives so that the spindle could would be might (many, many 146GB FC drives, for example) can now be run on much higher capacity 600GB SAS drives and still provide the same, or better performance.

Overall, automated storage tiering is becoming a de-facto standard in the storage industry. However different storage array vendors have taken very different approaches to the implementation of automated tiering, but in the end the result is uniformly the same. The ability of the enterprise to purchase Flash storage to help improve the performance of their applications while at the same time continuing to bend the cost curve of storage downward.

© Joerg Hallbauer for Gestalt IT, 2011. | Flash Storage and Automated Storage Tiering
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Background

Building arrays from pure memory isn’t new; Texas Memory Systems have had the RamSan series of products on the market for some time now (and there are others out there).  Of course, the problem for many large organisations is how to make use of such an expensive and relatively small device.  There are plenty of use cases where flash/SSD may be useful, however (a) it is difficult to target exactly which applications and (b) for those applications that can be identified, potentially only part of the data will benefit from acceleration.

One solution has been to follow the route of the traditional vendors and add SSD as an extra device within the same hardware chassis.  This isn’t a solution to using SSD but rather a sticking plaster over the problem; the SSD may give better read performance but it is unlikely that writes will be accelerated to the level justified by the additional costs of the SSD device itself.  In addition, the SSD is sitting behind a traditional storage array.  Vendors such as EMC, IBM and Hitachi have spent millions of man-hours and hundreds of millions of dollars on software developments to help smooth the impact and manage the unpredictable performance of hard drives.  Remember that when an I/O request is received, the storage array has no idea where a mechanical device like a hard drive is positioned and so cache, algorithms and that other clever intellectual property have been used to mask these physical inadequacies.

However, despite vendors’ best efforts, spikes and unpredictable response times do occur and there’s no way to remove them and guarantee completely consistent I/O responses.

The Violin Approach

So what happens if you can remove the cost issues and buy an SSD-based array for the same price as tier 1 storage?  This is the route Violin Memory are taking to market – make the SSD storage array as closely priced to tier 1 arrays as possible.  Remove the thought process and complications of determining what to place on SSD by making the price argument irrelevant.

In reality, Violin haven’t reached that price parity yet; prices are quoted around the $20/GB mark, which is around double what I’d expect to see for tier 1 storage (depending on volume).  However it is in the order of magnitude where organisations can look at those troublesome applications that decide that the cost of additional servers, disk spindles or re-writing the application is outweighed by simply moving the application to a Violin SSD device.

I think this is the ultimate tipping point for SSD use; where the cost of improving application performance is exceeded by the cost of moving to SSD, then SSD will win.  Where improving application performance is justified by increased business advantage, the business case is written.

Tech Specs

OK, let’s have a look at the technical specifications for the techies amongst you.  Firstly, today’s device capacity sits at 10TB in 3U and is expected to grow to 20TB in Q3.  I’ve also been told that this capacity is expected to be close to 5x greater by the end of 2010, which means 100TB of memory-based storage in a 3U unit.

The 3200 supports PCIe (x4 & x8)  as well as 4/8Gb Fibre Channel and 10Gb iSCSI and FCoE.  Latency is less than 100 microseconds.

Violin array use VIMMs (Violin’s name for their flash memory cards.  These are grouped together into 1TB units, using RAID-5 technology to manage failures.  Maintenance can be performed online periodically to replace failed VIMM devices.

There’s one major issue with Flash/memory-based arrays that Violin claim to have addressed.  That is the issue of degraded performance over time.  Have a look at the following graphic, showing saturated workload on the Crucial C300 versus X25M from Intel.  This graph and the associated review can be found on Anandtech’s website here.  Very quickly with heavy use, the performance for these devices drops off.  Violin claim their array doesn’t suffer similar issues and can deliver sustained performance.  Of course, we can believe that statement once we’ve seen a review of the product delivering the performance as promised.

Futures

A 10/20TB capacity in 3U isn’t huge by today’s standards.  If Violin Memory can deliver on their promises and bring a 3 to 5-fold increase in performance by year end (with a continual reduction in price) then things start to look interesting.  I’d like to see the results of some long-term stress tests on the 3200 series devices.  I have some more material to post in the coming days, once I can validate what’s open and not under NDA/embarbgo.  In the meantime, here are some questions to ponder:

• Do I have any I/O bound applications?
• Can I measure/determine my I/O bound applications?
• Is there direct businss advantage from increasing I/O throughput?

If you can start answering yes to the above questions, then perhaps SSD-based arrays are for you.

© Chris for Gestalt IT, 2010. | Violin Memory Inc Release New All-SSD Array
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Wandering the EMC World show floor was very revealing. Along with EMC’s new VPLEX, Chris Mellor and I spotted the unannounced SDRAM-based ZeusRAM SSD from STEC. While getting some hands-on time with Iomega’s new 12-drive storage array, I spotted an exciting but unannounced feature: The ix12-300r includes native Avamar backup client!

Native Avamar support in the ix12-300r? That’s new!

Chocolate and Peanut Butter

EMC’s Avamar backup product deserves much more press than it gets. Global deduplication is the secret sauce, allowing high efficiency for backups, both in terms of capacity and bandwidth usage. This means that Avamar is very well-suited for small business and remote office use.

Iomega’s new ix12 is similarly well-suited in this environment. It includes flexible storage allocation, both iSCSI SAN and NAS, and is bursting with features, from replication to webcam support. The 12-drive array fits perfectly into the small-business and remote-office markets with a low $5k-$10k price tag.

Avamar’s backup deduplication technology and Iomega’s “just right” small-business storage is a real “chocolate-and-peanut butter” combination. Both target the same markets and mixing them together is even better than selling them apart. Integrated Avamar client support makes the ix12 even more compelling, and will likely drive Avamar sales as well.

I talked to the Iomega execs at EMC World and they confirmed that this support will be included in the shipping ix12 software but was not yet supported by the company. They expect Avamar qualification to come later in the year, but I suspect that customer interest could accelerate this timetable. If you are interested in the combination, let Iomega and Avamar know!

ix12 Impressions

My release-day review of the ix12-300r was based on press materials and a briefing, but getting a hands-on look at the device revealed details beyond the Avamar support. I was quite pleased by the build quality of the array: It is solidly constructed and the connectors, fans, and power supplies looked to be of high quality. The designers seem to have paid attention to cooling and airflow, important in a box containing 12 spinning hard disk drives. The dual power supplies are hot-swappable and seemed fairly robust as well.

I also spotted two empty PCI Express slots at the rear of the ix12. One wonders what use Iomega will put these to. One can imagine adding additional gigabit or 10 gigabit Ethernet controllers, but solid-state storage (SSD) would be much more interesting. The ix12’s LifeLink software has been enhanced fore more-flexible RAID configuration; I wonder if it also includes the ability to tier storage to SSD. A mini array with EMC’s FAST technology would be compelling, but the use of SSD as a cache (FAST Cache?) might be simpler to implement.

Clearly, the ix12-300r is much more than a SATA-expanded ix4-200r. Iomega is adding real valuable business features to the system and moving it ever closer to the EMC and Dell CLARiiON products. Yet the price is still well below those systems. Chocolate and peanut butter, anyone?

© Stephen Foskett for Gestalt IT, 2010. | EMC Mixes Avamar Into Iomega ix12-300r
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STEC may not have been quite ready to reveal their next-generation ZeusRAM solid-state disk (SSD), but they are demonstrating it anyway at EMC World in Boston this week. The ZeusRAM is a fundamentally different animal from the existing ZeusIOPS drive in one critical way: Rather than using flash memory for primary data storage, the ZeusRAM uses DRAM. This improves reliability and longevity and ought to raise the bar on performance as well.

STEC has introduced ZeusRAM, a SDRAM-based drive

The ZeusRAM is small (just 8 GB) but STEC claims massive performance: 80,000 IOPS for both read and write (versus 80,000 read and 45,000 write for the 6 Gb SAS ZeusIOPS) and 500 MB/s sustained read and write (versus 350 and 300 for the ZeusIOPS). These numbers are well beyond the capabilities of whole shelves of traditional hard disk drives.

Should it lose power, the ZeusRAM will de-stage its content to flash RAM using power stored on internal super-capacitors. This is a major differentiator from in-system RAM disks which require whole-system battery backup and software to de-stage.

STEC has not announced pricing or availability information for the ZeusRAM drive at this point. We noted much interest in the drive from EMC staff at the EMC World show, and would not be surprised to see the ZeusRAM show up in a future Symmetrix or CLARiiON.

© Stephen Foskett for Gestalt IT, 2010. | STEC Spills the Beans on ZeusRAM SSD
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Nimbus claims that the S-class will deliver new levels of performance in a compact, reliable, and affordable package. The array starts at around $25,000 for 2.5 TB of thin-provisioned, deduplicated flash storage and scales to 100 TB and 500,000 IOPS. The array also boasts high-performance snapshots and integrated replication.

Joining Nimbus for this roundtable discussion were ten Tech Field Day delegates:

• Jason Boche (@JasonBoche, Boche.net)
• Carlo Costanzo (@CCostan, VMware Info)
• Chris Evans (@ChrisMEvans, The Storage Architect)
• Greg Ferro (@EtherealMind, EtherealMind)
• Scott D. Lowe (@ScottDLowe, Tech Republic)
• Scott Lowe (@Scott_Lowe, ScottLowe.org)
• Devang Panchigar (@StorageNerve, StorageNerve)
• Bas Raayman (@BasRaayman, Bas Raayman)
• Matt Simmons (@StandaloneSA, Standalone Sysadmin)
• Rick Vanover (@RickVanover, Virtualization Review)

Download the Nimbus roundtable podcast now, or subscribe in iTunes to tune in to the discussion!

© Stephen Foskett for Gestalt IT, 2010. | Podcast 4: Virtual Field Day Nimbus Roundtable
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SGI Acquires COPAN Systems

In fact to be more precise, SGI have acquired some of the assets of COPAN and left the liabilities behind for a mere $2 million in cash (press release).  The demise of COPAN raises two potential questions; is spin-down a dead technology or were COPAN in a market that wasn’t able to understand their technology?  I have to admit it took me a while to get what COPAN were offering.  In fact I had a presentation of their technology by the UK team a couple of years ago in which I experienced that “light bulb” moment.  However times change.  Ask yourself the following questions:

• How expensive was COPAN compared to a standard modular solution?
• What savings could I actually achieve in a COPAN solution?
• Which other vendors now offer spin-down in their products?

At the end of the day, the majority of an array is disk drives, which cost the same, whoever you purchase them from.  Savings from suspending power usage are not that great; powering down a single drive may only save $10-15/year, hardly a massive saving.  With other vendors also offering spin down in their products, it was only a matter of time before COPAN hit a wall.  I evaluated the product for deployment at a client.  My major issue with the offering was the sheer weight of it.  This factor alone would have made impractical for many data centres.

EMC Sells IP to VMware

It’s a bit like borrowing something from your parents; EMC are selling some of their software IP to VMware for the princely sum of $200 million (press release).  The products being transferred relate to server  and application management. Does this mean that owning the Hypervisor isn’t enough to beat the competition?  I expect it does.  Where’s the money to be made in selling a hypvervisor that in a few years will have to be given away for free?  Hyper-V may not be competitive today, but a free product definitely beats a one that has to be paid for, even if the features aren’t quite as good.  So the future is selling add-on value, simplification or tie-in.  Maybe that’s the reason behind the parental selloff.

STEC Shares Get Punished

STEC shares have yet again taken a battering after they missed earnings target by a mile (Barrons Report).  The press report on the link makes an interesting comment claiming EMC may have effectively stopped ordering SSDs.

I’ve personally always thought that SSDs were overhyped.  I never believed they would be adopted as quickly as EMC predicted (or more accurately would have wished).  Have a look at Beth Pariseau’s article from this time last year (TechTarget article).  At the time Tucci claimed EMC were selling “every SSD they could get their hands on”.  We can only assume that has changed.  What a difference a year makes.

© Chris for Gestalt IT, 2010. | COPAN, EMC/VMware & STEC
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My presence at Storage Expo NL may have been cursed, but my presentation went off without a hitch thanks to the creativity and flexibility of the VNU staff and Expo volunteers like Ilja Coolen. In my session, I talked about the shortcomings of traditional tiered storage as a way to advance the Noble Goals of Storage Management and proposed a solution: Although merely using different disk types will never deliver the goods, adding flash and cloud to an integrated, automated solution will be truly revolutionary. I look forward to the day when all of today’s buzz-worthy technologies (flash, cloud, thin provisioning, automated tiering, post-RAID) are mixed together to form a really revolutionary storage system.

I went ahead and recorded the entire presentation and posted it on Vimeo for anyone to see. But I just realized I never posted it here to my blog. So without further ado, I give you “Extreme Tiered Storage: Flash, Disk, and Cloud!”

Stephen Foskett on Extreme Tiered Storage from Stephen Foskett on Vimeo.

By the way, in case you were wondering, I used BoinxTV to create this video.

© Stephen Foskett for Gestalt IT, 2010. | Extreme Tiered Storage: Flash, Disk, and Cloud
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