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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Rich Bourdeau has written a nice article on InfoStor titled [Software as a Service (SaaS) meets Storage]. Last year, IBM acquired Arsenal Digital, and he mentions both in this article.It is interesting how this has evolved over the years.
Rent warehouse space for tapes
I remember when various companies offered remote storage for tapes. These would be temperature and humidity-controlledrooms, with access lists on who could bring tapes in, who could take tapes out, and so on. In the event of thedisaster, someone would collect the appropriate tapes and take them to a recovery site location.
Rent online/nearline storage from a Storage Service Provider (SSP)
SSPs rented storage space on disk, or provided automated tape libraries that could be written to. With tapes being ejected and stored in temperature/humidity-controlled vaults. Electronic vaulting eliminates a lot of theissues with cartridge handling and transportation, is more secure, and faster. Rented disk space, based on a Gigabytes-per-month rate, could be used for whatever the customer wanted. If these were for backups or archive,then the customer has to have their own software, to do their own processing at their own location, sending the data to the remote storage as appropriate, and manage their own administration.
Backup-as-a-Service and Archive-as-a-Service
We are now seeing the SaaS model applied to mundane and routine storage management tasks. New providers can offerthe software to send backups, the disk to write them to, and as needed the tape libraries and cartridges to rollover when the disk space is full. Disk capacity can be sized so that the most recent backups are on immediately accessible for fast recovery.
The same concept can be applied to archives. The key difference between a backup and an archive is that backups areversion-based. You might keep three versions of a backup, the most recent, and two older copies, in case something is wrong with the most recent copy, you can go back to older copies. This could be from undetected corruption of the data itself, or problems with the disk or tape media. An archive, on the other hand, is time-based. You want this data to be kept for a specific period of time, based on an event or fixed period of years.
Since BaaS and AaaS providers know what the data is, have some idea of the policies and usage patterns will be, can then optimize a storage solution that best meets service level agreements.
IBM is doing a bit of year-end housekeeping. The Storage Community (storagecommunity.org) will be discontinued as of January 1, 2017.
IBM will continue to host a community for all of its followers and contributors to share insights on the latest trends in storage at [ibm.co/StorageSolutions].
All of the most recent IBM content from storagecommunity.org will now be available at this new domain. IBM hopes that you will continue to engage in its community of storage industry thought leaders.
If you would like to contribute to the new community, please [register here]. Simply click the silhouette icon in the top right-hand corner of the page and select "register." Input your email address and create a password, then sign in. You will receive an email from IBM with further instructions to get you set up.
IBM's twitter handle (@SmarterStorage) will also be sunset as of January 1, 2017, but I encourage you to follow @IBMStorage, or my own twitter handle @az990tony, for the latest storage news and announcements from IBM.
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.
Last week, fellow IBMer Ron Riffe started his three-part series on the Storage Hypervisor. I discussed Part I already in my previous post [Storage Hypervisor Integration with VMware]. We wrapped up the week with a Live Chat with over 30 IT managers, industry analysts, independent bloggers, and IBM storage experts.
"The idea of shopping from a catalog isn’t new and the cost efficiency it offers to the supplier isn’t new either. Public storage cloud service providers seized on the catalog idea quickly as both a means of providing a clear description of available services to their clients, and of controlling costs. Here’s the idea… I can go to a public cloud storage provider like Amazon S3, Nirvanix, Google Storage for Developers, or any of a host of other providers, give them my credit card, and get some storage capacity. Now, the “kind” of storage capacity I get depends on the service level I choose from their catalog.
Most of today’s private IT environments represent the complete other end of the pendulum swing – total customization. Every application owner, every business unit, every department wants to have complete flexibility to customize their storage services in any way they want. This expectation is one of the reasons so many private IT environments have such a heavy mix of tier-1 storage. Since there is no structure around the kind of requests that are coming in, the only way to be prepared is to have a disk array that could service anything that shows up. Not very efficient… There has to be a middle ground.
Private storage clouds are a little different. Administrators we talk to aren’t generally ready to let all their application owners and departments have the freedom to provision new storage on their own without any control. In most cases, new capacity requests still need to stop off at the IT administration group. But once the request gets there, life for the IT administrator is sweet!
Here comes the request from an application owner for 500GB of new “Database” capacity (one of the options available in the storage service catalog) to be attached to some server. After appropriate approvals, the administrator can simply enter the three important pieces of information (type of storage = “Database”, quantity = 500GB, name of the system authorized to access the storage) and click the “Go” button (in TPC SE it’s actually a “Run now” button) to automatically provision and attach the storage. No more complicated checklists or time consuming manual procedures.
A storage hypervisor increases the utilization of storage resources, and optimizes what is most scarce in your environment. For Linux, UNIX and Windows servers, you typically see utilization rates of 20 to 35 percent, and this can be raised to 55 to 80 percent with a storage hypervisor. But what is most scarce in your environment? Time! In a competitive world, it is not big animals eating smaller ones as much as fast ones eating the slow.
Want faster time-to-market? A storage hypervisor can help reduce the time it takes to provision storage, from weeks down to minutes. If your business needs to react quickly to changes in the marketplace, you certainly don't want your IT infrastructure to slow you down like a boat anchor.
Want more time with your friends and family? A storage hypervisor can migrate the data non-disruptively, during the week, during the day, during normal operating hours, instead of scheduling down-time on an evenings and weekends. As companies adopt a 24-by-7 approach to operations, there are fewer and fewer opportunities in the year for scheduled outages. Some companies get stuck paying maintenance after their warranty expires, because they were not able to move the data off in time.
Want to take advantage of the new Solid-State Drives? Most admins don't have time to figure out what applications, workloads or indexes would best benefit from this new technology? Let your storage hypervisor automated tiering do this for you! In fact, a storage hypervisor can gather enough performance and usage statistics to determine the characteristics of your workload in advance, so that you can predict whether solid-state drives are right for you, and how much benefit you would get from them.
Want more time spent on strategic projects? A storage hypervisor allows any server to connect to any storage. This eliminates the time wasted to determine when and how, and let's you focus on the what and why of your more strategic transformational projects.
If this sounds all too familiar, it is similar to the benefits that one gets from a server hypervisor -- better utilization of CPU resources, optimizing the management and administration time, with the agility and flexibility to deploy new technologies in and decommission older ones out.
"Server virtualization is a fairly easy concept to understand: Add a layer of software that allows processing capability to work across multiple operating environments. It drives both efficiency and performance because it puts to good use resources that would otherwise sit idle.
Storage virtualization is a different animal. It doesn't free up capacity that you didn't know you had. Rather, it allows existing storage resources to be combined and reconfigured to more closely match shifting data requirements. It's a subtle distinction, but one that makes a lot of difference between what many enterprises expect to gain from the technology and what it actually delivers."
Jon Toigo on his DrunkenData blog brings back the sanity with his post [Once More Into the Fray]. Here is an excerpt:
"What enables me to turn off certain value-add functionality is that it is smarter and more efficient to do these functions at a storage hypervisor layer, where services can be deployed and made available to all disk, not to just one stand bearing a vendor’s three letter acronym on its bezel. Doesn’t that make sense?
I think of an abstraction layer. We abstract away software components from commodity hardware components so that we can be more flexible in the delivery of services provided by software rather than isolating their functionality on specific hardware boxes. The latter creates islands of functionality, increasing the number of widgets that must be managed and requiring the constant inflation of the labor force required to manage an ever expanding kit. This is true for servers, for networks and for storage.
Can we please get past the BS discussion of what qualifies as a hypervisor in some guy’s opinion and instead focus on how we are going to deal with the reality of cutting budgets by 20% while increasing service levels by 10%. That, my friends, is the real challenge of our times."
Did you miss out on last Friday's Live Chat? We are doing it again this Friday, covering parts I and II of Ron's posts, so please join the conversation! The virtual dialogue on this topic will continue in another [Live Chat] on September 30, 2011 from 12 noon to 1pm Eastern Time.
Over on the Tivoli Storage Blog, there is an exchange over the concept of a "Storage Hypervisor". This started with fellow IBMer Ron Riffe's blog post [Enabling Private IT for Storage Cloud -- Part I], with a promise to provide parts 2 and 3 in the next few weeks. Here's an excerpt:
"Storage resources are virtualized. Do you remember back when applications ran on machines that really were physical servers (all that “physical” stuff that kept everything in one place and slowed all your processes down)? Most folks are rapidly putting those days behind them.
In August, Gartner published a paper [Use Heterogeneous Storage Virtualization as a Bridge to the Cloud] that observed “Heterogeneous storage virtualization devices can consolidate a diverse storage infrastructure around a common access, management and provisioning point, and offer a bridge from traditional storage infrastructures to a private cloud storage environment” (there’s that “cloud” language). So, if I’m going to use a storage hypervisor as a first step toward cloud enabling my private storage environment, what differences should I expect? (good question, we get that one all the time!)
The basic idea behind hypervisors (server or storage) is that they allow you to gather up physical resources into a pool, and then consume virtual slices of that pool until it’s all gone (this is how you get the really high utilization). The kicker comes from being able to non-disruptively move those slices around. In the case of a storage hypervisor, you can move a slice (or virtual volume) from tier to tier, from vendor to vendor, and now, from site to site all while the applications are online and accessing the data. This opens up all kinds of use cases that have been described as “cloud”. One of the coolest is inter-site application migration.
A good storage hypervisor helps you be smart.
Application owners come to you for storage capacity because you’re responsible for the storage at your company. In the old days, if they requested 500GB of capacity, you allocated 500GB off of some tier-1 physical array – and there it sat. But then you discovered storage hypervisors! Now you tell that application owner he has 500GB of capacity… What he really has is a 500GB virtual volume that is thin provisioned, compressed, and backed by lower-tier disks. When he has a few data blocks that get really hot, the storage hypervisor dynamically moves just those blocks to higher tier storage like SSD’s. His virtual disk can be accessed anywhere across vendors, tiers and even datacenters. And in the background you have changed the vendor storage he is actually sitting on twice because you found a better supplier. But he doesn’t know any of this because he only sees the 500GB virtual volume you gave him. It’s 'in the cloud'."
"Let’s start with a quick walk down memory lane. Do you remember what your data protection environment looked like before virtualization? There was a server with an operating system and an application… and that thing had a backup agent on it to capture backup copies and send them someplace (most likely over an IP network) for safe keeping. It worked, but it took a lot of time to deploy and maintain all the agents, a lot of bandwidth to transmit the data, and a lot of disk or tapes to store it all. The topic of data protection has modernized quite a bit since then.
Fast forward to today. Modernization has come from three different sources – the server hypervisor, the storage hypervisor and the unified recovery manager. The end result is a data protection environment that captures all the data it needs in one coordinated snapshot action, efficiently stores those snapshots, and provides for recovery of just about any slice of data you could want. It’s quite the beautiful thing."
At this point, you might scratch your head and ask "Does this Storage Hypervisor exist, or is this just a theoretical exercise?" The answer of course is "Yes, it does exist!" Just like VMware offers vSphere and vCenter, IBM offers block-level disk virtualization through the SAN Volume Controller(SVC) and Storwize V7000 products, with a full management support from Tivoli Storage Productivity Center Standard Edition.
SVC has supported every release of VMware since the 2.5 version. IBM is the leading reseller of VMware, so it makes sense for IBM and VMware development to collaborate and make sure all the products run smoothly together. SVC presents volumes that can be formatted for VMFS file system to hold your VMDK files, accessible via FCP protocol. IBM and VMware have some key synergies:
Management integration with Tivoli Storage Productivity Center and VMware vCenter plug-in
VAAI support: Hardware-assisted locking, hardware-assisted zeroing, and hardware-assisted copying. Some of the competitors, like EMC VPLEX, don't have this!
Space-efficient FlashCopy. Let's say you need 250 VM images, all running a particular level of Windows. A boot volume of 20GB each would consume 5000GB (5 TB) of capacity. Instead, create a Golden Master volume. Then, take 249 copies with space-efficient FlashCopy, which only consumes space for the modified portions of the new volumes. For each copy, make the necessary changes like unique hostname and IP address, changing only a few blocks of data each. The end result? 250 unique VM boot volumes in less than 25GB of space, a 200:1 reduction!
Support for VMware's Site Recovery Manager using SVC's Metro Mirror or Global Mirror features for remote-distance replication.
Data center federation. SVC allows you to seamlessly do vMotion from one datacenter to another using its "stretched cluster" capability. Basically, SVC makes a single image of the volume available to both locations, and stores two physical copies, one in each location. You can lose either datacenter and still have uninterrupted access to your data. VMware's HA or Fault Tolerance features can kick in, same as usual.
But unlike tools that work only with VMware, IBM's storage hypervisor works with a variety of server virtualization technologies, including Microsoft Hyper-V, Xen, OracleVM, Linux KVM, PowerVM, z/VM and PR/SM. This is important, as a recent poll on the Hot Aisle blog indicates that [44 percent run 2 or more server hypervisors]!
Join the conversation! The virtual dialogue on this topic will continue in a [live group chat] this Friday, September 23, 2011 from 12 noon to 1pm EDT. Join me and about 20 other top storage bloggers, key industry analysts and IBM Storage subject matter experts to discuss storage hypervisors and get questions answered about improving your private storage environment.