Tony Pearson is a Master Inventor and Senior IT Architect for the IBM Storage product line at the
IBM Executive Briefing Center in Tucson Arizona, and featured contributor
to IBM's developerWorks. In 2016, Tony celebrates his 30th year anniversary with IBM Storage. He is
author of the Inside System Storage series of books. This blog is for the open exchange of ideas relating to storage and storage networking hardware, software and services.
(Short URL for this blog: ibm.co/Pearson )
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Continuing my rant from Monday's post [Time for a New Laptop], I got my new laptop Wednesday afternoon. I was hoping the transition would be quick, but that was not the case. Here were my initial steps prior to connecting my two laptops together for the big file transfer:
Document what my old workstation has
Back in 2007, I wrote a blog post on how to [Separate Programs from Data]. I have since added a Linux partition for dual-boot on my ThinkPad T60.
Windows XP SP3 operating system and programs
Red Hat Enterprise Linux 5.4
My Documents and other data
I also created a spreadsheet of all my tools, utilities and applications. I combined and deduplicated the list from the following sources:
Control Panel -> Add/Remove programs
Start -> Programs panels
Program taskbar at bottom of screen
The last one was critical. Over the years, I have gotten in the habit of saving those ZIP or EXE files that self-install programs into a separate directory, D:/Install-Files, so that if I had to unintsall an application, due to conflicts or compatability issues, I could re-install it without having to download them again.
So, I have a total of 134 applications, which I have put into the following rough categories:
AV - editing and manipulating audio, video or graphics
Files - backup, copy or manipulate disks, files and file systems
Browser - Internet Explorer, Firefox, Opera and Google Chrome
Communications - Lotus Notes and Lotus Sametime
Connect - programs to connect to different Web and Wi-Fi services
Demo - programs I demonstrate to clients at briefings
Drivers - attach or sync to external devices, cell phones, PDAs
Games - not much here, the basic solitaire, mindsweeper and pinball
Help Desk - programs to diagnose, test and gather system information
Projects - special projects like Second Life or Lego Mindstorms
Lookup - programs to lookup information, like American Airlines TravelDesk
Meeting - I have FIVE different webinar conferencing tools
Office - presentations, spreadsheets and documents
Platform - Java, Adobe Air and other application runtime environments
Player - do I really need SIXTEEN different audio/video players?
Printer - print drivers and printer management software
Scanners - programs that scan for viruses, malware and adware
Tools - calculators, configurators, sizing tools, and estimators
Uploaders - programs to upload photos or files to various Web services
Backup my new workstation
My new ThinkPad T410 has a dual-core i5 64-bit Intel processor, so I burned a 64-bit version of [Clonezilla LiveCD] and booted the new system with that. The new system has the following configuration:
Windows XP SP3 operating system, programs and data
There were only 14.4GB of data, it took 10 minutes to backup to an external USB disk. I ran it twice: first, using the option to dump the entire disk, and the second to dump the selected partition. The results were roughly the same.
Run Workstation Setup Wizard
The Workstation Setup Wizard asks for all the pertinent location information, time zone, userid/password, needed to complete the installation.
I made two small changes to connect C: to D: drive.
Changed "My Documents" to point to D:\Documents which will move the files over from C: to D: to accomodate its new target location. See [Microsoft procedure] for details.
Edited C:\notes\notes.ini to point to D:\notes\data to store all the local replicas of my email and databases.
Install Ubuntu Desktop 10.04 LTS
My plan is to run Windows and Linux guests through virtualization. I decided to try out Ubuntu Desktop 10.04 LTS, affectionately known as Lucid Lynx, which can support a variety of different virtualization tools, including KVM, VirtualBox-OSE and Xen. I have two identical 15GB partitions (sda2 and sda3) that I can use to hold two different systems, or one can be a subdirectory of the other. For now, I'll leave sda3 empty.
Take another backup of my new workstation
I took a fresh new backup of paritions (sda1, sda2, sda6) with Clonezilla.
The next step involved a cross-over Ethernet cable, which I don't have. So that will have to wait until Thursday morning.
I am still wiping the coffee off my computer screen, inadvertently sprayed when I took a sip while reading HDS' uber-blogger Hu Yoshida's post on storage virtualization and vendor lock-in.
HDS is a major vendor for disk storage virtualization, and Hu Yoshida has been around for a while, so I felt it was fair to disagree with some of the generalizations he made to set the record straight. He's been more careful ever since.
However, his latest post [The Greening of IT: Oxymoron or Journey to a New Reality] mentions an expert panel at SNW that includedMark O’Gara Vice President of Infrastructure Management at Highmark. I was not at the SNW conference last week in Orlando, so I will just give the excerpt from Hu's account of what happened:
"Later I had the opportunity to have lunch with Mark O’Gara. Mark is a West Point graduate so he takes a very disciplined approach to addressing the greening of IT. He emphasized the need for measurements and setting targets. When he started out he did an analysis of power consumption based on vendor specifications and came up with a number of 513 KW for his data center infrastructure....
The physical measurements showed that the biggest consumers of power were in order: Business Intelligence Servers, SAN Storage, Robotic tape Library, and Virtual tape servers....
Another surprise may be that tape libraries are such large consumers of power. Since tape is not spinning most of the time they should consume much less power than spinning disk - right? Apparently not if they are sitting in a robotic tape library with a lot of mechanical moving parts and tape drives that have to accelerate and decelerate at tremendous speeds. A Virtual Tape Library with de-duplication factor of 25:1 and large capacity disks may draw significantly less power than a robotic tape library for a given amount of capacity.
Obviously, I know better than to sip coffee whenever reading Hu's blog. I am down here in South America this week, the coffee is very hot and very delicious, so I am glad I didn't waste any on my laptop screen this time, especially reading that last sentence!
In that report, a 5-year comparison found that a repository based on SATA disk was 23 times more expensive overall, and consumed 290 times more energy, than a tape library based on LTO-4 tape technology. The analysts even considered a disk-based Virtual Tape Library (VTL). Focusing just on backups, at a 20:1 deduplication ratio, the VTL solution was still 5 times per expensive than the tape library. If you use the 25:1 ratio that Hu Yoshida mentions in his post above, that would still be 4 times more than a tape library.
I am not disputing Mark O'Gara's disciplined approach. It is possible that Highmark is using a poorly written backup program, taking full backups every day, to an older non-IBM tape library, in a manner that causes no end of activity to the poor tape robotics inside. But rather than changing over to a VTL, perhaps Mark might be better off investigating the use of IBM Tivoli Storage Manager, using progressive backup techniques, appropriate policies, parameters and settings, to a more energy-efficient IBM tape library.In well tuned backup workloads, the robotics are not very busy. The robot mounts the tape, and then the backup runs for a long time filling up that tape, all the meanwhile the robot is idle waiting for another request.
(Update: My apologies to Mark and his colleagues at Highmark. The above paragraph implied that Mark was using badproducts or configured them incorrectly, and was inappropriate. Mark, my full apology [here])
If you do decide to go with a Virtual Tape Library, for reasons other than energy consumption, doesn't it make sense to buy it from a vendor that understands tape systems, rather than buying it from one that focuses on disk systems? Tape system vendors like IBM, HP or Sun understand tape workloads as well as related backup and archive software, and can provide better guidance and recommendations based on years of experience. Asking advice abouttape systems, including Virtual Tape Libraries, from a disk vendor is like asking for advice on different types of bread from your butcher, or advice about various cuts of meat at the bakery.
The butchers and bakers might give you answers, but it may not be the best advice.
Well, it's Tuesday again, and you know what that means? IBM Announcements!
This week, IBM announces the second generation of Storwize V5000 flash and disk storage systems. There are the V5000F All-flash configurations, as well as the V5000 that can support a variety of flash and spinning disk drives.
There are three models:
The V5010 has dual 2-core/2-thread processors and 16GB of cache. It supports thin provisioning, FlashCopy, Easy Tier, and remote mirroring. The base unit includes 1 GbE Ethernet ports for iSCSI host connectivity, with options to add 16GB Fibre Channel, 12Gb SAS, and 10GbE iSCSI/FCoE as well.
The 2U controllers and expansion enclosures can hold either 24 small 2.5-inch drives, or 12 larger 3.5-inch drives. A single control enclosure has two active/active IBM Spectrum Virtualize nodes, and can attach up to 10 expansion enclosures for a maximum of 264 drives.
The V5020 unit has dual 2-core/4-thread processors and up to 32GB of cache. It supports everything the V5010 does, plus encryption. The encryption is done via the Intel AES-NI instruction set to eliminate the need for special "self-encrypting drives" (SED) that other storage devices may require.
The V5030 has dual 6-core/4-thread processors and up to 64GB of cache. It supports everything the V5010 and V5020 do, plus Real-time Compression and external virtualization. The Real-time Compression can achieve up to 80 percent space savings, representing a 5:1 compression ratio.
Each control enclosure can attach to 20 expansion enclosures, which can support 504 internal drives per controller, and up to 1,008 with two controllers (four Spectrum Virtualize nodes) clustered together. This is in addition to the drives in external storage systems virtualized.
If Eskimos have 37 words for "snow", then EMC has perhaps a similar number of names for "failure". I have already covered a few of their past attempts, including [ATMOS], [Invista], and [VPLEX]. Last week, EMC introduced its latest, called XtremeIO.
But rather than focus on XtremeIO's many shortcomings, I thought it would be better to point out the highlights of IBM's All-Flash array, IBM FlashSystem.
But first, a quick story.
Two years ago, I worked the booth at [Oracle OpenWorld 2011]. After a conference attendee had visited the booths of Violin Memory and Pure Storage, he asked me why IBM did not have an all-Flash array.
Of course IBM did, and I showed him the [Storwize V7000]. For example, a 2U model with 18 SSD drives of 400GB each, configured in two RAID-5 ranks 7+P+S could offer 5.6 TB of space, running up to 250,000 IOPS at sub-millisecond response times.
Why didn't IBM advertise the Storwize V7000 as an all-Flash array? I though the question was silly at the time, since the Storwize V7000 supported SSD, 15K, 10K and 7200 RPM spinning disk, it seemed obvious that it could be configured with only SSD if you chose.
Since then, IBM has added 800GB support to the Storwize V7000, doubling the capacity. More importantly, IBM acquired Texas Memory Systems, and offers a much better all-Flash array.
Flash can be deployed in three levels. The first is in the server itself, such as with PCiE cards containing Flash chips, limited to applications running on that server only.
The second option is a hybrid disk system, that can intermix Flash-based Solid State Drives (SSD) with regular spinning hard disk drives (HDD). These can be attached to many servers.
The problem with this approach is that when Flash is packaged to pretend to be spinning disk, it undermines some of the performance benefits. Traditional disk system architectures using SCSI commands over Device adapter loops can introduce added latency.
The third fits snuggly in the middle: all-Flash arrays designed from the ground up to be only Flash.
Whereas SSD can typically achieve an I/O latency in the 300 to 1000 microseconds range, IBM FlashSystem can process I/O in the 25 to 110 microsecond range. That is a huge difference!
(FTC Disclosure: The U.S. Federal Trade Commission requires that I mention that I am an IBM employee, and that this post may be considered a paid, celebrity endorsement of both the IBM FlashSystem and IBM Storwize family of products. I have no financial interest in EMC, do not endorse the XtremeIO mentioned here, and was not paid to mention their company or products in any manner.)
Fellow blogger and IBM Master Inventor Barry Whyte has a great comparison table in his blog post [Extreme Blogging]. I thought I would add an added column for the Storwize V7000 with 18 Solid State drives.
IBM FlashSystem 820
IBM Storwize V7000 with SSD
20 Terabytes: 1U
11 Terabytes: 2U
7 Terabytes: 6U
I/O latency (microseconds)
110us (~5x faster)
Maximum I/O per second
NAND Flash type
While it is easy to show that EMC's XtremeIO does not hold a candle to IBM FlashSystems, I think it is more amusing that it is not even as good as a Storwize V7000 with SSD that IBM offered two years ago, long before [EMC acquired XtremeIO company] back in May 2012.
Wrapping up my week's theme of storage optimization, I thought I would help clarify the confusion between data reduction and storage efficiency. I have seen many articles and blog posts that either use these two terms interchangeably, as if they were synonyms for each other, or as if one is merely a subset of the other.
Data Reduction is LOSSY
By "Lossy", I mean that reducing data is an irreversible process. Details are lost, but insight is gained. In his paper, [Data Reduction Techniques", Rajana Agarwal defines this simply:
"Data reduction techniques are applied where the goal is to aggregate or amalgamate the information contained in large data sets into manageable (smaller) information nuggets."
Data reduction has been around since the 18th century.
Take for example this histogram from [SearchSoftwareQuality.com]. We have reduced ninety individual student scores, and reduced them down to just five numbers, the counts in each range. This can provide for easier comprehension and comparison with other distributions.
The process is lossy. I cannot determine or re-create an individual student's score from these five histogram values.
This next example, complements of [Michael Hardy], represents another form of data reduction known as ["linear regression analysis"]. The idea is to take a large set of data points between two variables, the x axis along the horizontal and the y axis along the vertical, and find the best line that fits. Thus the data is reduced from many points to just two, slope(a) and intercept(b), resulting in an equation of y=ax+b.
The process is lossy. I cannot determine or re-create any original data point from this slope and intercept equation.
In this last example, from [Yahoo Finance], reduces millions of stock trades to a single point per day, typically closing price, to show the overall growth trend over the course of the past year.
The process is lossy. Even if I knew the low, high and closing price of a particular stock on a particular day, I would not be able to determine or re-create the actual price paid for individual trades that occurred.
Storage Efficiency is LOSSLESS
By contrast, there are many IT methods that can be used to store data in ways that are more efficient, without losing any of the fine detail. Here are some examples:
Thin Provisioning: Instead of storing 30GB of data on 100GB of disk capacity, you store it on 30GB of capacity. All of the data is still there, just none of the wasteful empty space.
Space-efficient Copy: Instead of copying every block of data from source to destination, you copy over only those blocks that have changed since the copy began. The blocks not copied are still available on the source volume, so there is no need to duplicate this data.
Archiving and Space Management: Data can be moved out of production databases and stored elsewhere on disk or tape. Enough XML metadata is carried along so that there is no loss in the fine detail of what each row and column represent.
Data Deduplication: The idea is simple. Find large chunks of data that contain the same exact information as an existing chunk already stored, and merely set a pointer to avoid storing the duplicate copy. This can be done in-line as data is written, or as a post-process task when things are otherwise slow and idle.
When data deduplication first came out, some lawyers were concerned that this was a "lossy" approach, that somehow documents were coming back without some of their original contents. How else can you explain storing 25PB of data on only 1PB of disk?
(In some countries, companies must retain data in their original file formats, as there is concern that converting business documents to PDF or HTML would lose some critical "metadata" information such as modificatoin dates, authorship information, underlying formulae, and so on.)
Well, the concern applies only to those data deduplication methods that calculate a hash code or fingerprint, such as EMC Centera or EMC Data Domain. If the hash code of new incoming data matches the hash code of existing data, then the new data is discarded and assumed to be identical. This is rare, and I have only read of a few occurrences of unique data being discarded in the past five years. To ensure full integrity, IBM ProtecTIER data deduplication solution and IBM N series disk systems chose instead to do full byte-for-byte comparisons.
Compression: There are both lossy and lossless compression techniques. The lossless Lempel-Ziv algorithm is the basis for LTO-DC algorithm used in IBM's Linear Tape Open [LTO] tape drives, the Streaming Lossless Data Compression (SLDC) algorithm used in IBM's [Enterprise-class TS1130] tape drives, and the Adaptive Lossless Data Compression (ALDC) used by the IBM Information Archive for its disk pool collections.
Last month, IBM announced that it was [acquiring Storwize. It's Random Access Compression Engine (RACE) is also a lossless compression algorithm based on Lempel-Ziv. As servers write files, Storwize compresses those files and passes them on to the destination NAS device. When files are read back, Storwize retrieves and decompresses the data back to its original form.
As with tape, the savings from compression can vary, typically from 20 to 80 percent. In other words, 10TB of primary data could take up from 2TB to 8TB of physical space. To estimate what savings you might achieve for your mix of data types, try out the free [Storwize Predictive Modeling Tool].
So why am I making a distinction on terminology here?
Data reduction is already a well-known concept among specific industries, like High-Performance Computing (HPC) and Business Analytics. IBM has the largest marketshare in supercomputers that do data reduction for all kinds of use cases, for scientific research, weather prediction, financial projections, and decision support systems. IBM has also recently acquired a lot of companies related to Business Analytics, such as Cognos, SPSS, CoreMetrics and Unica Corp. These use data reduction on large amounts of business and marketing data to help drive new sources of revenues, provide insight for new products and services, create more focused advertising campaigns, and help understand the marketplace better.
There are certainly enough methods of reducing the quantity of storage capacity consumed, like thin provisioning, data deduplication and compression, to warrant an "umbrella term" that refers to all of them generically. I would prefer we do not "overload" the existing phrase "data reduction" but rather come up with a new phrase, such as "storage efficiency" or "capacity optimization" to refer to this category of features.
IBM is certainly quite involved in both data reduction as well as storage efficiency. If any of my readers can suggest a better phrase, please comment below.