Well, it's Tuesday, and that means IBM announcements!
IBM kicks EMC in the teeth with the announcement of System Storage Easy Tier, a new feature available at no additional charge
on the DS8700 with the R5.1 level microcode. Barry Whyte introduces the concept in his [post this morning
]. I will use SLAM (sub-LUN automatic movement) to refer generically to IBM Easy Tier and EMC FAST v2. EMC has yet to deliver FAST v2, and given that they just recently got full-LUN FAST v1 working a few months ago, it might be next year
before you see EMC sub-LUN FAST v2.
Here are the key features of Easy Tier on the DS8700:
- Sub-LUN Automatic Movement
IBM made it really easy to implement this on the DS8700. Today, you have "extent pools" that can be either SSD-only or HDD-only. With this new announcement, we introduce "mixed" SSD+HDD extent pools. The hottest extents are moved to SSD, and cooler extents are moved down to HDD. The support applies to both Fixed block architecture (FBA) LUNs as well as Count-Key-Data (CKD) volumes. In other words, an individual LUN or CKD volume can have some of its 1GB extents on SSD and other extents on FC or SATA disk.
- Entire-LUN Manual Relocation
Entire-LUN Manual Relocation (ELMR, pronounced "Elmer"?) is similar to what EMC offers now with FAST v1. With this feature, you can now relocate an entire LUN non-disruptively from any extent pool to any other extent pool. You can relocate LUNs from an SSD-only or HDD-only pool over to a new Easy Tier-managed "mixed" pool, or take a LUN out of Easy Tier management by moving it to an SSD-only or HDD-only pool. Of course, this support also applies to both Fixed block architecture (FBA) LUNs as well as Count-Key-Data (CKD) volumes.
This feature also can be used to relocate LUNs and CKD volumes from FC to SATA pools, from RAID-10 to RAID-5 pools, and so on.
- Pool Mergers
What if you already have SSD-only and HDD-only pools and want to use Easy Tier? You can now merge pools to create a "mixed" pool.
- SSD Mini-Packs
Before this announcement, you had to buy 16 solid-state drives at a time, called Mega-packs. Now, you can choose to buy just 8 SSD at a time, called Mini-packs. It turns out that just moving as little as 10 percent of your data from Fibre Channel disk over to Solid-State with Easy Tier can result in up to 300 to 400 percent performance improvement. IBM plans to publish formal SPC-1 benchmark results using Easy Tier-managed mixed extent pool in a few weeks.
- Storage Tier Advisor Tool (STAT)
Don't have SSD yet, or not sure how awesome Easy Tier will be for your data center? The IBM Storage Tier Advisor Tool will analyze your extents and estimate how much benefit you will derive if you implement Easy Tier with various amounts of SSD. Those clients with R5.1 microcode on their DS8700 can download from the [DS8700 FTP site].
To learn more, see the [Easy Tier landing page] and the 10-page Easy Tier chapter in [DS8000 Introduction and Planning Guide]. IBM also had announcements regarding LTO-5 tape, N series and XIV storage systems, which I will get to in later posts.
technorati tags: IBM, Easy Tier, SLAM, ELMR, DS8700, SSD, HDD, extent pool, FBA, CKD, LUN, FC, SATA, disk, storage, RAID-5, RAID-10, Mega-Pack, Mini-Pack
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
The IBM Challenge was a big success. One of the contestants, Ken Jennings, [welcomes our new computer overlords]. Congratulations are in order to the IBM Research team who pulled off this Herculean effort!
Some folks have poked fun at some of the odd responses and wager amounts from the IBM Watson computer during the three-day tournament. Others were surprised as I was that the impressive feat was done with less than 1TB of stored data. Here is what John Webster wrote in CNET yesterday, in hist article [What IBM's Watson says to storage systems developers]:
"All well and good. But here's what I find most interesting as a result of what IBM has done in response to the Grand Challenge that motivated Watson's creators. We know, from Tony Pearson's blog, that the foundation of Watson's data storage system is a modified IBM SONAS cluster with a total of 21.6TB of raw capacity. But Pearson also reveals another very significant, and to me, surprising data point: "When Watson is booted up, the 15TB of total RAM are loaded up, and thereafter the DeepQA processing is all done from memory. According to IBM Research, the actual size of the data (analyzed and indexed text, knowledge bases, etc.) used for candidate answer generation and evidence evaluation is under 1 Terabyte."
What Pearson just said is that the data set Watson actually uses to reach his push-the-button decision would fit on a 1TB drive. So much for big data?"
To better appreciate how difficult the challenge was, and how a small amount of data can answer a billion different questions, I thought I would cover Business Intelligence, Data Retrieval and Text Mining concepts.
Let's start with Business Intelligence.
[Seth Grimes] pointed me to this quote from [A Business Intelligence System], written by Hans Peter Luhn back in October 1958 IBM Journal.
"In this paper, business is a collection of activities carried
on for whatever purpose, be it science, technology,
commerce, industry, law, government, defense, et cetera.
The communication facility serving the conduct of a business
(in the broad sense) may be referred to as an intelligence
system. The notion of intelligence is also defined
here, in a more general sense, as the ability to apprehend
the interrelationships of presented facts in such a way as
to guide action towards a desired goal."
Ideally, when you need "Business Intelligence" to help you make a better decision, you perform data retrieval from a structured database for the specific information you are looking for. In other cases, you might be looking for insight, patterns or trends. In that case, you go "data mining" against your structured databases.
Here's a simple example. John runs a fruit stand. One day, he kept track of how many apples and oranges were bought by men and women. How many questions can we ask against this small set of data? Let's count them:
- How many apples were sold to men?
- How many apples were sold to women?
- How many oranges were sold to men?
- How many oranges were sold to women?
But wait! For each row and column, we can combine them into totals.
- How many apples were sold in total?
- How many oranges were sold in total?
- How many fruit in total were sold to men?
- How many fruit in total were sold to women?
- How many fruit in total were sold?
|Total||63||50%||63||50%||126||But wait, there's more! Each row and column can be evaluated for relative percentages, as well as percentages of each cell compared to the total. You could make five relevant pie-charts from this data. This results in 16 more questions, such as:
- Of the fruit purchased by men, what percentage for apples?
- Of all the apples purchased, what percentage by women?
And that's not including more ethereal questions, such as:
- Are there gender-specific preferences for different types of fruit?
- What type of fruit do men prefer?
This is just for a small set, two market segments (by gender) and two products (apples and oranges). However, if you have many market segments (perhaps by age group, zip code, etc.) and many products, the number of queries that can be supported is huge. For small sets of data, you can easily do this with a spreadsheet program like IBM Lotus Symphony or Microsoft Excel.
(Photo courtesy of [OLAP, Cubes and Multidimensional Analysis] by Andrew Fryer.)
But why limit yourself to two dimensions? The above example was just for one day's worth of activity, if John captures this data for every day for historical and seasonal trending, it can be represented as a three-dimensional cube. The number of queries becomes astronomical. This is the basis for Online Analytical Processing (OLAP), and three-dimensional tables are often referred to as [OLAP cubes].
Back in 1970, IBM invented the Structured Query Language [SQL], and today, nearly all modern relational databases support this, including IBM DB2, Informix, Microsoft SQL Server, and Oracle DB. SQL poses two challenges. First, you had to structure the data in advance to the way you expect to perform your ad-hoc queries. Deciding the groups and categories in advance can limit the way information is recorded and captured.
Second, you had to be skilled at SQL to phrase your queries correctly to retrieve the data you are after. What ended up happening was that skilled SQL programmers would develop "canned reports" with fixed SQL parameters, so that less-skilled business decision makers could base their decisions from these reports.
IBM has fully integrated stacks to help process structured data, combining servers, storage, and advanced analytics software into a complete appliance. IBM offers the [Smart Analytics System] for robust, customized deployments, and recently acquired [Netezza] for pre-configured, and more rapid deployments.
However, the bigger problem is that more than 80 percent of information is not structured!
Semi-structured data like email provides some searchable fields like From and Subject. The rest of the information is unstructured, such as text files, photographs, video and audio. To look for specific information in unstructured sources can be like looking for a needle in a haystack, and trying to get insight, patterns or trends involves text mining.
IBM is a leader in Business Analytics and has made great progress in dealing with unstructured data. This includes [IBM OmniFind Enterprise Edition], [IBM e-Discovery Manager] and [IBM Cognos Business Intelligence].
This, in effect, is what IBM Watson was able to perform so well this week. Finding the needle in the haystacks of unstructured data from 200 million pages of text stored in its system, combined with the ability to apprehend the interrelationships of meaning and subtle nuance, resulted in an impressive technology demonstration. Certainly, this new technology will be powerful for a variety of use cases across a broad set of industries!
To learn more, read the Arizona Daily Star's article [After 'Jeopardy!' win, IBM program steps out].
technorati tags: IBM, Watson, Jeopardy, Challenge, John Webster, CNET, BI, data mining, Text Mining, OLAP, Arizona, Daily Star
Continuing on the [IBM Storage Launch of February 9], John Sing has offered to write the following guest post about the [announcement] of IBM Scale Out Network Attached Storage [IBM SONAS]. John and I have known each other for a while, traveled the world to work with clients and speak at conferences. He is an Executive IT Consultant on the SONAS team.
[John Sing profile]
Guest Post written by John Sing, IBM San Jose, California
What is IBM SONAS? It’s many things, so let’s start with this list:
- It’s IBM’s delivery of a productized, pre-packaged Scale Out NAS global virtual file server, delivered in a easy-to-use appliance
- IBM’s solution for large enterprise file-based storage requirements, where massive scale in capacity and extreme performance is required, especially for today’s modern analytics-based Competitive Advantage IT applications
- Scales to many petabytes of usable storage and billions of files in a single global namespace
- Provides integrated central management, central deployment of petabyte levels of storage
- Modular commercial-off-the-shelf [COTS] building blocks. I/O, storage, network capacity scale independently of each other. Up to 30 interface nodes and 60 storage nodes, in an IBM General Parallel File System [GPFS]-based cluster. Each 10Gb CEE interface node port is capable of streaming at 900 MB/sec
- Files are written in block-sized chunks, striped over as many multiple disk drives in parallel – aggregating throughput on a massive scale (both read and write), as well as providing auto-tuning, auto-balancing
- Functionality delivered via one program product, IBM SONAS Software, which provides all of above functions, along with clustered CIFS, NFS v2/v3 with session auto-failover, FTP, high availability, and more
IBM SONAS makes automated tiered storage achievable and realistic at petabyte levels:
- Integrated global policy engine file placement, physical management, replication, deletion, archival
- Integrated high performance parallel scan engine capable of identifying files at over 10 million files per minute per node
- Integrated parallel data movement engine to physically relocate the data within tiered storage
And we’re just scratching the surface. IBM has plans to deploy additional protocols, storage hardware options, and software features.
However, the real question of interest should be, “who really needs that much storage capacity and throughput horsepower?”
The answer may surprise you. IMHO, the answer is: almost any modern enterprise that intends to stay competitive. Hmmm…… Consider this: the reason that IT exists today is no longer to simply save cost (that may have been true 10 years ago). Everyone is reducing cost… but how much competitive advantage is purchased through “let’s cut our IT budget by 10% this year”?
Notice that in today’s world, there are (many) bright people out there, changing our world every day through New Intelligence Competitive Advantage analytics-based IT applications such as real time GPS traffic data, real time energy monitoring and redirection, real time video feed with analytics, text analytics, entity analytics, real time stream computing, image recognition applications, HDTV video on demand, etc. Think of how GPS industry, cell phone / Twitter / Facebook, iPhone and iPad applications, as examples, are creating whole new industries and markets almost overnight.
Then start asking yourself, “What's behind these Competitive Advantage IT applications – as they are the ones that are driving all my storage growth? Why do they need so much storage? What do those applications mean for my storage requirements?”
( Read more about Analytics, pages 14-48 of [New Intelligence
for a Smarter Planet - Driving Business Innovation with IBM Analytic Solutions] )
To be “real-time”, long-held IT paradigms are being broken every day. Things like “data proximity”: we can no longer can extract terabytes of data from production databases and load them to a data warehouse – where’s the “real-time” in that? Instead, today’s modern analytics-based applications demand:
- Multiple processes and servers (sometimes numbering in the 100s) simultaneously ….
- Running against hundreds of terabytes of data of live production data, streaming in from expanding number of smarter sensors, input devices, users
- Producing digital image-intensive results that must be programatically sent to an ever increasing number of mobile devices in geographically dispersed storage
- Requiring parallel performance levels, that used to be the domain only of High Performance Computing (HPC)
This is a major paradigm shift in storage – and that is the solution and storage capabilities that IBM SONAS is designed to address. And of course, you should be able to save significant cost through the SONAS global virtual file server consolidation and virtualization as well.
Certainly, this topic warrants more discussion. If you found it interesting, contact me, your local IBM Business Partner or IBM Storage rep to discuss Competitive Advantage IT applications and SONAS further.
technorati tags: , IBM, Scale-Out, NAS, SONAS, John Sing, San+Jose, COTS, Petabytes, CEE, CIFS, NFS, FTP, HPC, New Intelligence, Analytics, Competitive Advantage IT Applications
Are you tired of hearing about Cloud Computing without having any hands-on experience? Here's your chance. IBM has recently launched its IBM Development and Test Cloud beta. This gives you a "sandbox" to play in. Here's a few steps to get started:
- Go to the [IBM Developer & Test in the IBM Cloud beta] dashboard and register for an account. This can be your email address and your own password. You can watch the helpful videos.
- Generate a "key pair". There are two keys. A "public" key that will reside in the cloud, and a "private" key that you download to your personal computer. Don't lose this key.
- Request an IP address. This step is optional, but I went ahead and got a static IP, so I don't have to type in long hostnames like "vm353.developer.ihost.com".
- Request storage space. Again, this step is optional, but you can request a 50GB, 100GB and 200GB LUN. I picked a 200GB LUN. Note that each instance comes with some 10 to 30GB storage already. The advantage to a storage LUN is that it is persistent, and you can mount it to different instances.
- Start an "instance". An "instance" is a virtual machine, pre-installed with whatever software you chose from the "asset catalog". These are Linux images running under Red Hat Enterprise Virtualization (RHEV) which is based on Linux's kernel virtual machine (KVM). When you start an instance, you get to decide its size (small, medium, or large), whether to use your static IP address, and where to mount your storage LUN. On the examples below, I had each instance with a static IP and mounted the storage LUN to /media/storage subdirectory. The process takes a few minutes.
- Download some programs on your personal computer. I downloaded an SSH client called [PuTTY] and an [NX client from NoMachine].
So, now that you are ready to go, what instance should you pick from the catalog? Here are three examples to get you started:
- IBM WebSphere sMASH Application Builder
- Base OS server to run LAMP stack
Next, I decided to try out one of the base OS images. There are a lot of books on Linux, Apache, MySQL and PHP (LAMP) which represents nearly 70 percent of the web sites on the internet. This instance let's you install all the software from scratch. Between Red Hat and Novell SUSE distributions of Linux, Red Hat is focused on being the Hypervisor of choice, and SUSE is focusing on being the Guest OS of choice. Most of the images on the "asset catalog" are based on SLES 10 SP2. However, there was a base OS image of Red Hat Enterprise Linux (RHEL) 5.4, so I chose that.
To install software, you either have to find the appropriate RPM package, or download a tarball and compile from source. To try both methods out, I downloaded tarballs of Apache Web Server and PHP, and got the RPM packages for MySQL. If you just want to learn SQL, there are instances on the asset catalog with DB2 and DB2 Express-C already pre-installed. However, if you are already an expert in MySQL, or are following a tutorial or examples based on MySQL from a classroom textbook, or just want a development and test environment that matches what your company uses in production, then by all means install MySQL.
This is where my SSH client comes in handy. I am able to login to my instance and use "wget" to fetch the appropriate files. An alternative is to use "SCP" (also part of PuTTY) to do a secure copy from your personal computer up to the instance. You will need to do everything via command line interface, including editing files, so I found this [VI cheat sheet] useful. I copied all of the tarballs and RPMs on my storage LUN ( /media/storage ) so as not to have to download them again.
Compiling and configuring them is a different matter. By default, you login as an end user, "idcuser" (which stands for IBM Developer Cloud user). However, sometimes you need "root" level access. Use "sudo bash" to get into root level mode, and this allows you to put the files where they need to be. If you haven't done a configure/make/make install in awhile, here's your chance to relive those "glory days".
In the end, I was able to confirm that Apache, MySQL and PHP were all running correctly. I wrote a simple index.php that invoked phpinfo() to show all the settings were set correctly. I rebooted the instance to ensure that all of the services started at boot time.
- Rational Application Developer over VDI
This last example, I started an instance pre-installed with Rational Application Developer (RAD), which is a full Integrated Development Environment (IDE) for Java and J2EE applications. I used the "NX Client" to launch a virtual desktop image (VDI) which in this case was Gnome on SLES 10 SP2. You might want to increase the screen resolution on your personal computer so that the VDI does not take up the entire screen.
From this VDI, you can launch any of the programs, just as if it were your own personal computer. Launch RAD, and you get the familiar environment. I created a short Java program and launched it on the internal WebSphere Application Server test image to confirm it was working correctly.
If you are thinking, "This is too good to be true!" there is a small catch. The instances are only up and running for 7 days. After that, they go away, and you have to start up another one. This includes any files you had on the local disk drive. You have a few options to save your work:
- Copy the files you want to save to your storage LUN. This storage LUN appears persistent, and continues to exist after the instance goes away.
- Take an "image" of your "instance", a function provided in the IBM Developer and Test Cloud. If you start a project Monday morning, work on it all week, then on Friday afternoon, take an "image". This will shutdown your instance, and backup all of the files to your own personal "asset catalog" so that the next time you request an instance, you can chose that "image" as the starting point.
Another option is to request an "extension" which gives you another 7 days for that instance. You can request up to five unique instances running at the same time, so if you wanted to develop and test a multi-host application, perhaps one host that acts as the front-end web server, another host that does some kind of processing, and a third host that manages the database, this is all possible. As far as I can tell, you can do all the above from either a Windows, Mac or Linux personal computer.
Getting hands-on access to Cloud Computing really helps to understand this technology!
technorati tags: , IBM, Development, Test, Cloud, WebSphere, sMASH, WaveMaker, LAMP, Linux, Apache, MySQL, PHP, Rational, RAD, VDI, , RHEL, RHEV, KVM, SUSE, SLES, Novell, NX, PuTTY, SSH
In my post yesterday [Spreading out the Re-Replication process
], fellow blogger BarryB [aka The Storage Anarchist
]raises some interesting points and questions in the comments section about the new IBM XIV Nextra architecture.I answer these below not just for the benefit of my friends at EMC, but also for my own colleagues within IBM,IBM Business Partners, Analysts and clients that might have similar questions.
- If RAID 5/6 makes sense on every other platform, why not so on the Web 2.0 platform?
Your attempt to justify the expense of Mirrored vs. RAID 5 makes no sense to me. Buying two drives for every one drive's worth of usable capacity is expensive, even with SATA drives. Isn't that why you offer RAID 5 and RAID 6 on the storage arrays that you sell with SATA drives?Let's take a look at various disk configurations, for example 3TB on 750GB SATA drives:
And if RAID 5/6 makes sense on every other platform, why not so on the (extremely cost-sensitive) Web 2.0 platform? Is faster rebuild really worth the cost of 40+% more spindles? Or is the overhead of RAID 6 really too much for those low-cost commodity servers to handle.
- JBOD: 4 drives
- JBOD here is industry slang for "Just a Bunch of Disks" and was invented as the term for "non-RAID".Each drive would be accessible independently, at native single-drive speed, with no data protection. Puttingfour drives in a single cabinet like this provides simplicity and convenience only over four separate drivesin their own enclosures.
- RAID-10: 8 drives
- RAID-10 is a combination of RAID-1 (mirroring) and RAID-0 (striping). In a 4x2 configuration, data is striped across disks 1-4,then these are mirrored across to disks 5-8. You get performance improvement and protection against a singledrive failure.
- RAID-5: 5 drives
- This would be a 4+P configuration, where there would be four drives' worth of data scattered across fivedrives. This gives you almost the same performance improvement as RAID-10, similar protection againstsingle drive failure, but with fewer drives per usable TB capacity.
- RAID-6: 6 drives
- This would be a 4+2P configuration, where the first P represents linear parity, and the second represents a diagonal parity. Similar in performance improvement as RAID-5, but protects against single and double drive failures, and still better than RAID-10 in terms of drives per TB usable capacity.
For all the RAID configurations, rebuild would require a spare drive, but often spares are shared among multiple RAID ranks, not dedicated to a single rank. To this end, you often have to have several spares per I/O loop, and a different set of spares for each kind of speed and capacity. If you had a mix of 15K/73GB, 10K/146GB, and 7200/500GB drives, then you would have three sets of spares to match.
In contrast, IBM XIV's innovative RAID-X approach doesn't requireany spare drives, just spare capacity on existing drives being used to hold data. The objects can be mirroredbetween any two types of drives, so no need to match one with another.
All of these RAID levels represent some trade-off between cost, protection and performance, and IBM offers each of theseon various disk systems platforms. Calculating parity is more complicated than just mirrored copies, but this can be done with specialized chips in cache memory to minimize performance impact.IBM generally recommends RAID-5 for high-performance FC disk, and RAID-6 for slower, large capacity SATA disk.
However, the questionassumes that the drive cost is a large portion of the overall "disk system" cost. It isn't. For example,Jon Toigo discusses the cost of EMC's new AX4 disk system in his post [National Storage Rip-Off Day]:
- EMC is releasing its low end Clariion AX4 SAS/SATA array with 3TB capacity for $8600. It ships with four 750GB SATA drives (which you and I could buy at list for $239 per unit). So, if the disk drives cost $956 (presumably far less for EMC), that means buyers of the EMC wares are paying about $7700 for a tin case, a controller/backplane, and a 4Gbps iSCSI or FC connector. Hmm.
- Dell is offering EMC’s AX4-5 with same configuration for $13,000 adding a 24/7 warranty.
(Note: I checked these numbers. $8599 is the list price that EMC has on its own website. External 750GB drivesavailable at my local Circuit City ranged from $189 to $329 list price. I could not find anything on Dell'sown website, but found [The Register] to confirm the $13,000 with 24x7 warranty figure.)
Disk capacity is a shrinking portion of the total cost of ownership (TCO). In addition to capacity, you are paying forcache, microcode and electronics of the system itself, along with software and services that are included in the mix,and your own storage administrators to deal with configuration and management. For more on this, see [XIV storage - Low Total Cost of Ownership].
- EMC Centera has been doing this exact type of blob striping and protection since 2002
As I've noted before, there's nothing "magic" about it - Centera has been employing the same type of object-level replication for years. Only EMC's engineers have figured out how to do RAID protection instead of mirroring to keep the hardware costs low while not sacrificing availability.
I agree that IBM XIV was not the first to do an object-level architecture, but it was one of the first to apply object-level technologies to the particular "use case" and "intended workload" of Web 2.0 applications.
RAID-5 based EMC Centera was designed insteadto hold fixed-content data that needed to be protected for a specific period of time, such as to meet government regulatory compliance requirements. This is data that you most likelywill never look at again unless you are hit with a lawsuit or investigation. For this reason, it is important to get it on the cheapest storage configuration as possible. Before EMC Centera, customers stored this data on WORM tape and optical media, so EMC came up with a disk-only alternative offering.IBM System Storage DR550 offers disk-level access for themost recent archives, with the ability to migrate to much less expensive tape for the long term retention. The end result is that storing on a blended disk-plus-tape solution can help reduce the cost by a factor of 5x to 7x, making RAID level discussion meaningless in this environment. For moreon this, see my post [OptimizingData Retention and Archiving].
While both the Centera and DR550 are based on SATA, neither are designed for Web 2.0 platforms.When EMC comes out with their own "me, too" version, they will probably make a similar argument.
- IBM XIV Nextra is not a DS8000 replacement
Nextra is anything but Enterprise-class storage, much less a DS8000 replacement. How silly of all those folks to suggest such a thing.
I did searches on the Web and could not find anybody, other than EMC employees, who suggested that IBM XIV Nextra architecture represented a replacement for IBM System Storage DS8000. The IBM XIV press release does not mentionor imply this, and certainly nobody I know at IBM has suggested this.
The DS8000 is designed for a different "use case" andset of "intended workloads" than what the IBM XIV was designed for. The DS8000 is the most popular disk systemfor our IBM System z mainframe platform, for activities like Online Transaction Processing (OLTP) and large databases, supporting ESCON and FICON attachment to high-speed 15K RPM FC drives. Web 2.0 customers that might chooseIBM XIV Nextra for their digital content might run their financial operations or metadata search indexes on DS8000.Different storage for different purposes.
As for the opinion that this is not "enterprise class", there are a variety of definitions that refer to this phrase.Some analysts look at "price band" of units that cost over $300,000 US dollars. Other analysts define this as beingattachable to mainframe servers via ESCON or FICON. Others use the term to refer to five-nines reliability, havingless than 5 minutes downtime per year. In this regard, based on the past two years experience at 40 customer locations,I would argue that it meets this last definition, with non-disruptive upgrades, microcode updates and hot-swappable components.
By comparison, when EMC introduced its object-level Centera architecture, nobody suggested it was the replacement for their Symmetrix or CLARiiON devices. Was it supposed to be?
- Given drive growth rates have slowed, improving utilization is mandatory to keep up with 60-70 percent CAGR
Look around you, Tony- all of your competitors are implementing thin provisioning specifically to drive physical utilization upwards towards 60-80%, and that's on top of RAID 5/RAID 6 storage and not RAID 1. Given that disk drive growth rates and $/GB cost savings have slowed significantly, improving utilization is mandatory just to keep up with the 60-70% CAGR of information growth.
Disk drive capacities have slowed for FC disk because much of the attention and investment has been re-directed to ATA technology. Dollar-per-GB price reduction is slowing for disks in general, as researchers are hitting physicallimitations to the amount of bits they can pack per square inch of disk media, and is now around 25 percent per year.The 60-70 percent Compound Annual Growth Rate (CAGR) is real, and can be even growing faster for Web 2.0providers. While hardware costs drop, the big ticket items to watch will be software, services and storage administrator labor costs.
To this end, IBM XIV Nextra offers thin provisioning and differential space-efficient snapshots. It is designed for 60-90 percent utilization, and can be expanded to larger capacities non-disruptively in a very scalable manner.
Well, I hope that helps clear some things up.
technorati tags: IBM, XIV, Nextra, EMC, BarryB, RAID-0, RAID-1, RAID-5, RAID-6, RAID-10, RAID-X, AX4, Dell, AX4-5, FC, SAS, SATA, iSCSI, TCO, blob, object-level, disk, storage, system, Centera, ESCON, FICON, Symmetrix, CLARiiON, ATA, CAGR, Web2.0
A reader of my blog asked me what seemed like a simple enough question:
Whatever happened to Lotus Approach? I loved that personal db. (thoughit's been awhile...)
Of course, researching an answer, I encountered some interesting new information. Interestingly, everyone tries to "read between the lines" and tries to determine what solution is best.
From a colleague from Lotus:
You can still get [Lotus Approach] as part of Smartsuite.
However, I have to assume his real question is ... "what is the quick and easy way for me to build a lightweight database app like Microsoft Access that I can distribute as a standalone executable?"
To which I would say "Lotus has a program called Approach, which is part of Lotus SmartSuite, which some people still use. However, a lot of the focus in IBM now centers around the lightweight Cloudscape database which IBM acquired from Informix, which is now known as the [open source project called Derby]. Many IBM and Lotus products, such as Lotus Expeditor use the JDBC connection to Derby, which allows you to use Windows, Linux, Flash, etc. ... with no vendor lock in".
I am familiar with Cloudscape, and I evaluated it as a potential database for IBM TotalStorage Productivity Center, when I was the lead architect defining the version 1 release. It runs entirely on Java, which is both a plus and minus. Plus in that it runs anywhere Java runs, but a minus in that it is not optimized for high performance or large scalability. Because of this, we decided instead on using the full commercial DB2 database instead for Productivity Center.
Not to be undone, my colleagues over at DB2 offered a different alternative, [DB2 Express-C], which runs on a variety of Windows, Linux-x86, and Linux on POWER platforms. It is "free" as in beer, not free as in speech, which means you can download and use it today at no charge, and even ship products with it included, but you are not allowed to modify and distribute altered versions of it, as you can with "free as in speech" open source code, as in the case of Derby above (see [Apache License 2.0"] for details).
(If you have no idea what I am talking about in my distinction between "free speech" and "free beer", see Simon Phipps' article[Perspective: Free speech, free beer and free software] orthe definition from the [Free Software Foundation].)
As I see it, DB2 Express-C has two key advantages. First, if you like the free version, you can purchase a "support contract" for those that need extra hand-holding, or are using this as part of a commercial business venture. Second,for those who do prefer vendor lock-in, it is easyto upgrade Express-C to the full IBM DB2 database product, so if you are developing a product intended for use with DB2, you can develop it first with DB2 Express-C, and migrate up to full DB2 commercial version when you are ready.
This is perhaps more information than you probably expected for such a simple question. Meanwhile, I am stilltrying to figure out MySQL as part of my [OLPC volunteer project].
technorati tags: IBM, Lotus, Approach, SmartSuite, TotalStorage, Productivity Center, Cloudscape, Apache, Derby, free, speech, beer, DB2, Express-C, Windows, Linux, POWER, open source
My series last week on IBM Watson (which you can read [here], [here], [here], and [here]) brought attention to IBM's Scale-Out Network Attached Storage [SONAS]. IBM Watson used a customized version of SONAS technology for its internal storage, and like most of the components of IBM Watson, IBM SONAS is commercially available as a stand-alone product.
Like many IBM products, SONAS has gone through various name changes. First introduced by Linda Sanford at an IBM SHARE conference in 2000 under the IBM Research codename Storage Tank, it was then delivered as a software-only offering SAN File System, then as a services offering Scale-out File Services (SoFS), and now as an integrated system appliance, SONAS, in IBM's Cloud Services and Systems portfolio.
If you are not familiar with SONAS, here are a few of my previous posts that go into more detail:
This week, IBM announces that SONAS has set a world record benchmark for performance, [a whopping 403,326 IOPS for a single file system]. The results are based on comparisons of publicly available information from Standard Performance Evaluation Corporation [SPEC], a prominent performance standardization organization with more than 60 member companies. SPEC publishes hundreds of different performance results each quarter covering a wide range of system performance disciplines (CPU, memory, power, and many more). SPECsfs2008_nfs.v3 is the industry-standard benchmark for NAS systems using the NFS protocol.
(Disclaimer: Your mileage may vary. As with any performance benchmark, the SPECsfs benchmark does not replicate any single workload or particular application. Rather, it encapsulates scores of typical activities on a NAS storage system. SPECsfs is based on a compilation of workload data submitted to the SPEC organization, aggregated from tens of thousands of fileservers, using a wide variety of environments and applications. As a result, it is comprised of typical workloads and with typical proportions of data and metadata use as seen in real production environments.)
The configuration tested involves SONAS Release 1.2 on 10 Interface Nodes and 8 Storage Pods, resulting a single file system over 900TB usable capacity.
- 10 Interface Nodes; each with:
- Maximum 144 GB of memory
- One active 10GbE port
- 8 Storage Pods; each with:
- 2 Storage nodes and 240 drives
- Drive type: 15K RPM SAS hard drives
- Data Protection using RAID-5 (8+P) ranks
- Six spare drives per Storage Pod
IBM wanted a realistic "no compromises" configuration to be tested, by choosing:
- Regular 15K RPM SAS drives, rather than a silly configuration full of super-expensive Solid State Drives (SSD) to plump up the results.
- Moderate size, typical of what clients are asking for today. The Goldilocks rule applies. This SONAS is not a small configuration under 100TB, and nowhere close to the maximum supported configuration of 7,200 disks across 30 Interface Nodes and 30 Storage Pods.
- Single file system, often referred to as a global name space, rather than using an aggregate of smaller file systems added together that would be more complicated to manage. Having multiple file systems often requires changes to applications to take advantage of the aggregate peformance. It is also more difficult to load-balance your performance and capacity across multiple file systems. Of course, SONAS can support up to 256 separate file systems if you have a business need for this complexity.
The results are stunning. IBM SONAS handled three times more workload for a single file system than the next leading contender. All of the major players are there as well, including NetApp, EMC and HP.
Congratulations to the SONAS development and test teams! Scale-Out NAS is a competitive space. SONAS can handle not only large streaming files but also small random I/O workloads extraordinarily well. Just in the last two years, to compete against IBM's leadership in this realm, [HP acquired Ibrix], [EMC acquired Isilon] and [Dell has acquired what's left of Exanet's assets], THey have a lot of catching up to do!
technorati tags: IBM, SONAS, Watson, Storage Tank, SFS, SoFS, SBSC, SSD, SAS, , IOPS, SPEC, SPECsfs, SPECsfs2008, SPECsfs2008_nfs.v3, EMC, Isilon, HP, Ibrix, Dell, Exanet, Global Name Space, scale-out,, Watson, IBM Watson, benchmark, performance, record performance, world record, filesystem, file+system, nfs, EMC, NetApp, VNX, Isilon, storage, storage+system, NAS
IBM once again delivers storage innovation!
(Note: The following paragraphs have been updated to clarify the performance tests involved.)
This time, IBM breaks the 1 million IOPS barrier, achieved by running a test workload consisting of a 70/30 mix of random 4K requests. That is 70 percent reads, 30 percent writes, with 4KB blocks. The throughput achieved was 3.5x times that obtained by running the identical workload on the fastest IBM storage system today (IBM System Storage SAN Volume Controller 4.3),
and an estimated EIGHT* times the performance of EMC DMX. With an average response time under 1 millisecond, this solution would be ideal for online transaction processing (OLTP) such as financial recordings or airline reservations.
(*)Note: EMC has not yet published ANY benchmarks of their EMC DMX box with SSD enterprise flash drives (EFD). However, I believe that the performance bottleneck is in their controller and not the back-end SSD or FC HDD media, so I have givenEMC the benefit of the doubt and estimated that their latest EMC DMX4 is as fast as an[IBMDS8300 Turbo] with Fibre Channel drives. If or when EMC publishes benchmarks, the marketplace can make more accurate comparisons. Your mileage may vary.
IBM used 4 TB of Solid State Disk (SSD) behind its IBM SAN Volume Controller (SVC) technology to achieve this amazing result. Not only does this represent a significantly smaller footprint, but it uses only 55 percent of the power and cooling.
The SSD drives are made by [Fusion IO] and are different than those used by EMC made by STEC.
The SVC addresses the one key problem clients face today with competitive disk systems that support SSD enterprise flash drives: choosing what data to park on those expensive drives? How do you decide which LUNs, which databases, or which files should be permanently resident on SSD? With SVC's industry-leading storage virtualization capability, you are not forced to decide. You can move data into SSD and back out again non-disruptively, as needed to meet performance requirements. This could be handy for quarter-end or year-end processing, for example.
For more on this, see the [IBM Press Release] or thearticles in [Network World] by Jon Brodkin, and [Cnet News] by Brooke Crothers.
Our clients have often told us at IBM that performance is one of their top purchase criteria. IBM once again has shown that it listens to the marketplace!
technorati tags: IBM, SVC, million, IOPS, EMC, DMX, Network World, Cnet, Jon Brodkin, Brooke Crothers, benchmark, leading, performance, SSD, EFD, FC, HDD, disk, systems, media
Last week, I got the following comment from Bob Swann:
I am looking for the IBM VM Poster or a picture of the IBM VM "Catch the Wave"
Do you know where I might find it?
Well, Bob, I made some phone calls. The company that published these posters no longer exists, butI found a coworker at the Poughkeepsie Briefing Center who still had the poster on his wall, and he was kind enough to take a picture of it for you.
|VM: The Wave of the Future|
(click thumbnail at left to see larger image)
Some may recognize this as a [mash-up] using as a base the famous Japanese 10-inch by 15-inch block print[The Great Wave off Kanagawa] byartist [Katsushika Hokusai]. I had this as my laptop'swallpaper screen image until last year when I was presenting in Kuala Lumpur, Malaysia. I was told that it reminded people about the horrible tsunami caused by the [Indian Ocean earthquake] back in 2004.I was actually scheduled to fly the last week of December 2004 to Jakarta, Indonesia, but at the last minute ourclient team changed plans. I would have been on route over the Pacific ocean when the tsunami hit, and probably stranded over there for weeks or months until the airports re-opened.
The Wave theme was in part to honor the IBM users group called World Alliance VSE VM and Linux (WAVV) which is havingtheir next meeting [April 18-22, 2008] in Chattanooga, Tennessee. I presentedat this conference back in 1996 in Green Bay, Wisconsin, as part of the IBM Linux for S/390 team. It started onthe Sunday that Wisconsin switched their clocks for [DaylightSaving Time], and the few of us from Arizona or other places that don't both with this, all showed up forbreakfast an hour early.
When I was in Australia last year, I was told the wave that sports fans do, by raising their hands in coordinatedsequence, was called the [Mexican Wave]in most other countries. When I was there, Melbourne was trying to outlaw this practice at their cricket matches.
The "wave" represents a powerful metaphor, from z/VM operating system on System z mainframes to VMware and Xenon Intel-based processor machines, as the direction of virtualization that we are heading for future data centers.The Mexican wave represents a glimpse of what humans can accomplish with collaboration on a globalscale. It can also represent the tidal wave of data arising from nearly 60 percent annual growth instorage capacity. (I had to mention storage eventually, to avoid being completely off-topic on this post!)
I hope this is the graphic you were looking for Bob. If anyone else has wave-themed posters they would like to contribute, please post a comment below.
technorati tags: Bob Swann, IBM poster, z/VM, Japanese, Great Wave, Kanagawa, Katsushika Hokusai, Kuala Lumpur, Malaysia, Indian Ocean, Jakarta, Indonesia, WAVV, Mexican Wave, storage, capacity, growth, Linux,Melbourne, Australia, VMware, Xen