R&D measures – Page 4 – Silverton Consulting

Scality’s Open Source S3 Driver

Posted on September 18, 2016September 19, 2016 by Ray in Cloud services, Crowdsourcing, Object storage, R&D measures, storage scalability, Visionary leadershp

We were at Scality last week for Cloud Field Day 1 (CFD1) and one of the items they discussed was their open source S3 driver. (Videos available here).

Scality was on the 25th floor of a downtown San Francisco office tower. And the view outside the conference room was great. Giorgio Regni, CTO, Scality, said on the two days a year it wasn’t foggy out, you could even see Golden Gate Bridge from their conference room.

Scality

As you may recall, Scality is an object storage solution that came out of the telecom, consumer networking industry to provide Google/Facebook like storage services to other customers.

Scality RING is a software defined object storage that supports a full complement of interface legacy and advanced protocols including, NFS, CIGS/SMB, Linux FUSE, RESTful native, SWIFT, CDMI and Amazon Web Services (AWS) S3. Scality also supports replication and erasure coding based on object size.

RING 6.0 brings AWS IAM style authentication to Scality object storage. Scality pricing is based on usable storage and you bring your own hardware.

Giorgio also gave a session on the RING’s durability (reliability) which showed they support 13-9’s data availability. He flashed up the math on this but it was too fast for me to take down:)

Scality has been on the market since 2010 and has been having a lot of success lately, having grown 150% in revenue this past year. In the media and entertainment space, Scality has won a lot of business with their S3 support. But their other interface protocols are also very popular.

Why S3?

It looks as if AWS S3 is becoming the defacto standard for object storage. AWS S3 is the largest current repository of objects. As such, other vendors and solution providers now offer support for S3 services whenever they need an object/bulk storage tier behind their appliances/applications/solutions.

This has driven every object storage vendor to also offer S3 “compatible” services to entice these users to move to their object storage solution. In essence, the object storage industry, like it or not, is standardizing on S3 because everyone is using it.

But how can you tell if a vendor’s S3 solution is any good. You could always try it out to see if it worked properly with your S3 application, but that involves a lot of heavy lifting.

However, there is another way. Take an S3 Driver and run your application against that. Assuming your vendor supports all the functionality used in the S3 Driver, it should all work with the real object storage solution.

Open source S3 driver

Scality open sourced their S3 driver just to make this process easier. Now, one could just download their S3server driver (available from Scality’s GitHub) and start it up.

Scality’s S3 driver runs ontop of a Docker Engine so to run it on your desktop you would need to install Docker Toolbox for older Mac or Windows systems or run Docker for Mac or Docker for Windows for newer systems. (We also talked with Docker at CFD1).

Firing up the S3server on my Mac

I used Docker for Mac but I assume the terminal CLI is the same for both.Downloading and installing Docker for Mac was pretty straightforward. Starting it up took just a double click on the Docker application, which generates a toolbar Docker icon. You do need to enter your login password to run Docker for Mac but once that was done, you have Docker running on your Mac.

Open up a terminal window and you have the full Docker CLI at your disposal. You can download the latest S3 Server from Scality’s Docker hub by executing a pull command (docker pull scality/s3server), to fire it up, you need to define a new container (docker run -d –name s3server -p 8000:8000 scality/s3server) and then start it (docker start s3server).

It’s that simple to have a S3server running on your Mac. The toolbox approach for older Mac’s and PC’S is a bit more complicated but seems simple enough.

The data is stored in the container and persists until you stop/delete the container. However, there’s an option to store the data elsewhere as well.

I tried to use CyberDuck to load some objects into my Mac’s S3server but couldn’t get it to connect properly. I wrote up a ticket to the S3server community. It seemed to be talking to the right port, but maybe I needed to do an S3cmd to initialize the bucket first – I think.

[Update 2016Sep19: Turns out the S3 server getting started doc said you should download an S3 profile for Cyberduck. I didn’t do that originally because I had already been using S3 with Cyberduck. But did that just now and it now works just like it’s supposed to. My mistake]

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Anyways, it all seemed pretty straight forward to run S3server on my Mac. If I was an application developer, it would make a lot of sense to try S3 this way before I did anything on the real AWS S3. And some day, when I grew tired of paying AWS, I could always migrate to Scality RING S3 object storage – or at least that’s the idea.

Comments?

Pure Storage FlashBlade well positioned for next generation storage

Posted on June 16, 2016June 17, 2016 by Ray in Distributed computing, Ethernet, File Storage, NFS throughput, R&D measures, Software Defined Network, SSD storage, Strategic Inflection Points, System effectiveness

Sometimes, long after I listen to a vendor’s discussion, I come away wondering why they do what they do. Oftentimes, it passes but after a recent session with Pure Storage at SFD10, it lingered.

Why engineer storage hardware?

In the last week or so, executives at Hitachi mentioned that they plan to reduce hardware R&D activities for their high end storage. There was much confusion what it all meant but from what I hear, they are ahead now, and maybe it makes more sense to do less hardware and more software for their next generation high end storage. We have talked about hardware vs. software innovation a lot (see recent post: TPU and hardware vs. software innovation [round 3]).
Continue reading “Pure Storage FlashBlade well positioned for next generation storage” →

An analyst forecasting contest ala SuperForecasting & 1st #Storage-QoW

Posted on December 8, 2015January 26, 2016 by Ray in Crowdsourcing, Decision making, Forecasting, QoW 2015, R&D measures, Scenario planning

I recently read the book SuperForecasting: the art and science of prediction by P. E. Tetlock & D. Gardner. Their Good Judgement Project has been running for years now and the book is the results of their experiments. I thought it was a great book.

But it also got me to thinking, how can industry analysts do a better job at forecasting storage trends and events?

Impossible to judge most analyst forecasts

One thing the book mentioned was that typically analyst/pundit forecasts are too infrequent, vague and time independent to be judge-able as to their accuracy. I have committed this fault as much as anyone in this blog and on our GreyBeards on Storage podcast (e.g. see our Yearend podcast videos…).

What do we need to do differently?

The experiments documented in the book show us the way. One suggestion is to start putting time durations/limits on all forecasts so that we can better assess analyst accuracy. The other is to start estimating a probability for a forecast and updating your estimate periodically when new information becomes available. Another is to document your rational for making your forecast. Also, do post mortems on both correct and incorrect forecasts to learn how to forecast better.

Finally, make more frequent forecasts so that accuracy can be assessed statistically. The book discusses Brier scores as a way of scoring the accuracy of forecasters.

How to be better forecasters?

In the back of the book the author’s publish a list of helpful hints or guidelines to better forecasting which I will summarize here (read the book for more information):

Triage – focus on questions where your work will pay off. For example, try not to forecast anything that’s beyond say 5 years out, because there’s just too much randomness that can impact results.
Split intractable problems into tractable ones – the author calls this Fermizing (after the physicist) who loved to ballpark answers to hard questions by breaking them down into easier questions to answer. So decompose problems into simpler (answerable) problems.
Balance inside and outside views – search for comparisons (outside) that can be made to help estimate unique events and balance this against your own knowledge/opinions (inside) on the question.
Balance over- and under-reacting to new evidence – as forecasts are updated periodically, new evidence should impact your forecasts. But a balance has to be struck as to how much new evidence should change forecasts.
Search for clashing forces at work – in storage there are many ways to store data and perform faster IO. Search out all the alternatives, especially ones that can critically impact your forecast.
Distinguish all degrees of uncertainty – there are many degrees of knowability, try to be as nuanced as you can and properly aggregate your uncertainty(ies) across aspects of the question to create a better overall forecast.
Balance under/over confidence, prudence/decisiveness – rushing to judgement can be as bad as dawdling too long. You must get better at both calibration (how accurate multiple forecasts are) and resolution (decisiveness in forecasts). For calibration think weather rain forecasts, if rain tomorrow is 80% probably then over time rain probability estimates should be on average correct. Resolution is no guts no glory, if all your estimates are between 0.4 and 0.6 probable, your probably being to conservative to really be effective.
During post mortems, beware of hindsight bias – e.g., of course we were going to have flash in storage because the price was coming down, controllers were becoming more sophisticated, reliability became good enough, etc., represents hindsight bias. What was known before SSDs came to enterprise storage was much less than this.

There are a few more hints than the above. In the Good Judgement Project, forecasters were put in teams and there’s one guideline that deals with how to be better forecasters on teams. Then, there’s another that says don’t treat these guidelines as gospel. And a third, on trying to balance between over and under compensating for recent errors (which sounds like #4 above).

Again, I would suggest reading the book if you want to learn more.

Storage analysts forecast contest

I think we all want to be better forecasters. At least I think so. So I propose a multi-year long contest, where someone provides a storage question of the week and analyst,s such as myself, provide forecasts. Over time we can score the forecasts by creating a Brier score for each analysts set of forecasts.

I suggest we run the contest for 1 year to see if there’s any improvements in forecasting and decide again next year to see if we want to continue.

Question(s) of the week

But the first step in better forecasting is to have more frequent and better questions to forecast against.

I suggest that the analysts community come up with a question of the week. Then, everyone would get one week from publication to record their forecast. Over time as the forecasts come out we can then score analysts in their forecasting ability.

I would propose we use some sort of hash tag to track new questions, “#storage-QoW” might suffice and would stand for Question of the week for storage.

Not sure if one question a week is sufficient but that seems reasonable.

(#Storage-QoW 2015-001): Will 3D XPoint be GA’d in enterprise storage systems within 12 months?

3D XPoint NVM was announced last July by Intel-Micron (wrote a post about here). By enterprise storage I mean enterprise and mid-range class, shared storage systems, that are accessed as block storage via Ethernet or Fibre Channel as SCSI device protocols or as file storage using SMB or NFS file access protocols. By 12 months I mean by EoD 12/8/2016. By GA’d, I mean announced as generally available and sellable in any of the major IT regions of the world (USA, Europe, Asia, or Middle East).

I hope to have my prediction in by next Monday with the next QoW as well.

Anyone interested in participating please email me at Ray [at] SilvertonConsulting <dot> com and put QoW somewhere in the title. I will keep actual names anonymous unless told otherwise. Brier scores will be calculated starting after the 12th forecast.

Please email me your forecasts. Initial forecasts need to be in by one week after the QoW goes live. You can update your forecasts at any time.

Forecasts should be of the form “[YES|NO] Probability [0.00 to 0.99]”.

Better forecasting demands some documentation of your rational for your forecasts. You don’t have to send me your rational but I suggest you document it someplace you can use to refer back to during post mortems.

Let me know if you have any questions and I will try to answer them here

I could use more storage questions…

Comments?

Photo Credits: Renato Guerreiro, Crystalballer

Blood in the racks

Posted on November 13, 2015 by Ray in R&D measures, Strategic Inflection Points, System effectiveness

Read an ArsTechnica UK article the other day (IBM is trying to solve all of computing’s scaling issues with 5D electronic blood) about IBM Research in Zurich working on supplying electricity and cooling to their super computer servers using a form of electronic blood. What this has to do with 5D is another question entirely.

Why blood?

As we all know mammalian blood provides both cooling and nutrients to organisms within an animal. IBM’s electronic blood would be used to provide thermal cooling to their server circuitry as well as electronic energy to those same circuits.

One of the problems with todays chips is that with more components being added each year, their heat density (W/mm**2) is going up significantly. But the power feeds are also increasing as components counts go up. All of this is leading to a serious problems in trying to cool and power ever denser chips. The article says that for Intel’s recent Ivy Bridge chips, a majority of its 1155 pins are for power delivery and its heat density is ~0.5W/mm**2.

IBM research takes a radical turn

IBM has been working with micro fluidic pathways in their chips to supply cooling to the areas of the chips that need it the most. But by adding electronic charges to these cooling fluids they hope to be able to power their chips as well as cool them with the same mechanism.

Electronic charges are carried in soluble oxygen-reduction (redox) particles that can be oxidized to supply electricity and then reduced for recharge. IBM R&D have shown that their electronic blood charge-discharge cycle can be up to 80% efficient using 1V power.

Not sure I understand why they call in 5D but maybe if you read the IBM research paper (requires paymen) there would be a better explanation. The ArsTechnica paper takes a shot but other than cooling being the 4th dimension and power the 5th dimension, I’m not sure what the other 3 are used for.

Comments?

Moore’s law is still working with new 2D-electronics, just 1nm thin

Posted on July 24, 2015July 29, 2015 by Ray in Market dynamics, R&D measures, Strategy, Visionary leadershp

This week scientists at Oak Ridge National Laboratory have created two dimensional nano-electronic circuits just 1nm tall (see Nature Communications article). Apparently they were able to create one crystal ~~two~~ ~~crystals ontop of one anot~~her, then infused ~~the top~~ that layer with sulfur. With that as a base they used standard scalable photolitographic and electron beam lithographic processing techniques to pattern electronic junctions in the crystal layer and then used a pulsed laser evaporate ~~to burn off selective~~ sulfur atoms from a target ~~(selective sulferization of the material)~~, converting MoSe2 to MoS2. At the end of this process was a 2D electronic circuit just 3 atoms thick, with heterojunctions, molecularly similar to pristine MOS available today, but at much thinner (~1nm) and smaller scale (~5nm).

In other news this month, IBM also announced that they had produced working prototypes of a ~7nm transistor in a processor chip (see NY Times article). IBM sold off their chip foundry a while ago to Global Foundries, but continue working on semiconductor research with SEMATECH, an Albany NY semiconductor research consortium. Recently Samsung and Intel left SEMATECH, maybe a bit too early.

On the other hand, Intel announced they were having some problems getting to the next node in the semiconductor roadmap after their current 14nm transistor chips (see Fortune article). Intel stated that the last two generations took 2.5 years instead of 2 years, and that pace is likely to continue for the foreseeable future. Intel seems to be spending more research and $’s creating low-power or new (GPUs) types of processing than in a mad rush to double transistors every 2 years.

So taking it all in, Moore’s law is still being fueled by Billion $ R&D budgets and the ever increasing demand for more transistors per area. It may take a little longer to double the transistors on a chip, but we can see at least another two generations down the ITRS semiconductor roadmap. That is, if the Oak Ridge research proves manufacturable as it seems to be.

So Moore’s law has at least another generation or two to run. Whether there’s a need for more processing power is anyone’s guess but the need for cheaper flash, non-volatile memory and DRAM is a certainty for as far as I can see.

Comments?

Photo Credits:

Racetrack memory gets rolling

Posted on June 4, 2013 by Ray in R&D measures, SSD storage, Strategic Inflection Points

A recent MIT study showed how new technology can be used to control and write magnetized bits in nano-structures, using voltage alone. This new technique also consumes much less power than using magnets or magnetism as well.

They envision a sort of nano-circuit, -wire or -racetrack with a series of transistor-like structures spaced at regular intervals above it. Nano-bits would be racing around these nano-wires as a series of magnetized domains. These new transitor-like devices would be a sort of onramp for the bits as well as stop-lights/speed limits for the racetrack.

Magnetic based racetrack memory issues

The problems with using magnets to write the bits in nano-racetrack is that magnetism casts a wide shadow and can impact adjacent race tracks, sort of like shingled writes (we last discussed in Shingled magnetic recording disks). The other problem has been a way to (magnetically) control the speed of racing bits so they can be isolated and read or written effectively.

Magneto-ionic racetrack memory solutions

But MIT researchers have discovered a way to use voltage to change the magnetic orientation of a bit on a race track. They also found a way through the use of voltage to precisely control the position of magnetic bits speeding around the track and to electronically isolate and select a bit.

What they have created is sort of a transistor for magnetized domains using ion-rich materials. Voltages can be used to attract or repel those ions and then those ions can interact with flowing magnetic domains to speed up or slow down the movement of magnetic domains.

Thus, the transistor-like device can be set to attract (or speed up) magnetized domains, slow down magnetized domains or stop them and also be used to change the magnetic orientation of a domain. MIT researchers call these devices Magneto-ionic devices.

Racetrack memory redefined

So now we have a way to (electronically) seek to bit data on a race track, a way to precisely (electronically) select bits on the race track, and a way to precisely (electronically) write data on a race track. And presumably, with an appropriate (magnetic) read head, a way to read this data. As an added bonus, apparently data once written on the racetrack requires no additional power to stay magnetized.

So the transistor-like devices are a combination of write heads, motors and brakes for the racetrack memory. Not sure, but if they can write, slow down and speedup magnetic domains, why can’t they read them as well that way the transistor-like devices could be a read head as well.

Why do they need more than one write-head per track. It seems to me that one should suffice for a fairly long track, not unlike disk drives. I suppose more of them would make the track faster to write. But they would all have to operate in tandem, speeding up or stoping the racing bits on the track all together and then starting them all back up, together again. Maybe this way they can write a byte or a word or a chunk of data all at the same time.

In any event, it seems that race track memory took a (literally) quantum leap forward with this new research out of MIT.

Racetrack memory futures

IBM has been talking about race track memory for some time now and this might be the last hurdle to overcome to getting there (we last discussed this in A “few exabytes-a-day” from SKA post).

In addition, there doesn’t appear to be any write cycle, bit duration or the need for erasing whole page issues with this type of technology. So as an underlying storage for a new sort of semi-conductor storage device (SSD) this has significant inherent advantages.

Not to mention that is all based on nano-based device sizes which means that it can pack a lot of bits in very little volume or area. So SSDs based on these racetrack memory technologies will be denser, faster, and require less energy – could you want.

Image: Nürburgring 2012 by Juriën Minke

EMCworld 2013 Day 2

Posted on May 7, 2013 by Ray in Cloud services, desktop virtualization, Information economy, Internet traffic, Mobile computing, R&D measures, Server virtualization, Software Defined Network, Visionary leadershp

The first session of the day was with Joe Tucci EMC Chairman and CEO. He talked about the trends transforming IT today. These include Mobile, Cloud, Big Data and Social Networking. He then discussed IDC’s 1st, 2nd and 3rd computing platform framework where the first was mainframe, the second was client-server and the third is mobile. Each of these platforms had winers and losers. EMC wants definitely to be one of the winners in the coming age of mobile and they are charting multiple paths to get there.

Mainly they will use Pivotal, VMware, RSA and their software defined storage (SDS) product to go after the 3rd platform applications. Pivotal becomes the main enabler to help companies gain value out of the mobile-social networking-cloud computing data deluge. SDS helps provide the different pathways for companies to access all that data. VMware provides the software defined data center (SDDC) where SDS, server virtualization and software defined networking (SDN) live, breathe and interoperate to provide services to applications running in the data center.

Joe started talking about the federation of EMC companies. These include EMC, VMware, RSA and now Pivotal. He sees these four brands as almost standalone entities whose identities will remain distinct and seperate for a long time to come.

Joe mentioned the internet of things or the sensor cloud as opening up new opportunities for data gathering and analysis that dwarfs what’s coming from mobile today. He quoted IDC estimates that says by 2020 there will be 200B devices connected to the internet, today there’s just 2 to 3B devices connected.

Pivotal’s debut

Paul Maritz, Pivotal CEO got up and took us through the Pivotal story. Essentially they have three components a data fabric, an application development fabric and a cloud fabric. He believes the mobile and internet of things will open up new opportunities for organizations to gain value from their data wherever it may lie, that goes well beyond what’s available today. These activities center around consumer grade technologies which 1) store and reason over very large amounts of data; 2) use rapid application development; and 3) operate at scale in an entirely automated fashion.

He mentioned that humans are a serious risk to continuous availability. Automation is the answer to the human problem for the “always on”, consumer grade technologies needed in the future.

Parts of Pivotal come from VMware, Greenplum and EMC with some available today in specific components. However by YE they will come out with Pivotal One which will be the first framework with data, app development and cloud fabrics coupled together.

Paul called Pivotal Labs as the special forces of his service organization helping leading tech companies pull together the awesome apps needed for the technology of tomorrow, consisting of Extreme programming, Agile development and very technically astute individuals. Also, CETAS was mentioned as an analytics-as-a-service group providing such analytics capabilities to gaming companies doing log analysis but believes there’s a much broader market coming.

Paul also showed some impressive numbers on their new Pivotal HD/HAWQ offering which showed it handled many more queries than Hive and Cloudera/Impala. In essence, parts of Pivotal are available today but later this year the whole cloud-app dev-big data framework will be released for the first time.

Next up was a media-analyst event where David Goulden, EMC President and COO gave a talk on where EMC has come from and where they are headed from a business perspective.

Then he and Joe did a Q&A with the combined media and analyst community. The questions were mostly on the financial aspects of the company rather than their technology, but there will be a more focused Q&A session tomorrow with the analyst community.

Joe was asked about Vblock status. He said last quarter they announced it had reached a $1B revenue run rate which he said was the fastest in the industry. Joe mentioned EMC is all about choice, such as Vblock different product offerings, VSpex product offerings and now with ViPR providing more choice in storage.

Sometime today Joe had mentioned that they don’t really do custom hardware anymore. He said of the 13,000 engineers they currently have ~500 are hardware engineers. He also mentioned that they have only one internally designed ASIC in current shipping product.

Then Paul got up and did a Q&A on Pivotal. He believes there’s definitely an opportunity in providing services surrounding big data and specifically mentioned CETAS as offering analytics-as-a-service as well as Pivotal Labs professional services organization. Paul hopes that Pivotal will be $1B revenue company in 5yrs. They already have $300M so it’s well on its way to get there.

Next, there was a very interesting media and analyst session that was visually stimulating from Jer Thorp, co-founder of The Office for Creative Research. And about the best way to describe him is he is a data visualization scientist.

He took some NASA Kepler research paper with very dry data and brought it to life. Also he did a number of analyzes of public Twitter data and showed twitter user travel patterns, twitter good morning analysis, twitter NYT article Retweetings, etc. He also showed a video depicting people on airplanes around the world. He said it is a little known fact but over a million people are in the air at any given moment of the day.

Jer talked about the need for data ethics and an informed data ownership discussion with people about the breadcrumbs they leave around in the mobile connected world of today. If you get a chance, you should definitely watch his session.

Next Juergen Urbanski, CTO T-Systems got up and talked about the importance of Hadoop to what they are trying to do. He mentioned that in 5 years, 80% of all new data will land on Hadoop first. He showed how Hadoop is entirely different than what went before and will take T-Systems in vastly new directions.

Next up at EMCworld main hall was Pat Gelsinger, VMware CEO’s keynote on VMware. The story was all about Software Defined Data Center (SDDC) and the components needed to make this happen. He said data was the fourth factor of production behind land, capital and labor.

Pat said that networking was becoming a barrier to the realization of SDDC and that they had been working on it for some time prior to the Nicera acquisition. But now they are hard at work merging the organic VMware development with Nicera to create VMware NSX a new software defined networking layer that will be deployed as part of the SDDC.

Pat also talked a little bit about how ViPR and other software defined storage solutions will provide the ease of use they are looking for to be able to deploy VMs in seconds.

Pat demo-ed a solution specifically designed for Hadoop clusters and was able to configure a hadoop cluster with about 4 clicks and have it start deploying. It was going to take 4-6 minutes to get it fully provisioned so they had a couple of clusters already configured and they ran a pseudo Hadoop benchmark on it using visual recognition and showed how Vcenter could be used to monitor the cluster in real time operations.

Pat mentioned that there are over 500,000 physical servers running Hadoop. Needless to say VMware sees this as a prime opportunity for new and enhanced server virtualization capabilities.

That’s about it for the major keynotes and media sessions from today.

Tomorrow looks to be another fun day.

SNWUSA Spring 2013 summary

Posted on April 4, 2013June 4, 2013 by Ray in Block Storage, DAS, Disk storage, Ethernet, FC, File Storage, iSCSI, Networking, R&D measures, SSD storage, Storage, Storage performance

For starters the parties were a bit more subdued this year although I heard Wayne’s suite was hopping to 4am last night (not that I would ever be there that late).

And a trend seen the past couple of years was even more evident this year, many large vendors and vendor spokespeople went missing. I heard that there were a lot more analyst presentations this SNW than prior ones although it was hard to quantify. But it did seem that the analyst community was pulling double duty in presentations.

I would say that SNW still provides a good venue for storage marketing across all verticals. But these days many large vendors find success elsewhere, leaving SNW Expo mostly to smaller vendors and niche products. Nonetheless, there were a\ a few big vendors (Dell, Oracle and HP) still in evidence. But EMC, HDS, IBM and NetApp were not showing on the floor.

I would have to say the theme for this years SNW was hybrid storage. It seemed last fall the products that impressed me were either cloud storage gateways or all flash arrays but this year there weren’t as many of these at the show but hybrid storage certainly has arrived.

Best hybrid storage array of the show

It’s hard to pick just one hybrid storage vendor as my top pick, especially since there were at least 3 others talking to me under NDA, but from my perspective the Hybrid vendor of the show had to be Tegile (pronounced I think, as te’-jile). They seemed to have a fully functional system with snapshot, thin provisioning, deduplication and pretty good VMware support (only time I have heard a vendor talk about VASA “stun” support for thin provisioned volumes).

They made the statement that SSD in their system is used as a cache, not a tier. This use is similar to NetApp’s FlashCache and has proven to be a particularly well performing approach to use of hybrid storage. (For more information on that take a look at some of my NFS and recent SPC-1 benchmark review dispatches. How well this is integrated with their home grown dedupe logic is another question.

On the negative side, they seem to be lacking a true HA/dual controller version but could use two separate systems with synch (I think) replication between them to cover this ground?? They also claimed their dedupe had no performance penalty, a pretty bold claim that cries out for some serious lab validation and/or benchmarking to prove. They also offer an all flash version of their storage (but then how can it be used as a cache?).

The marketing team seemed pretty knowledgeable about the market space and they seem to be going after mid-range storage space.

The product supports file (NFS and CIFS/SMB), iSCSI and FC with GigE, 10GbE and 8Gbps FC. They quote “effective” capacities with dedupe enabled but it can be disabled on a volume basis.

Overall, I was impressed by their marketing and the product (what little I saw).

Best storage tool of the show

Moving onto other product categories, it was hard to see anything that caught my eye. Perhaps I have just been to too many storage conferences but I did get somewhat excited when I looked at SwiftTest. Essentially they offer a application profiling, storage modeling, workload generating tool set.

The team seems to be branching out of their traditional vendor market focus and going after large service providers and F100 companies with large storage requirements.

Way back, when I was in Engineering, we were always looking for some information as to how customers actually used storage products. Well what SwiftTest has, is an appliance to instrument your application environment (through network taps/hardware port connections) to monitor your storage IO and create a statistical operational profile of your I/O environment. Then take that profile and play it against a storage configuration model to show how well it’s likely to perform. And if that’s not enough the same appliance can be used to drive a simulated version of the operational profile back onto a storage system.

It offers NFS (v2,v3, v4) CIFS/SMB (SMB1, SMB2, SMB3) FC, iSCSI, and HTTP/REST (what no FCoe?). They mentioned an $8oK price tag for the base appliance (one protocol?) but grows up pretty fast, if you want all of them. They also seem to have three levels of appliances (my guess more performance and more protocols come with the bigger boxes).

Not sure where they top out but simulating an operational profile can be quite complex especially when you have to be able to control data patterns to match deduplication potential in customer data, drive markov chains with probability representations of operational profiles, and actually execute IO operations. They said something about their ports have dedicated CPU cores to insure adequate performance or something similar but still it seems to little to hit high IO workloads.

Like I said, when I was in engineering were searching for this type of solution back in the late 90s and we would have probably bought it in a moment, if it was available.

GoDaddy.com, the domain/web site services provider was one of their customers that used the appliance to test storage configurations. They presented at SNW on some of their results but I missed their session (the case study is available on SwiftTests website).

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In short, SNW had a diverse mixture of end user customers but lacked a full complement of vendors to show off to them. The ratio of vendors to customers has definitely shifted to end-users the last couple of years and if anything has gotten more skewed to end-users, (which paradoxically should appeal to more storage vendors?!).

I talked with lots of end-users, from companies like FedEx, Northrop Grumman and AOL to name just a few big ones. But there were plenty of smaller ones as well.

The show lasted three days and had sessions scheduled all the way to the end. I was surprised at the length and the fact that it started on Tuesday rather than Monday as in years past. Apparently, SNIA and Computerworld are still tweaking the formula.

It seemed to me there were more cancelled sessions than in years past but again this was hard to quantify.

Some of the customers I talked with thought SNW should go to a once a year and can’t understand why it’s still twice a year. Many mentioned VMworld as having taken the place of SNW in being a showplace for storage vendors of all sizes and styles. That and the vendor specific shows from EMC, IBM, Dell and others.

The fall show is moving to Long Beach, CA. Probably, a further experiment to find a formula that works. Let’s hope they succeed.

Comments?