The Economics of Software Defined Storage

I’ve written before about object storage and scale-out software-defined storage. These seem to be ideas whose time has come, but I have also learned that the economics of these solutions need to be examined closely.

If you look to buy high function storage software, with per TB licensing, and premium support, on premium Intel servers with premium support, then my experience is that you have just cornered yourself into old-school economics. I have made this mistake before. Great solution, lousy economics. This is not what Facebook or Google does, by the way.

If you’re going to insist on premium-on-premium then, unless you have very specific drivers for SDS, or extremely large scale, you might be better to go and buy an integrated storage-controller-plus-expansion-trays solution from a storage hardware vendor (and make sure it’s one that doesn’t charge per TB).

With workloads such as analytics and disk-to-disk backups, we are not dealing with transactional systems of record and we should not be applying old-school economics to the solutions. Well managed risk should be in proportion to the critical availability requirements of the data. Which brings me to Open Source.

Open Source software has sometimes meant complexity and poorly tested features and bugs that require workarounds but the variety, maturity and general usability of Open Source storage software has been steadily improving, and feature/bug risks can be managed. The pay-off is software at $0 per usable TB instead of US$1,500 or US$2,000 per usable TB (seriously folks, I’m not just making these vendor prices up).

It should be noted that open source software without vendor support is not the same as unsupported. Community support is at the heart of the Open Source movement. There are also some Open Source storage software solutions that offer an option for full support, so you have choice about how far you want to go.

It’s taken us a while to work out that we can and should be doing all of this, rather than always seeking the most elegant solution, or the one that comes most highly recommended by Gartner, or the one that has the largest market share, or the newest thing from our favorite big vendors.

It’s not always easy and a big part of the success is making sure we can contain the costs of the underlying hardware. Documentation and quoting and design are all considerably harder in this world, because you’re going to have to work out a bunch of this for yourself. Most integrators just don’t have the patience or skill to make it happen reliably, but those that do can deliver significant benefits to their customers.

Right now we’re working solutions based on S3 or iSCSI or NFS scale out storage with options for community or full support. Ideal use cases are analytics, backup target storage, migration off AWS S3 to on-premises to save cost, and test/dev environments for those who are deploying to Amazon S3, but I’m sure you can think of others.

Ben Corrie on Containers… Live in New Zealand

Tempted as I am to start explaining what containers are and why they make sense, I will resist that urge and assume for now you have all realised that they are a big part of our future whether that be on-premises or Public Cloud-based.

Containers are going to bring as much change to Enterprise IT as virtualization did back in the day, and knowing how to do it well is vital to success.

ViFX is bringing Ben Corrie, Containers super-guru, to New Zealand to help get the revolution moving.

Ben blogged about the potential for containers back in June 2015. Click on his photo for a quick recap:

Register now to hear one of the key architects of change in our industry speak in Auckland and Wellington in April, along with deep dive and demos in a 3 hour session. I would suggest to those further afield that this is also worth flying in from Australia, Christchurch etc.

Auckland 19th April

Wellington 21st April

~

And since it’s been a while since I finished a post with a link to youtube, here is The Fall doing “Container Drivers“.

Free Object Storage Seminar – Tues 16th Feb @ViFX

What is object storage and how does it differ from block and file?

Sign up for a free Object Storage seminar – discussion & examples – Tues, 16th Feb, 12-1.30pm, ViFX Auckland. lunch will be provided.

https://www.eventbrite.co.nz/e/object-storage-auckland-registration-19772808001

 

Thank you for your I.T. Support

Back in 2011 I blogged on buying a new car, entitled the anatomy of a purchase. Well, the transmission on the Jag has given out and I am now the proud owner of a Toyota Mark X.

The anatomy of the purchase was however a little different this time. Over the last 4 years and I found that the official Jaguar service agents (25 Kms away) offered excellent support. 25 Kms is not always a convenient distance however, so I did try using local neighbourhood mechanics for minor things, but quickly realized that they were going to struggle with anything more complicated.

Support became my number one priority

When it came to buying a replacement, the proximity of a fully trained and equipped service agent became my number one priority. There is only one such agency in my neighbourhood, and that is Toyota, so my first decision was that I was going to buy a Toyota.

I.T. Support

Coming from a traditional I.T. vendor background my approach to I.T. support has always been that it should be fully contracted 7 x 24, preferably with a 2 hour response time, for anything that business depended on. But something has changed.

Scale-Out Systems

The support requirements for software haven’t really changed, but hardware is now a different game. Clustered systems, scale-out systems, web-scale systems, including hyper-converged (server/storage) systems will typically quickly re-protect a system after a node failure, thereby removing the need for panic-level hardware support response. Scale-out systems have a real advantage over standalone servers and dual controller storage systems in this respect.

It has taken me some time to get used to not having 7×24 on-site hardware support, but the message from customers is that next-business-day service or next+1 is a satisfactory hardware support model for clustered mission-critical systems.

Nutanix gold level support for example, offers next-business-day on-site service (after failure confirmation) or next+1 if the call is logged after 3pm so, given a potential day or two delay, it is worth asking the question “What happens if a second node fails?”

If the second node failure occurs after the data from the first node has been re-protected, then there will only be the same impact as if one host had failed. You can continue to lose nodes in a Nutanix cluster provided the failures happen after the short re-protection time, and until you run out of physical space to re-protect the VM’s. (Readers familiar with the IBM XIV distributed cache grid architecture will also recognise this approach to rinse-and-repeat re-protection.)

This is discussed in more detail in a Nutanix blog post by Andre Leibovici.

To find out more about options for scale-out infrastructure, try talking to ViFX.

Decoupling Storage Performance from Capacity

Decoupling storage performance from storage capacity is an interesting concept that has gained extra attention in recent times. Decoupling is predicated on a desire to scale performance when you need performance and to scale capacity when you need capacity, rather than traditional spindle-based scaling delivering both performance and capacity.

Also relevant is the idea that today’s legacy disk systems are holding back app performance. For example, VMware apparently claimed that 70% of all app performance support calls were caused by external disk systems.

The Business Value of Storage Performance

IT operations have spent the last 10 years trying to keep up with capacity growth, with less focus on performance growth. The advent of flash has however shown that even though you might not have a pressing storage performance problem, if you add flash your whole app environment will generally run faster and that can mean business advantages ranging from better customer experiences to more accurate business decision making.

A Better Customer Experience

My favorite example of performance affecting customer experience is from my past dealings with an ISP of whom I was a residential customer. I was talking to a call centre operator who explained to me that ‘the computer was slow’ and that it would take a while to pull up the information I was seeking. We chatted as he slowly navigated the system, and as we waited, one of the things he was keen to chat about was how much he disliked working for that ISP   : o

I have previously referenced a mobile phone company in the US who replaced all of their call centre storage with flash, specifically so as to deliver a better customer experience. The challenge with that is cost. The CIO was quoted as saying that the cost to go all flash was not much more per TB than he had paid for tier1 storage in the previous buying cycle (i.e. 3 or maybe 5 years earlier). So effectively he was conceding that he was paying more per TB for tier1 storage now than he was some years ago. Because the environment deployed did not decouple performance from capacity however, that company has almost certainly significantly over-provisioned storage performance, hence the cost per TB being higher than on the last buying cycle.

More Accurate Business Decision Making

There are many examples of storage performance improvements leading to better business decisions, most typically in the area of data warehousing. When business intelligence reports have more up to date data in them, and they run more quickly, they are used more often and decisions are more likely to be evidence-based rather than based on intuition. I recall one CIO telling me about a meeting of the executive leadership team of his company some years ago where each exec was asked to write down the name of the company’s largest supplier – and each wrote a different name – illustrating the risk of making decisions based on intuition rather than on evidence/business intelligence.

Decoupling Old School Style

Of course we have always been able to decouple performance and capacity to some extent, and it was traditionally called tiering. You could run your databases on small fast drives RAID10 and your less demanding storage on larger drives with RAID5 or RAID6. What that didn’t necessarily give you was a lot of flexibility.

Products like IBM’s SAN Volume Controller introduced flexibility to move volumes around between tiers in real-time, and more recently VMware’s Storage vMotion has provided a sub-set of the same functionality.

And then sub-lun tiering (Automatic Data Relocation, Easy Tier, FAST, etc) reduced the need for volume migration as a means of managing performance, by automatically promoting hot chunks to flash, and dropping cooler chunks to slower disks. You could decouple performance from capacity somewhat by choosing your flash to disk ratio appropriately, but you still typically had to be careful with these solutions since the performance of, for example, random writes that do not go to flash would be heavily dependent on the disk spindle count and speed.

So for the most part, decoupling storage performance and capacity in an existing disk system has been about adding flash and trying not to hit internal bottlenecks.

Traditional random I/O performance is therefore a function of:

1. the amount/percent of flash cf the data block working set size
2. the number and speed of disk spindles
3. bus and cache (and sometimes CPU) limitations

Two products that bring their own twists to the game:

Nimble Storage

Nimble Storage uses flash to accelerate random reads, and accelerates writes through compression into sequential 4.5MB stripes (compare this to IBM’s Storwize RtC which compresses into 32K chunks and you can see that what Nimble is doing is a little different).

Nimble performance is therefore primarily a function of

1. the amount of flash (read cache)
2. the CPU available to do the compression/write coalescing

The number of spindles is not quite so important when you’re writing 4.5MB stripes. Nimble systems generally support at least 190 TB nett (if I assume 1.5x compression average, or 254 TB if you expect 2x) from 57 disks and they claim that performance is pretty much decoupled from disk space since you will generally hit the wall on flash and CPU before you hit the wall on sequential writes to disk. Also this kind of decoupling allows you to get good performance and capacity in a very small amount of rack space. Nimble also offers CPU scaling in the form of a scale-out four-way cluster.

Nimble have come closer to decoupling performance and capacity than any other external storage vendor I have seen.

PernixData FVP

PernixData Flash Virtualization Platform (FVP) is a software solution designed to build a flash read/write cache inside a VMware ESXi cluster, thereby accelerating I/Os without needing to add anything to your external disk system. PernixData argue that it is more cost effective and efficient to add flash into the ESXi hosts than it is to add them into external storage systems. This has something in common with the current trend for converged scale-out server/storage solutions, but PernixData also works with existing external SAN environments.

There is criticism that flash technologies deployed in external storage are too far away from the app to be efficient. I recall Amit Dave (IBM Distinguished Engineer) recounting an analogy of I/O to eating, for which I have created my own version below:

• Data in the CPU cache is like food in your spoon
• Data in the server RAM is like food on your plate
• Data in the shared Disk System cache is like food in the serving bowl in the kitchen
• Data on the shared Disk System SSDs is like food you can get from your garden
• Data on hard disks is like food in the supermarket down the road

PernixData works by keeping your data closer to the CPU – decoupling performance and capacity by focusing on a server-side caching layer and scaling alongside your compute ESXi cluster. So this is analagous to getting food from your table rather than food from your garden. With PernixData you tend to scale performance as you add more compute nodes, rather than when you add more back-end capacity.

To Decouple or not to Decouple?

Decoupling as a theoretical concept is surely a good thing – independent scaling in two dimensions – and it is especially nice if it can be done without introducing significant extra cost, complexity or management overhead.

It is however probably also fair to say that many other systems can approximate the effect, albeit with a little more complexity.

———————————————————————————————————-

Disclosures:

Jim Kelly holds PernixPrime accreditation from PernixData and is a certified Nimble Storage Sales Professional. ViFX is a reseller of both Nimble Storage and PernixData.

How well do you know your scale-out storage architectures?

The clustered/scale-out storage world keeps getting more and more interesting and for some they would say more and more confusing.

There are too many to list them all here, but here are block diagrams depicting seven interesting storage or converged hardware architectures. See if you can decipher my diagrams and match the labels by choosing between the three sets of options in the multi-choice poll at the bottom of the page:

 

A	VMware EVO: RACK
B	IBM XIV
C	VMware EVO: RAIL
D	Nutanix
E	Nimble
F	IBM GPFS Storage Server (GSS)
G	VMware Virtual SAN

 

 

A	VMware EVO: RACK
B	IBM XIV
C	VMware EVO: RAIL
D	Nutanix
E	Nimble
F	IBM GPFS Storage Server (GSS)
G	VMware Virtual SAN

 

You can read more on VMware’s EVO:RAIL here.

Hypervisor / Storage Convergence

This is simply a re-blogging of an interesting discussion by James Knapp at http://www.vifx.co.nz/testing-the-hyper-convergence-waters/ looking at VMware Virtual SAN. Even more interesting than the blog post however is the whitepaper “How hypervisor convergence is reinventing storage for the pay-as-you-grow era” which ViFX has come up with as a contribution to the debate/discussion around Hypervisor storage.

I would recommend going to the first link for a quick read of what James has to say and then downloading the whitepaper from there for a more detailed view of the technology.

 

 

IBM Software-defined Storage

The phrase ‘Software-defined Storage’ (SDS) has quickly become one of the most widely used marketing buzz terms in storage. It seems to have originated from Nicira’s use of the term ‘Software-defined Networking’ and then adopted by VMware when they bought Nicira in 2012, where it evolved to become the ‘Software-defined Data Center’ including ‘Software-defined Storage’. VMware’s VSAN technology therefore has the top of mind position when we are talking about SDS. I really wish they’d called it something other than VSAN though, so as to avoid the clash with the ANSI T.11 VSAN standard developed by Cisco.

I have seen IBM regularly use the term ‘Software-defined Storage’ to refer to:

1. GPFS
2. Storwize family (which would include FlashSystem V840)
3. Virtual Storage Center / Tivoli Storage Productivity Center

I recently saw someone at IBM referring to FlashSystem 840 as SDS even though to my mind it is very much a hardware/firmware-defined ultra-low-latency system with a very thin layer of software so as to avoid adding latency.

Interestingly, IBM does not seem to market XIV as SDS, even though it is clearly a software solution running on commodity hardware that has been ‘applianced’ so as to maintain reliability and supportability.

Let’s take a quick look at the contenders:

1. GPFS: GPFS is a file system with a lot of storage features built in or added-on, including de-clustered RAID, policy-based file tiering, snapshots, block replication, support for NAS protocols, WAN caching, continuous data protection, single namespace clustering, HSM integration, TSM backup integration, and even a nice new GUI. GPFS is the current basis for IBM’s NAS products (SONAS and V7000U) as well as the GSS (gpfs storage server) which is currently targeted at HPC markets but I suspect is likely to re-emerge as a more broadly targeted product in 2015. I get the impression that gpfs may well be the basis of IBM’s SDS strategy going forward.

2. Storwize: The Storwize family is derived from IBM’s SAN Volume Controller technology and it has always been a software-defined product, but tightly integrated to hardware so as to control reliability and supportability. In the Storwize V7000U we see the coming together of Storwize and gpfs, and at some point IBM will need to make the call whether to stay with the DS8000-derived RAID that is in Storwize currently, or move to the gpfs-based de-clustered RAID. I’d be very surprised if gpfs hasn’t already won that long-term strategy argument.

3. Virtual Storage Center: The next contender in the great SDS shootout is IBM’s Virtual Storage Center and it’s sub-component Tivoli Storage Productivity Center. Within some parts of IBM, VSC is talked about as the key to SDS. VSC is edition dependent but usually includes the SAN Volume Controller / Storwize code developed by IBM Systems and Technology Group, as well as the TPC and FlashCopy Manager code developed by IBM Software Group, plus some additional TPC analytics and automation. VSC gives you a tremendous amount of functionality to manage a large complex site but it requires real commitment to secure that value. I think of VSC and XIV as the polar opposites of IBM’s storage product line, even though some will suggest you do both. XIV drives out complexity based on a kind of 80/20 rule and VSC is designed to let you manage and automate a complex environment.

Commodity Hardware: Many proponents of SDS will claim that it’s not really SDS unless it runs on pretty much any commodity server. GPFS and VSC qualify by this definition, but Storwize does not, unless you count the fact that SVC nodes are x3650 or x3550 servers. However, we are already seeing the rise of certified VMware VSAN-ready nodes as a way to control reliability and supportability, so perhaps we are heading for a happy medium between the two extremes of a traditional HCL menu and a fully buttoned down appliance.

Product Strategy: While IBM has been pretty clear in defining its focus markets – Cloud, Analytics, Mobile, Social, Security (the ‘CAMSS’ message that is repeatedly referred to inside IBM) I think it has been somewhat less clear in articulating a clear and consistent storage strategy, and I am finding that as the storage market matures, smart people are increasingly wanting to know what the vendors’ strategies are. I say vendors plural because I see the same lack of strategic clarity when I look at EMC and HP for example. That’s not to say the products aren’t good, or the roadmaps are wrong, but just that the long-term strategy is either not well defined or not clearly articulated.

It’s easier for new players and niche players of course, and VMware’s Software-defined Storage strategy, for example, is both well-defined and clearly articulated, which will inevitably make it a baseline for comparison with the strategies of the traditional storage vendors.

A/NZ STG Symposium: For the A/NZ audience, if you want to understand IBM’s SDS product strategy, the 2014 STG Tech Symposium in August is the perfect opportunity. Speakers include Sven Oehme from IBM Research who is deeply involved with gpfs development, Barry Whyte from IBM STG in Hursley who is deeply involved in Storwize development, and Dietmar Noll from IBM in Frankfurt who is deeply involved in the development of Virtual Storage Center.

Melbourne – August 19-22

Auckland – August 26-28

Steve Wozniak’s Birthday

Just a quick post to let readers know that I have resigned from IBM after 14 years with the company and I’m looking forward to starting work at ViFX on Monday 11th August, which it seems also happens to be Steve Wozniak‘s birthday.

I will work out in time what this means for the blog (my move to ViFX, not Steve’s birthday) but it’s pretty likely that I will also start looking at some non-IBM technologies – maybe including such things as VMware, Nutanix, Commvault, Actifio, Violin and Nimble Storage.

And having failed to create any meaningful link whatsoever between my move and the birth of the Woz I will leave it at that… until the 11th : )

 

 

My name is Storage and I’ll be your Server tonight…

Ever since companies like Data General moved RAID control into an external disk sub-system back in the early ’90s it has been standard received knowledge that servers and storage should be separate.

While the capital cost of storage in the server is generally lower than for an external centralised storage subsystem, having storage as part of each server creates fragmentation and higher operational management overhead. Asset life-cycle management is also a consideration – servers typically last 3 years and storage can often be sweated for 5 years since the pace of storage technology change has traditionally been slower than for servers.

When you look at some common storage systems however, what you see is that they do include servers that have been ‘applianced’ i.e. closed off to general apps, so as to ensure reliability and supportability.

• IBM DS8000 includes two POWER/AIX servers
• IBM SAN Volume Controller includes two IBM SystemX x3650 Intel/Linux servers
• IBM Storwize is a custom variant of the above SVC
• IBM Storwize V7000U includes a pair of x3650 file heads running RHEL and Tivoli Storage Manager (TSM) clients and Space Management (HSM) clients
• IBM GSS (GPFS Storage Server) also uses a pair of x3650 servers, running RHEL

At one point the DS8000 was available with LPAR separation into two storage servers (intended to cater to a split production/non-production environment) and there was talk at the time of the possibility of other apps such as TSM being able to be loaded onto an LPAR (a feature that was never released).

Apps or features?: There are a bunch of apps that could be run on storage systems, and in fact many already are, except they are usually called ‘features’ rather than apps. The clearest examples are probably in the NAS world, where TSM and Space Management and SAMBA/CTDB and Ganesha/NFS, and maybe LTFS, for example, could all be treated as features.

I also recall Netapp once talking about a Fujitsu-only implementation of ONTAP that could be run in a VM on a blade server, and EMC has talked up the possibility of running apps on storage.

GPFS: In my last post I illustrated an example of using IBM’s GPFS to construct a server-based shared storage system. The challenge with these kinds of systems is that they put onus onto the installer/administrator to get it right, rather than the traditional storage appliance approach where the vendor pre-constructs the system.

Virtualization: Reliability and supportability are vital, but virtualization does allow the possibility that we could have ring-fenced partitions for core storage functions and still provide server capacity for a range of other data-oriented functions e.g. MapReduce, Hadoop, OpenStack Cinder & Swift, as well as apps like TSM and HSM, and maybe even things like compression, dedup, anti-virus, LTFS etc., but treated not so much as storage system features, but more as genuine apps that you can buy from 3rd parties or write yourself, just as you would with traditional apps on servers.

The question is not so much ‘can this be done’, but more, ‘is it a good thing to do’? Would it be a good thing to open up storage systems and expose the fact that these are truly software-defined systems running on servers, or does that just make support harder and add no real value (apart from providing a new fashion to follow in a fashion-driven industry)? My guess is that there is a gradual path towards a happy medium to be explored here.

IBM GPFS – Software Defined Storage

GPFS (General Parallel File System) is one of those very cool technologies that you can do so much with that it’s actually fun to design solutions with it (provided you’re the kind of person that also gets a kick from a nice elegant mathematical proof by induction).

Back in 2010 I was asked by an IBM systems software strategist for my opinion as to whether GPFS had potential as a mainstream product, or if it was best kept back as an underlying component in mainstream solutions. I was strongly in the component camp, but now I almost regret that, because it may be that really the only thing that was holding GPFS back was the lack of its own comprehensive GUI. That is something I still hope will be addressed in the not too distant future.

Anyway, this is a sample design that attempts to show some of the things you can do with GPFS by way of building a software defined storage and server environment.

The central box shows GPFS servers (virtualized in this example) and the left and right boxes show GPFS clients. GPFS also supports ILM policies between disk tiers and out to LTFS tape, as well as optional integration with HSM (via Tivoli Space Management) and fast efficient backup with Tivoli Storage Manager.

There are of course a few caveats and restrictions. Check out the GPFS infocenter for the technical details.

This second diagram shows a simpler view of how to build a highly available software defined storage environment. The example shows two physical servers, but you can add many servers and still have a single storage pool. Mirroring is on a per volume basis. Also you could use GPFS native RAID to build a RAID6 array in each server for example.

IBM FlashSystem 840 for Legacy-free Flash

Flash storage is at an interesting place and it’s worth taking the time to understand IBM’s new FlashSystem 840 and how it might be useful.

A traditional approach to flash is to treat it like a fast disk drive with a SAS interface, and assume that a faster version of traditional systems are the way of the future. This is not a bad idea, and with auto-tiering technologies this kind of approach was mastered by the big vendors some time ago, and can be seen for example in IBM’s Storwize family and DS8000, and as a cache layer in the XIV. Using auto-tiering we can perhaps expect large quantities of storage to deliver latencies around 5 millseconds, rather than a more traditional 10 ms or higher (e.g. MS Exchange’s jetstress test only fails when you get to 20 ms).

Some players want to use all SSDs in their disk systems, which you can do with Storwize for example, but this is again really just a variation on a fairly traditional approach and you’re generally looking at storage latencies down around one or two millseconds. That sounds pretty good compared to 10 ms, but there are ways to do better and I suspect that SSD-based systems will not be where it’s at in 5 years time.

The IBM FlashSystem 840 is a little different and it uses flash chips, not SSDs. It’s primary purpose is to be very very low latency. We’re talking as low as 90 microseconds write, and 135 microseconds read. This is not a traditional system with a soup-to-nuts software stack. FlashSystem has a new Storwize GUI, but it is stripped back to keep it simple and to avoid anything that would impact latency.

This extreme low latency is a unique IBM proposition, since it turns out that even when other vendors use MLC flash chips instead of SSDs, by their own admission they generally still end up with latency close to 1 ms, presumably because of their controller and code-path overheads.

• 2u appliance with hot swap modules, power and cooling, controllers etc
• Concurrent firmware upgrade and call-home support
• Encryption is standard
• Choice of 16G FC, 8G FC, 40G IB and 10G FCoE interfaces
• Choice of upgradeable capacity

Nett of 2-D RAID5	4 modules	8 modules	12 modules
2GB modules	4 TB	12 TB	20 TB
4GB modules	8 TB	24 TB	40 TB

• Also a 2 TB starter option with RAID0
• Each module has 10 flash chips and each chip has 16 planes
• RAID5 is applied both across modules and within modules
• Variable stripe RAID within modules is self-healing

I’m thinking that prime targets for these systems include Databases and VDI, but also folks looking to future-proof their general performance. If you’re making a 5 year purchase, not everyone will want to buy a ‘mature’ SSD legacy-style flash solution, when they could instead buy into a disk-free architecture of the future.

But, as mentioned, FlashSystem does not have a full traditional software stack, so let’s consider the options if you need some of that stuff:

• IMHO, when it comes to replication, databases are usually best replicated using log shipping, Oracle Data Guard etc.
• VMware volumes can be replicated with native VMware server-based tools.
• AIX volumes can be replicated using AIX Geographic Mirroring.
• On AIX and some other systems you can use logical volume mirroring to set up a mirror of your volumes with preferred read set to the FlashSystem 840, and writes mirrored to a V7000 or (DS8000 or XIV etc), thereby allowing full software stack functions on the volumes (on the V7000) without slowing down the reads off the FlashSystem.
• You can also virtualize FlashSystem behind SVC or V7000
• Consider using Tivoli Storage Manager dedup disk to disk to create a DR environment

Right now, FlashSystem 840 is mainly about screamingly low latency and high performance, with some reasonable data center class credentials, and all at a pretty good price. If you have a data warehouse, or a database that wants that kind of I/O performance, or a VDI implementation that you want to de-risk, or a general workload that you want to future-proof, then maybe you should talk to IBM about FlashSystem 840.

Meanwhile I suggest you check out these docs:

• FlashSystem Infocenter
• FlashSystem Implementation Redbook
• Deploying IBM FlashSystem in VMware Environments

• TSM for Data Protection
• TSM for Virtual Environments Deployment

IBM FlashSystem: Feeding the Hogs

IBM has announced its new FlashSystem family following on from the acquisition of Texas Memory Systems (RAMSAN) late last year.

The first thing that interests me is where FlashSystem products are likely to play in 2013 and this graphic is intended to suggest some options. Over time the blue ‘candidate’ box is expected to stretch downwards.

For the full IBM FlashSystem family you can check out the product page at http://www.ibm.com/storage/flash

Probably the most popular product will be the FlashSystem 820, they key characteristics of which are as follows:

Usable capacity options with RAID5

• 10.3 TB per FlashSystem
• 20.6 TB per FlashSystem
• Up to 865 TB usable in a single 42u rack

Latency

• 110 usec read latency
• 25 usec write latency

IOPS

• Up to 525,000 4KB random read
• Up to 430,000 4KB 70/30 read/write
• Up to 280,000 4KB random write

Throughput

• up to 3.3 GB/sec FC
• up to 5 GB/sec IB

Physical

• 4 x 8 GB/sec FC ports
• or 4 x 40 Gbps QDR Infiniband ports
• 300 VA
• 1,024 BTU/hr
• 13.3 Kg
• 1 rack unit

High Availability including 2-Dimensional RAID

• Module level Variable Stripe RAID
• System level RAID5 across flash modules
• Hot swap modules
• eMLC (10 x the endurance of MLC)

For those who like to know how things plug together under the covers, the following three graphics take you through conceptual and physical layouts.

With IBM’s Variable Stripe RAID, if one die fails in a ten-chip stripe, only the failed die is bypassed, and then data is restriped across the remaining nine chips.

Integration with IBM SAN Volume Controller (and Storwize V7000)

The IBM System Storage Interoperation Center is showing these as supported with IBM POWER and IBM System X (Intel) servers, including VMware 5.1 support.

The IBM FlashSystem is all about being fast and resilient. The system is based on FPGA and hardware logic so as to minimize latency. For those customers who want advanced software features like volume replication, snapshots (ironically called FlashCopy), thin provisioning, broader host support etc, the best way to achieve all of that is by deploying FlashSystem 820 behind a SAN Volume Controller (or Storwize V7000). This can also be used in conjunction with Easy Tier, with the SVC/V7000 automatically promoting hot blocks to the FlashSystem.

I’ll leave you with this customer quote:

“With some of the other solutions we tested, we poked and pried at them for weeks to get the performance where the vendors claimed it should be.  With the RAMSAN we literally just turned it on and that’s all the performance tuning we did.  It just worked out of the box.”

—feeding the hogs—

What do you get at an IBM Systems Technical Symposium?

What do you get at an IBM Systems Technical Symposium? Well for the event in Auckland, New Zealand November 13-15 I’ve tried to make the storage content as interesting as possible. If you’re interested in attending, send me an email at jkelly@nz.ibm.com and I will put you in contact with Jacell who can help you get registered. There is of course content from our server teams as well, but my focus has been on the storage content, planned as follows:

Erik Eyberg, who has just joined IBM in Houston from Texas Memory Systems following IBM’s recent acquisition of TMS, will be presenting “RAMSAN – The World’s Fastest Storage”. Where does IBM see RAMSAN fitting in and what is the future of flash? Check out RAMSAN on the web, on twitter, on facebook and on youtube.

Fresh from IBM Portugal and recently transferred to IBM Auckland we also welcome Joao Almeida who will deliver a topic that is sure to be one of the highlights, but unfortunately I can’t tell you what it is since the product hasn’t been announced yet (although if you click here you might get a clue).

Zivan Ori, head of XIV software development in Israel knows XIV at a very detailed level – possibly better than anyone, so come along and bring all your hardest questions! He will be here and presenting on:

• XIV Performance – What you need to know
• Looking Beyond the XIV GUI

John Sing will be flying in from IBM San Jose to demonstrate his versatility and expertise in all things to do with Business Continuance, presenting on:

• Big Data – Get IBM’s take on where Big Data is heading and the challenges it presents and also how some of IBM’s products are designed to meet that challenge.
• ProtecTIER Dedup VTL options, sizing and replication
• Active/Active datacentres with SAN Volume Controller Stretched Cluster
• Storwize V7000U/SONAS Global Active Cloud Engine multi-site file caching and replication

Andrew Martin will come in from IBM’s Hursley development labs to give you the inside details you need on three very topical areas:

• Storwize V7000 performance
• Storwize V7000 & SVC 6.4 Real-time Compression
• Storwize V7000 & SVC Thin Provisioning

Senaka Meegama will be arriving from Sydney with three hot topics around VMware and FCoE:

• Implementing SVC & Storwize V7000 in a VMware Environment
• Implementing XIV in a VMware Environment
• FCoE Network Design with IBM System Storage

Jacques Butcher is also coming over from Australia to provide the technical details you all crave on Tivoli storage management:

• Tivoli FlashCopy Manager 3.2 including Vmware Integration
• TSM for Virtual Environments 6.4
• TSM 6.4 Introduction and Update plus TSM Roadmap for 2013

Maurice McCullough will join us from Atlanta, Georgia to speak on:

• The new high-end DS8870 Disk System
• XIV Gen3 overview and tour

Sandy Leadbeater will be joining us from Wellington to cover:

• Storwize V7000 overview
• Scale-Out NAS and V7000U overview

I will be reprising my Sydney presentations with updates:

• Designing Scale Out NAS & Storwize V7000 Unified Solutions
• Replication with SVC and Storwize V7000

And finally, Mike McKenzie will be joining us from Brocade in Australia to give us the skinny on IBM/Brocade FCIP Router Implementation.

ALL YOUR BASE ARE BELONG TO US

There are four reasons I can think of why a company wants to buy another:

1. To take a position in a market you didn’t expect to be in but has suddenly become important to you (e.g. EMC buying VMware)
2. To take a position in a market you did expect to be in, but the internal projects to get you where you wanted have failed (e.g. HP buying 3PAR)
3. To gain mass in a market in which you already play successfully (e.g. Oracle buying JDE and PeopleSoft)
4. To prevent your competitor gaining an asset that they could use to attack your market (e.g. Oracle buying Sun/MySQL)

Is it time for the Enterprise Linux Server?

IBM’s Z10 Enterprise Linux Server is an interesting alternative to a large-scale VMware deployment. Essentially, any Linux workload that is a good fit for being virtualised with Vmware is a good fit for being virtualised on Z10.

XIV Async (Snapshot) Replication

Snapshot-based Replication/Mirroring:

I thought it might be worth taking a quick look at async (snapshot) replication/mirroring which was released for XIV earlier this year with 10.2.0.a of the firmware. XIV async is similar in concept to Netapp’s async SnapMirror, both are snapshot based and both consume snapshot space as a part of the mirroring process. One difference of course is that with XIV both async and sync replication are included in the base price of the XIV, there is no added licence fee or maintenance fee to pay. I’d call it ‘free’ but I’d just get another bunch of people on twitter telling me they still haven’t received their free XIVs yet…