The technology industry is full of trade-offs. Take for example solar cells that convert sunlight to electricity. Every hour, more energy hits the Earth in the form of sunlight than the entire planet consumes in an entire year. The general trade-off is between energy conversion efficiency versus abundance of materials:
- Get 9-11 percent efficiency using rare materials like indium (In), gallium (Ga) or cadmium (Cd).
- Get only 6.7 percent efficiency using abundant materials like copper (Cu), tin (Sn), zinc (Zn), sulfur (S), and selenium (Se)
IBM has eliminated this trade-off with a record-setting breakthrough last week, demonstrating 9.6 percent efficiency [thin film solar cells using earth-abundant materials].
A second trade-off is exemplified by EMC's recent GeoProtect announcement. This appears similar to the geographic dispersal method introduced by a company called [CleverSafe]. The trade-off is between the amount of space to store one or more copies of data and the protection of data in the event of disaster. Here's an excerpt from fellow blogger Chuck Hollis (EMC) titled ["Cloud Storage Evolves"]:
"Imagine a average-sized Atmos network of 9 nodes, all in different time zones around the world. And imagine that we were using, say, a 6+3 protection scheme.
The implication is clear: any 3 nodes could be completely lost: failed, destroyed, seized by the government, etc.
-- and the information could be completely recovered from the surviving nodes."
For organizations worried about their information falling into the wrong hands (whether criminal or government sponsored!), any subset of the nodes would yield nothing of value -- not only would the information be presumably encrypted, but only a few slices of a far bigger picture would be lost.
Seized by the government? falling into the wrong hands? Is EMC positioning ATMOS as "Storage for Terrorists"? I can certainly appreciate the value of being able to protect 6PB of data with only 9PB of storage capacity, instead of keeping two copies of 6PB each, the trade-off means that you will be accessing the majority of your data across your intranet, which could impact performance. But, if you are in an illicit or illegal business that could have a third of your facilities "seized by the government", then perhaps you shouldn't house your data centers there in the first place. Having two copies of 6PB each, in two "friendly nations", might make more sense.
(In reality, companies often keep way more than just two copies of data. It is not unheard of for companies to keep three to five copies scattered across two or three locations. Facebook keeps SIX copies of photographs you upload to their website.)
ChuckH argues that the governments that seize the three nodes won't have a complete copy of the data. However, merely having pieces of data is enough for governments to capture terrorists. Even if the striping is done at the smallest 512-byte block level, those 512 bytes of data might contain names, phone numbers, email addresses, credit cards or social security numbers. Hackers and computer forensics professionals take advantage of this.
You might ask yourself, "Why not just encrypt the data instead?" That brings me to the third trade-off, protection versus application performance. Over the past 30 years, companies had a choice, they could encrypt and decrypt the data as needed, using server CPU cycles, but this would slow down application processing. Every time you wanted to read or update a database record, more cycles would be consumed. This forced companies to be very selective on what data they encrypted, which columns or fields within a database, which email attachments, and other documents or spreadsheets.
An initial attempt to address this was to introduce an outboard appliance between the server and the storage device. For example, the server would write to the appliance with data in the clear, the appliance would encrypt the data, and pass it along to the tape drive. When retrieving data, the appliance would read the encrypted data from tape, decrypt it, and pass the data in the clear back to the server. However, this had the unintended consequences of using 2x to 3x more tape cartridges. Why? Because the encrypted data does not compress well, so tape drives with built-in compression capabilities would not be able to shrink down the data onto fewer tapes.
(I covered the importance of compressing data before encryption in my previous blog post
[Sock Sock Shoe Shoe].)
Like the trade-off between energy efficiency and abundant materials, IBM eliminated the trade-off by offering compression and encryption on the tape drive itself. This is standard 256-bit AES encryption implemented on a chip, able to process the data as it arrives at near line speed. So now, instead of having to choose between protecting your data or running your applications with acceptable performance, you can now do both, encrypt all of your data without having to be selective. This approach has been extended over to disk drives, so that disk systems like the IBM System Storage DS8000 and DS5000 can support full-disk-encryption [FDE] drives.
Certainly, something to think about!
technorati tags: , sunlight, solar cells, electricity, indium, gallium, cadmium, copper, tin, zinc, sulfur, selenium, thin+film, efficiency, EMC, Chuck Hollis, GeoProtect, Cleversafe, governement, seizure, Facebook, terrorists, encryption, forensics, hackers, protection, performance, disk, tape
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.
|/dev/sda1||26GB||NTFS||C:||Windows XP SP3 operating system and programs|
|/dev/sda2||12GB||ext3||/(root)||Red Hat Enterprise Linux 5.4|
|/dev/sda6||80GB||NTFS||D:||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
- C:\Program Files
- 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:
|/dev/sda1||320GB||NTFS||C:||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.
- Re-Partition Disk Drive
I burned a 64-bit version of [System Rescue CD] and ran [Gparted] to re-partition this disk into the following:
|/dev/sda1||40GB||NTFS||C:||Windows XP SP3 operating system and programs|
|/dev/sda2||15GB||ext3||/(root)||Ubuntu Desktop 10.04 LTS|
|/dev/sda6||245GB||NTFS||D:||My Documents and other data|
- Redefine Windows directory structure
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.
technorati tags: IBM, Lenovo, ThinkPad, T60, T410, Intel, Clonezilla, SysRescCD, Gparted, Windows, Ubuntu, Linux, Lucid, LTS
Wrapping up my coverage of the annual [2010 System Storage Technical University], I attended what might be perhaps the best session of the conference. Jim Nolting, IBM Semiconductor Manufacturing Engineer, presented the new IBM zEnterprise mainframe, "A New Dimension in Computing", under the Federal track.
The zEnterprises debunks the "one processor fits all" myth. For some I/O-intensive workloads, the mainframe continues to be the most cost-effective platform. However, there are other workloads where a memory-rich Intel or AMD x86 instance might be the best fit, and yet other workloads where the high number of parallel threads of reduced instruction set computing [RISC] such as IBM's POWER7 processor is more cost-effective. The IBM zEnterprise combines all three processor types into a single system, so that you can now run each workload on the processor that is optimized for that workload.
- IBM zEnterprise z196 Central Processing Complex (CPC)
Let's start with the new mainframe z196 central processing complex (CPC). Many thought this would be called the z11, but that didn't happen. Basically, the z196 machine has a maximum 96 cores versus z10's 64 core maximum, and each core runs 5.2GHz instead of z10's cores running at 4.7GHz. It is available in air-cooled and water-cooled models. The primary operating system that runs on this is called "z/OS", which when used with its integrated UNIX System Services subsystem, is fully UNIX-certified. The z196 server can also run z/VM, z/VSE, z/TPF and Linux on z, which is just Linux recompiled for the z/Architecture chip set. In my June 2008 post [Yes, Jon, there is a mainframe that can help replace 1500 servers], I mentioned the z10 mainframe had a top speed of nearly 30,000 MIPS (Million Instructions per Second). The new z196 machine can do 50,000 MIPS, a 60 percent increase!
(Update: Back in 2007, IBM and Sun mutually supported [OpenSolaris on an IBM System z mainframe]. Unfortunately, after Oracle acquired Sun, the OpenSolaris Governing Board has [grown uneasy over Oracle's silence] about the future of OpenSolaris on any platform. The OpenSolaris [download site] identifies 2009.06 as the latest release, but only for x86 and SPARC chip sets. Apparently, the 2010.03 release expected five months ago in March has slipped. Now it looks official that [OpenSolaris is Dead].)
The z196 runs a hypervisor called PR/SM that allows the box to be divided into dozens of logical partitions (LPAR), and the z/VM operating system can also act as a hypervisor running hundreds or thousands of guest OS images. Each core can be assigned a specialty engine "personality": GP for general processor, IFL for z/VM and Linux, zAAP for Java and XML processing, and zIIP for database, communications and remote disk mirroring. Like the z9 and z10, the z196 can attach to external disk and tape storage via ESCON, FICON or FCP protocols, and through NFS via 1GbE and 10GbE Ethernet.
- IBM zEnterprise BladeCenter Extension (zBX)
There is a new frame called the zBX that basically holds two IBM BladeCenter chassis, each capable of 14 blades, so total of 28 blades per zBX frame. For now, only select blade servers are supported inside, but IBM plans to expand this to include more as testing continues. The POWER-based blades can run native AIX, IBM's other UNIX operating system, and the x86-based blades can run Linux-x86 workloads, for example. Each of these blade servers can run a single OS natively, or run a hypervisor to have multiple guest OS images. IBM plans to look into running other POWER and x86-based operating systems in the future.
If you are already familiar with IBM's BladeCenter, then you can skip this paragraph. Basically, you have a chassis that holds 14 blades connected to a "mid-plane". On the back of the chassis, you have hot-swappable modules that snap into the other side of the mid-plane. There are modules for FCP, FCoE and Ethernet connectivity, which allows blades to talk to each other, as well as external storage. BladeCenter Management modules serve as both the service processor as well as the keyboard, video and mouse Local Console Manager (LCM). All of the IBM storage options available to IBM BladeCenter apply to zBX as well.
Besides general purpose blades, IBM will offer "accelerator" blades that will offload work from the z196. For example, let's say an OLAP-style query is issued via SQL to DB2 on z/OS. In the process of parsing the complicated query, it creates a Materialized Query Table (MQT) to temporarily hold some data. This MQT contains just the columnar data required, which can then be transferred to a set of blade servers known as the Smart Analytics Optimizer (SAO), then processes the request and sends the results back. The Smart Analytics Optimizer comes in various sizes, from small (7 blades) to extra large (56 blades, 28 in each of two zBX frames). A 14-blade configuration can hold about 1TB of compressed DB2 data in memory for processing.
- IBM zEnterprise Unified Resource Manager
You can have up to eight z196 machines and up to four zBX frames connected together into a monstrously large system. There are two internal networks. The Inter-ensemble data network (IEDN) is a 10GbE that connects all the OS images together, and can be further subdivided into separate virtual LANs (VLAN). The Inter-node management network (INMN) is a 1000 Mbps Base-T Ethernet that connects all the host servers together to be managed under a single pane of glass known as the Unified Resource Manager. It is based on IBM Systems Director.
By integrating service management, the Unified Resource Manager can handle Operations, Energy Management, Hypervisor Management, Virtual Server Lifecycle Management, Platform Performance Management, and Network Management, all from one place.
- IBM Rational Developer for System z Unit Test (RDz)
But what about developers and testers, such as those Independent Software Vendors (ISV) that produce mainframe software. How can IBM make their lives easier?
Phil Smith on z/Journal provides a history of [IBM Mainframe Emulation]. Back in 2007, three emulation options were in use in various shops:
- Open Mainframe, from Platform Solutions, Inc. (PSI)
- FLEX-ES, from Fundamental Software, Inc.
- Hercules, which is an open source package
None of these are viable options today. Nobody wanted to pay IBM for its Intellectual Property on the z/Architecture or license the use of the z/OS operating system. To fill the void, IBM put out an officially-supported emulation environment called IBM System z Professional Development Tool (zPDT) available to IBM employees, IBM Business Partners and ISVs that register through IBM Partnerworld. To help out developers and testers who work at clients that run mainframes, IBM now offers IBM Rational Developer for System z Unit Test, which is a modified version of zPDT that can run on a x86-based laptop or shared IBM System x server. Based on the open source [Eclipse IDE], the RDz emulates GP, IFL, zAAP and zIIP engines on a Linux-x86 base. A four-core x86 server can emulate a 3-engine mainframe.
With RDz, a developer can write code, compile and unit test all without consuming any mainframe MIPS. The interface is similar to Rational Application Developer (RAD), and so similar skills, tools and interfaces used to write Java, C/C++ and Fortran code can also be used for JCL, CICS, IMS, COBOL and PL/I on the mainframe. An IBM study ["Benchmarking IDE Efficiency"] found that developers using RDz were 30 percent more productive than using native z/OS ISPF. (I mention the use of RAD in my post [Three Things to do on the IBM Cloud]).
What does this all mean for the IT industry? First, the zEnterprise is perfectly positioned for [three-tier architecture] applications. A typical example could be a client-facing web-server on x86, talking to business logic running on POWER7, which in turn talks to database on z/OS in the z196 mainframe. Second, the zEnterprise is well-positioned for government agencies looking to modernize their operations and significantly reduce costs, corporations looking to consolidate data centers, and service providers looking to deploy public cloud offerings. Third, IBM storage is a great fit for the zEnterprise, with the IBM DS8000 series, XIV, SONAS and Information Archive accessible from both z196 and zBX servers.
To learn more, see the [12-page brochure] or review the collection of [IBM Redbooks]. Check out the [IBM Conferences schedule] for an event near you. Next year, the IBM Storage University will be held July 18-22, 2011 in Orlando, Flordia.
technorati tags: IBM, Technical University, zEnterprise, x86, POWER7, RISC, z/OS, Linux, AIX, OpenSolaris, Oracle, FICON, NFS, z196, zBX, DB2, SAO, IEDN, INMN, RDz, ISV, Eclipse, Cloud Computing
A client asked me to explain "Nearline storage" to them. This was easy, I thought, as I started my IBM career on DFHSM, now known as DFSMShsm for z/OS, which was created in 1977 to support the IBM 3850 Mass Storage System (MSS), a virtual storage system that blended disk drives and tape cartridges with robotic automation. Here is a quick recap:
- Online storage is immediately available for I/O. This includes DRAM memory, solid-state drives (SSD), and always-on spinning disk, regardless of rotational speed.
- Nearline storage is not immediately available, but can be made online quickly without human intervention. This includes optical jukeboxes, automated tape libraries, as well as spin-down massive array of idle disk (MAID) technologies.
- Offline storage is not immediately available, and requires some human intervention to bring online. This can include USB memory sticks, CD/DVD optical media, shelf-resident tape cartridges, or other removable media.
These terms and their definitions have been used for decades, and are consistent with or at least similar to definitions I found on [Wikipedia], [Webopedia], [WiseGEEK], and [SearchStorage].
Sadly, it appears a few storage manufacturers and vendors have been misusing the term "Nearline" to refer to "slower online" spinning disk drives. I find this [June 2005 technology paper from Seagate], and this [2002 NetApp Press Release], the latter of which included this contradiction for their "NearStore" disk array. Here is the excerpt:
"Providing online access to reference information—NetApp nearline storage solutions quickly retrieve and replicate reference and archive information maintained on cost-effective storage—medical images, financial models, energy exploration charts and graphs, and other data-intensive records can be stored economically and accessed in multiple locations more quickly than ever"
Which is it, "online access" or "nearline storage"?
If a client asked why slower drives consume less energy or generate less heat, I could explain that, but if they ask why slower drives must have SATA connections, that is a different discussion. The speed of a drive and its connection technology are for the most part independent. A 10K RPM drive can be made with FC, SAS or SATA connection.
I am opposed to using "Nearlne" just to distinguish between four-digit speeds (such as 5400 or 7200 RPM) versus "online" for five-digit speeds (10,000 and 15,000 RPM). The difference in performance between 10K RPM and 7200 RPM spinning disks is miniscule compared to the differences between solid-state drives and any spinning disk, or the difference between spinning disk and tape.
I am also opposed to using the term "Nearline" for online storage systems just because they are targeted for the typical use cases like backup, archive or other reference information that were previously directed to nearline devices like automated tape libraries.
Can we all just agree to refer to drives as "fast" or "slow", or give them RPM rotational speed designations, rather than try to incorrectly imply that FC and SAS drives are always fast, and SATA drives are always slow? Certainly we don't need new terms like "NL-SAS" just to represent a slower SAS connected drive.
technorati tags: IBM, online, nearline, offline, FC, SATA, SAS, NL-SAS, MAID, SSD, DVD, optical, NetApp, Seagate,
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.
To read independent views on IBM's acquisition, read Lauren Whitehouse (ESG) post [Remote Another Chair, Chris Mellor (The Register) article [Storwize Swallowed], or Dave Raffo (SearchStorage.com) article [IBM buys primary data compression].
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.
technorati tags: IBM, data reduction, storage efficiency, histogram, linear regression, thin provisioning, data deduplication, lossy, lossless, EMC, Centera, hash collisions, Information Archive, LTO, LTO-DC, SLDC, ALDC, compression, deduplication, Storwize, supercomputers, HPC, analytics