To be specific: What if you needed to transfer data at 1TB per second?

That was the problem faced by the U.S. Department of Energy (DoE) and their Sequoia supercomputer at the Lawrence Livermore National Laboratory (LLNL), one of the fastest supercomputing systems on the planet.

You can read the official press release here. I wanted to get more into the technical details.

People talk a lot about “big data” recently – no clear definition seems to exist, in my opinion it’s something that has some of the following properties:

• Too much data to be processed by a “normal” computer or cluster
• Too much data to work with using a relational DB
• Too much data to fit in a single storage system for performance and/or capacity reasons – or maybe just simply:
• Too much data to process using traditional methods within an acceptable time frame

Clearly, this is a bit loose – how much is “too much”? How long is “too long”? For someone only armed with a subnotebook computer, “too much” does not have the same meaning as for someone rocking a 12-core server with 256GB RAM and a few TB of SSD.

So this definition is relative… but in some cases, such as the one we are discussing, absolute – given the limitations of today’s technology.

For instance, the amount of storage LLNL required was several tens of PB in a single storage pool that could provide unprecedented I/O performance to the tune of 1TB/s. Both size and performance needed to be scalable. It also needed to be reliable and fit within a reasonable budget and not require extreme space, power and cooling. A tall order indeed.

This created some serious logistics problems regarding storage:

• No single disk array can hold that amount of data
• No single disk array can perform anywhere close to 1TB/s

Let’s put this in perspective: The storage systems that scale the biggest are typically scale-out clusters from the usual suspects of the storage world (we make one, for example). Even so, they max out at less PB than the deployment required.

The even bigger problem is that a single large scale-out system can’t really deliver more than a few tens of GB/s under optimal conditions – more than fast enough for most “normal” uses but utterly unacceptable for this case.

The only realistic solution to satisfy the requirements was massive parallelization, specifically using the NetApp E-Series for the back-end storage and the Lustre cluster filesystem.

A bit about the solution…

Almost a year ago NetApp purchased the Engenio storage line from LSI. That storage line is resold by several companies like IBM, Oracle, Quantum, Dell, SGI, Teradata and more. IBM also resells the ONTAP-based FAS systems and calls them “N-Series”.

That purchase has made NetApp the largest provider of OEM arrays on the planet by far. It was a good deal – very rapid ROI.

There was a lot of speculation as to why NetApp would bother with the purchase. After all, the ONTAP-based systems have a ton more functionality than pretty much any other array and are optimized for typical mostly-random workloads – DBs, VMs, email, plus megacaching, snaps, cloning, dedupe, compression, etc – all with RAID6-equivalent protection as standard.

The E-Series boxes on the other hand don’t do thin provisioning, dedupe, compression, megacaching… and their snaps are the less efficient copy-on-first-write instead of redirect-on-write. So, almost the anti-ONTAP

The first reason for the acquisition was that, on purely financial terms, it was a no-brainer deal even if one sells shoes for a living, let alone storage. Even if there were no other reasons, this one would be enough.

Another reason (and the one germane to this article) was that the E-Series has a tremendous sustained sequential performance density. For instance, the E5400 system can sustain about 4GB/s in 4U (real GB/s, not out of cache), all-in. That’s 4U total for 60 disks including the controllers. Expandable, of course. It’s no slouch for random I/O either, plus you can load it with SSDs, too…

Again, note – 60 drives per 4U shelf and that includes the RAID controllers, batteries etc. In addition, all drives are front-loading and stay active while servicing the shelf – as opposed to most (if not all) dense shelves in the market that need the entire (very heavy) shelf pulled out and/or several drives offlined in order to replace a single failed drive… (there’s some really cool engineering in the shelf to do this without thermal problems, performance loss or vibrations). All this allows standard racks and no fear of the racks tipping over while servicing the shelves (you know who you are!)

There are some vendors that purely specialize in sequential I/O and tipping racks – yet they have about 3-4x less performance density than the E5400, even though they sometimes have higher per-controller throughput. In a typical marketing exercise, some of our more usual competitors have boasted 2GB/s/RU for their controllers, meaning that in 4U the controllers (that take up 4U in that example) can do 8GB/s, but that requires all kinds of extra rack space to achieve (extra UPSes, several shelves, etc). Making their resulting actual throughput number well under 1GB/s/RU. Not to mention the cost (those systems are typically more expensive than a 5400). Which is important with projects of the scale we are talking about.

Most importantly, what we accomplished at the LLNL was no marketing exercise…

The benefits of truly high performance density

Clearly, if your requirements are big enough, you end up spending a lot less money and needing a lot less rack space, power and cooling by going with a highly performance-dense solution.

However, given the requirements of the LLNL, it’s clear that you can’t use just a single E5400 to satisfy the performance and capacity requirements of this use case. What you can do though is use a bunch of them in parallel… and use that massive performance density to achieve about 40GB/s per industry-standard rack with 600x high-capacity disks (1.8PB raw per rack).

For even higher performance per rack, the E5400 can use the faster SAS or SSD drives – 480 drives per rack (up to 432TB raw), providing 80GB/s reads/60GB/s writes.

Enter the cluster filesystem

So, now that we picked the performance-dense, reliable, cost-effective building block, how do we tie those building blocks together?

The answer: By using a cluster filesystem.

Loosely defined, a cluster filesystem is simply a filesystem that can be accessed simultaneously by the servers mounting it. In addition, it also typically means it can span storage systems and make them look as one big entity.

It’s not a new concept – and there are several examples, old and new: AFS, Coda, GPFS, and the more prevalent Stornext and Lustre are some.

The LLNL picked Lustre for this project. Lustre is a distributed filesystem that breaks apart I/O into multiple Object Storage Servers, each connected to storage (Object Storage Targets). Metadata is served by dedicated servers that are not part of the I/O stream and thus not a bottleneck. See below for a picture (courtesy of the Lustre manual) of how it is all connected:

High-speed connections are used liberally for lower latency and higher throughput.

A large file can reside on many storage servers, and as a result I/O can be spread out and parallelized.

Lustre clients see a single large namespace and run a proprietary protocol to access the cluster.

It sounds good in theory – and it delivered in practice: 1TB/s sustained performance. Not sure what the upper limit would be. But clearly it’s a highly scalable solution.

Putting it all together

NetApp has fully realized solutions for the “big data” applications out there – complete with the product and services needed to complete each engagement. The Lustre solution employed by the LLNL is just one of the options available. There is Hadoop, Full Motion uncompressed HD video, and more.

So – how fast do you need to go?

D

Technorati Tags: NetApp, performance, Lustre

Recently we have been focusing on benchmarking realistic configurations that people might actually put in their datacenters, instead of lab queens with unusable configs focused on achieving the highest result regardless of cost.

However, it seems the press doesn’t care about realistic configs (or to even understand the configs) but instead likes headline-grabbing big numbers.

So we decided to go for the best of both worlds – a headline-grabbing “big number” but also a config that would make more financial sense than the utterly crazy setups being submitted by competitors.

Without further ado, NetApp achieved over 1.5 million SPEC SFS2008 NFS operations per second with a 24-node cluster based on FAS6240 boxes running ONTAP 8 in Cluster Mode. Click here for the specific result. There are other results in the page showing different size clusters so you can get some idea of the scaling possible.

See below table for a high-level analysis (including the list pricing I could find for these specific performance-optimized configs for whatever that’s worth). The comparison is between NetApp and the nearest scale-out competitor result (one of many EMC’s recent acquisitions –  Isilon, the niche, dedicated NAS box – nothing else is close enough to bother including in the comparison).

BTW – the EMC price list is publicly available from here (and other places I’m sure): http://www.emc.com/collateral/emcwsca/master-price-list.pdf

From page 422:

S200-6.9TB & 200GB SSD, 48GB RAMS200-6.9TB & 200GB SSD, 48GB RAM, 2x10GE SFP+ & 2x1G $84,061. Times 140…

Before we dive into the comparison, an important note since it seems the competition doesn’t understand how to read SPEC SFS results:

Out of 1728 450GB disks (the number includes spares and OS drives, otherwise it was 1632 disks), the usable capacity was 574TB (73% of all raw space – even more if one considers a 450GB disk never actually provides 450 real GB in base2). The exported capacity was 288TB. This doesn’t mean we tried to short-stroke or that there is a performance benefit exporting a smaller filesystem – the way NetApp writes to disk, the size of the volume you export has nothing to do with performance. Since SPEC SFS doesn’t use all the available disk space, the person doing the setup thought like a real storage admin and didn’t give it all the available space. 

Lest we be accused of tuning this config or manually making sure client accesses were load-balanced and going to the optimal nodes, please understand this:  23 out of 24 client accesses were not going to the nodes owning the data and were instead happening over the cluster interconnect (which, for any scale-out architecture, is worst-case-scenario performance). Look under the “Uniform Access Rules Compliance” in the full disclosure details of the result in the SPEC website here. This means that, compared to the 2-node ONTAP 7-mode results, there is a degradation due to the cluster operating (intentionally) through non-optimal paths.

Notice the response time charts:

NetApp exhibits traditional storage system behavior – latency is very low initially and gradually gets higher the more the box is pushed, as one would expect. Isilon on the other hand starts out slow and gets faster as more metadata gets cached, until the controllers run out of steam (SPEC SFS is very heavy in NAS metadata ops, and should not be compared to heavy-duty block benchmarks like SPC-1).

This is one of the reasons an Isilon cluster is not really applicable for low-latency DB-type apps, or low-latency VMs. It is a great architecture designed to provide high sequential speeds for large files over NAS protocols, and is not a general-purpose storage system. Kudos to the Isilon guys for even getting the great SPEC result in the first place, given that this isn’t what the box is designed to do (the extreme Isilon configuration needed to run the benchmark is testament to that). The better application for Isilon would be capacity-optimized configs (which is what the system is designed for to begin with).

Some important points:

1. First and foremost, the cluster-mode ONTAP architecture now supports all protocols, it is the only unified scale-out architecture available. Any competitors playing in that space only have NAS or SAN offerings but not both in a single architecture.
2. We didn’t even test with the even faster 6280 box and extra cache (that one can take 8TB cache per node). The result is not the fastest a NetApp cluster can go With 6280s it would be a healthy percentage faster, but we had a bunch of the 6240s in the lab so it was easier to test them, plus they’re a more common and less expensive box, making for a more realistic result.
3. ONTAP in cluster-mode is a general-purpose storage OS, and can be used to run Exchange, SQL, Oracle, DB2, VMs, etc. etc. Most other scale-out architectures are simply not suitable for low-latency workloads like DBs and VMs and are instead geared towards high NAS throughput for large files (IBRIX, SONAS, Isilon to name a few – all great at what they do best).
4. ONTAP in cluster mode is, indeed, a single scale-out cluster and administered as such. It should not be compared to block boxes with NAS gateways in front of them like VNX, HDS + Bluearc, etc.
5. In ONTAP cluster mode, workloads and virtual interfaces can move around the cluster non-disruptively, regardless of protocol (FC, iSCSI, NFS and yes, even CIFS can move around non-disruptively assuming you have clients that can talk SMB 2.1 and above).
6. In ONTAP cluster mode, any data can be accessed from any node in the cluster – again, impossible with non-unified gateway solutions like VNX that have individual NAS servers in front of block storage, with zero awareness between the NAS heads aside from failover.
7. ONTAP cluster mode can allow certain cool things like upgrading storage controllers from one model to another completely non-disruptively, most other storage systems need some kind of outage to do this. All we do is add the new boxes to the existing cluster
8. ONTAP cluster mode supports all the traditional NetApp storage efficiency and protection features: RAID-DP, replication, deduplication, compression, snaps, clones, thin provisioning. Again, the goal is to provide a scale-out general-purpose storage system, not a niche box for only a specific market segment. It even supports virtualizing your existing storage.
9. There was a single namespace for the NFS data. Granted, not the same architecture as a single filesystem from some competitors.
10. Last but not least – no “special” NetApp boxes are needed to run Cluster Mode. In contrast to other vendors selling a completely separate scale-out architecture (different hardware and software and management), normal NetApp systems can enter a scale-out cluster as long as they have enough connectivity for the cluster network and can run ONTAP 8. This ensures investment protection for the customer plus it’s easier for NetApp since we don’t have umpteen hardware and software architectures to develop for and support
11. Since people have been asking: The SFS benchmark generates about 120MB per operation. The slower you go, the less space you will use on the disks, regardless of how many disks you have. This creates some imbalance in large configs (for example, only about 128TB of the 864TB available was used on Isilon).

Just remember – in order to do what ONTAP in Cluster Mode does, how many different architectures would other vendors be proposing?

• Scale-out SAN
• Scale-out NAS
• Replication appliances
• Dedupe appliances
• All kinds of management software

How many people would it take to keep it all running? And patched? And how many firmware inter-dependencies would there be?

And what if you didn’t need, say, scale-out SAN to begin with, but some time after buying traditional SAN realized you needed scale-out? Would your current storage vendor tell you you needed, in addition to your existing SAN platform, that other one that can do scale-out? That’s completely different than the one you bought? And that you can’t re-use any of your existing stuff as part of the scale-out box, regardless of how high-end your existing SAN is?

How would that make you feel?

Always plan for the future…

Comments welcome.

D

PS: Made some small edits in the RAID parts and also added the official EMC pricelist link.

Technorati Tags: Benchmark, EMC, Flash Cache, NAS, NetApp, NFS, RAID-DP, SPEC SFS, SSD, Isilon

Should be better now, I just wish the people doing the hacking would devote their considerable skills to helping out humanity…

Anyway, there are some impressive new scores at storageperformance.org, with the usual crazy configurations of thousands of drives etc.

Regarding price/performance:

When looking at $/IOP, make sure you are comparing list price (look at the full disclosure report, that has all the details for each config).

Otherwise, you could get the wrong $/IOP since some vendors have list prices, others show heavy discounting.

For example, a box that does $6.5/IOP after 50% discounting, would be $13/IOP using list prices.

Regarding RAID:

As I have mentioned in other posts, RAID plays a big role in both protection and performance.

All SPC-1 results are using RAID10, with the notable exception of NetApp (we use RAID-DP, mathematically analogous to RAID6 in protection).

Here’s a (very) rough way to convert a RAID10 result to RAID6, if the vendor you’re looking for doesn’t have a RAID6 result:

1. SPC-1 is about 60% writes.
2. Take any RAID10 result, let’s say 200,000 IOPS.
3. 60% of that is 120,000, that’s the write ops. 40% is the reads, or 80,000 read ops.
4. If using RAID6, you’d be looking at roughly a 4x slowdown for the writes: 120,000/4 = 30,000
5. Add that to the 40% of the reads and you get the final result:
6. 80,000 reads + 30,000 writes = 110,000 RAID6-corrected SPC-1 IOPS. Which is almost half the RAID10 result…

Just make sure you’re comparing apples to apples, that’s all. I know we all suffer from ADD in this age of information overload, but do spend some time going through the full disclosure, since there’s always interesting stuff in there…

D

I’m writing this post because more and more I see some vendors not using scientific methods to size their solution, instead aiming to reach a price point, hoping the technology will work to achieve the requisite performance (and if it doesn’t, it’s sold anyway, either they can give some free gear to make the problem go away, or the customer can always buy more, right?)

Back in the “good old days”, with legacy arrays one could (and still can) get fairly deterministic performance by knowing the workload required and, given a RAID type, know roughly how many disks would be needed to maintain the required performance in a sustained fashion, as long as the controller and buses were not overloaded.

With modern systems, there is now a plethora of options that can be used to get more performance out of the array, or, alternatively, get the same average performance as before, using less hardware (hopefully for less money).

If anything, advanced technologies have made array sizing more complex than before.

For instance, Megacaches can be used to dramatically change the I/O reaching the back-end disks of the array. NetApp FAS systems can have up to 16TB of deduplication-aware, ultra-granular (4K) and intelligent read cache. Truly a gigantic size, bigger than the vast majority of storage users will ever need (and bigger than many customers’ entire storage systems). One could argue that with such an enormous amount of cache, one could dispense with most disk drives and instead save money by using SATA (indeed, several customers are doing exactly that). Other vendors are following NetApp’s lead and starting to implement similar technologies — simply because it makes a lot of sense.

However…

It is crucial that, when relying on caching, extra care is taken to size the solution properly, if a reduction in the number and speed of the back-end disks is desired.

You see, caches only work well if they can cache the majority of what’s called the active working set.

Simply put, the working set is not all your data, but the subset of the data you’re “touching” constantly over a period of time. For a customer that has, say, a 20TB Database, the true working set may only be something as small as 5% — enabling most of the active data to fit in 1TB of cache. So, during daily use, a 1TB cache could satisfy most of the I/O requirements of the DB. The back-end disks could comfortably be just enough SATA to fit the DB.

But what about the times when I/O is not what’s normally expected? Say, during a re-indexing, or a big DB export, or maybe month-end batch processing. Such operations could vastly change the working set and temporarily raise it from 5% to something far larger — at which point, a 1TB cache and a handful of back-end SATA may not be enough.

Which is why, when sizing, multiple measurements need to be taken, and not just average or even worst-case.

Let’s use a database as an example again (simply because the I/O can change so dramatically with DBs).You could easily have the following I/O types:

1. Normal use – 20,000 IOPS, all random, 8K I/O size, 80% reads
2. DB exports — high MB/s, mostly sequential write,large I/O size, relatively few IOPS
3. Sequential read after random write — maybe data is added to the DB randomly, then a big sequential read (or maybe many parallel ones) are launched.

You see, the I/O profile can change dramatically. If you only size for case #1, you may not have enough back-end disk to sustain the DB exports or the parallel sequential table scans. If you size for case 2, you may think you don’t need much cache since the I/O is mostly sequential (and most caches are bypassed for sequential I/O). But that would be totally wrong during normal operation.

If your storage vendor has told you they sized for what generates the most I/O, then the question is, what kind of I/O was it?

The other new trendy technology (and the most likely to be under-sized) is Autotiering.

Autotiering, simply put, allows moving chunks of data around the array depending on their “heat index”. Chunks that are very active may end up on SSD, whereas chunks that are dormant could safely stay on SATA.

Different arrays do different kinds of Autotiering, mostly based on various underlying architectural characteristics and limitations. For example, on an EMC Symmetrix the chunk size is about 7.5MB. On an HDS VSP, the chunk is about 40MB. On an IBM DS8000, SVC or EMC Clariion/VNX, it’s 1GB.

With Autotiering, just like with caching, the smaller the chunk size, the more efficient the end result will ultimately be. For instance, a 7.5MB chunk could need as little as 3-5%% of ultra-fast disk as a tier, whereas a 1GB chunk may need as much as 10-15%, due to the larger size chunk containing not very active data mixed together with the active data.

Since most arrays write data with a geometric locality of reference (in contrast, NetApp uses geometric and temporal), with large-chunk autotiering you end up with pieces of data that are “hot” that always occupy the same chunk as neighboring “cool” pieces of data. This explains why the smaller the chunk, the better off you are.

So, with a large chunk, this can happen:

The array will try to cache as much as it can, then migrate chunks if they are consistently busy or not. But the whole chunk has to move, not just the active bits within the chunk… which may be just fine, as long as you have enough of everything.

So what can you do to ensure correct sizing?

There are a few things you can do to make sure you get accurate sizing with modern technologies.

1. Provide performance statistics to vendors — the more detailed the better. If we don’t know what’s going on, it’s hard to provide an engineered solution.
2. Provide performance expectations — i.e. “I want Oracle queries to finish in 1/4th the time compared to what I have now” — and tie those expectations to business benefits (makes it easier to justify).
3. Ask vendors to show you their sizing tools and explain the math behind the sizing — there is no magic!
4. Ask vendors if they are sizing for all the workloads you have at the moment (not just different apps but different workloads within each app) — and how.
5. Ask them to show you what your working set is and how much of it will fit in the cache.
6. Ask them to show you how your data would be laid out in an Autotiered environment and what bits of it would end up on what tier. How is that being calculated? Is the geometry of the layout taken into consideration?
7. Do you have enough capacity for each tier? On Autotiering architectures with large chunks, do you have 10-15% of total storage being SSD?
8. Have the controller RAM and CPU overheads due to caching and autotiering been taken into account? Such technologies do need extra CPU and RAM to work. Ask to see the overhead (the smaller the Autotiering chunk size, the more metadata overhead, for example). Nothing is free.
9. Beware of sizings done verbally or on cocktail napkins, calculators, or even spreadsheets – I’ve yet to see a spreadsheet model storage performance accurately.
10. Beware of sizings of the type “a 15K disk can do 180 IOPS” — it’s a lot more complicated than that!
11. Understand the difference between sequential, random, reads, writes and I/O size for each proposed architecture — the differences in how I/O is done depending on the platform are staggering and can result in vastly different disk requirements — making apples-to-apples comparisons challenging.
12. Understand the extra I/O and capacity impact of certain CDP/Replication devices — it can be as much as 3x, and needs to be factored in.
13. What RAID type is each vendor using? That can have a gigantic performance impact on write-intensive workloads (in addition to the reliability aspect).
14. If you are getting unbelievably low pricing — ask for a contract ensuring upgrade pricing will be along the same lines. “The first hit is free” is true in more than one line of business.
15. And, last but by no means least — ask how busy the proposed solution will be given the expected workload! It surprises me that people will try to sell a box that can do the workload but will be 90% busy doing so. Are you OK with that kind of headroom? Remember – disk arrays are just computers running specialized software and hardware, and as such their CPU can run out of steam just like anything else.

If this all seems hard — it’s because it is. But see it as due diligence — you owe it to your company, plus you probably don’t want to be saddled with an improperly-sized box for the next 3-5 years, just because the offer was too good to refuse…

D

Technorati Tags: compellent, FAST, FAST Cache, FASTv2, Flash, Flash Cache, NetApp, performance, ssd, Autotiering

Never attribute to malice that which is adequately explained by stupidity.

A variation of that is:

Never attribute to malice that which is adequately explained by stupidity, but don’t rule out malice.

You see, EMC sponsored a study comparing their systems to ones from the company they look up to and try to emulate. The report deals with ease-of-use (and I’ll be the first to admit the current iteration of EMC boxes is far easier to use than in the past and the GUI has some cool stuff in it). I was intrigued, but after reading the official-looking report posted by Chuck Hollis, I wondered who in their right mind will lend it credence, and ignored it since I have a real day job solving actual customer problems and can’t possibly respond to every piece of FUD I see (and I see a lot).

Today I’m sitting in a rather boring meeting so I thought I’d spend a few minutes to show how misguided the document is.

In essence, the document tackles the age-old dilemma of which race car to get by comparing how easy it is to change the oil, and completely ignores the “winning the race with said car” part. My question would be: “which car allows you to win the race more easily and with the least headaches, least cost and least effort?”

And if you think winning a “race” is just about performance, think again.

It is also interesting how the important aspects of efficiency, reliability and performance are not tackled, but I guess this is a “usability” report…

Strange that a company named “Strategic Focus” reduces itself to comparing arrays by measuring the number of mouse clicks. Not sure how this is strategic for customers. They were commissioned by EMC, so maybe EMC considers this strategic.

I’ll show how wrong the document is by pointing at just some of the more glaring issues, but I’ll start by saying a large multinational company has many PB of NetApp boxes around the globe and 3 relaxed guys to manage it all. How’s that for a real example?

1. Page 2, section 4, “Methodology”: EMC’s own engineers set up the VNX properly. No mention of who did the NetApp testing, what their qualifications are, and so on. So, first question: “Do these people even know what they’re doing? Have they really used a NetApp system before?”
2. Page 10, Table A, showing the configurations. A NetApp FAS3070 was used, running the latest code at this moment (8.01). Thanks EMC for the unintended compliment – you see, that system is 2 generations old (the current one is 3270 and the previous one is 3170) yet it can still run the very latest 64-bit ONTAP code just fine. What about the EMC CX3? Can it run FLARE31? Or is that a forklift upgrade? Something to be said for investment protection
3. Page 3 table 5-1, #1. Storage pools on all modern arrays would typically be created upfront, so the wording is very misleading. In order to create a new LUN one does NOT NEED to create a pool. Same goes for all vendors.
4. Same table and section (also mentioned in section 7): Figuring out the space available is as simple as going to the aggregate page, where the space is clearly shown for the aggregates. So, unsure what is meant here.
5. Regarding LUN creation… Let me ask you a question: After you create a LUN on any array, what do you need to do next? You see, the goal is to attach the LUN to a host, do alignment, partition creation, multipathing and create a filesystem and write stuff to it. You know, use it. NetApp largely automates end-to-end creation of host filesystems and, indeed, does not need an administrator to create a LUN on the array at all. Clearly the person doing the testing is either not aware of this or decided to omit this fact.
6. Page 4, item 4 (thin provisioning). Asinine statement – plus, any NetApp LUN can be made thick or thin with a single click, whereas a VNX needs to do a migration. Indeed, NetApp does not complicate things whether thin or thick is required, does not differentiate between thin and thick when writing, and therefore does not incur a performance penalty, whereas EMC does (according to EMC documentation).
7. Page 4, item 5 (Creation of virtual CIFS servers). The Multistore feature is free of charge on all new systems and allows one to create fully segregated, secure multitenancy virtual CIFS, NFS and iSCSI NetApp “partitions” – far beyond the capabilities of EMC. Again, misleading.
8. Page 4, item 6 (growing storage elements). No measurable difference? Kindly show all the steps to grow a LUN until the new space is visible from the host side. End-to-end is important to real users since they want to use the storage. Or maybe not, for the authors of this document.
9. Page 5, Item 1. We are really talking here about EMC snapshots? Seriously? Versus NetApp? To earn the right to do so assumes your snapshots are a usable and decent feature and that you can take a good number of them without the box crumbling to pieces. Ask any vendor about a production array with the most snaps and ask to talk to the customer using it. Then compare the number of snaps to a typical NetApp customer’s. Don’t be surprised if one number is a few hundred times less than the other.
10. Page 5, item 3 (storage tiering): part of a longer conversation but this assumes all arrays need to do tiering. If my solution is optimized to the level that it doesn’t need to do this but yours is not optimized so it needs tiering, why on earth am I being penalized for doing storage more efficiently than you? (AKA the “not invented here” syndrome).
11. Page 6 item 1 (VMware awareness): NetApp puts all the awareness inside vCenter and, indeed, datastore creation (including volume/LUN/NAS creation and resizing), VM cloning etc. all from within vCenter itself. Ask for a demo and prepare to be amazed.
12. Page 6, item 2 – (dedupe/compress individual VMs): This one had my blood boiling. You see, EMC cannot even dedupe individual VMs, (impossible, given the fact that current DART code only does dedupe at the file and not block level and no two active VMs will ever be exactly the same), can’t dedupe at all for block storage (maybe in the future but not today), and in general doesn’t recommend compression for VMs! Ask to see the best practices guide that states all this is supported and recommended for active production VMs, and to talk to a customer doing it at scale (not 10 VMs). A feature you can theoretically turn on but that will never work is not quite useful, you see…
13. Page 8, entire table: Too much to comment on, suffice it to say that NetApp systems come with tools not mentioned in this report that go so far beyond what Unisphere does that it’s not even funny (at no additional cost). Used by customers that have thousands of NetApp systems. That’s how much those tools scale. EMC would need vast portions of the Ionix suite to do anything remotely similar (at $$$). Of course, mentioning that would kinda derail this document… and the piece about support and upgrades is utterly wrong, but I like to keep the surprise for when I do the demos and not share cool IP ideas here
14. Page 11, Table B1: In the end, the funniest one of all! If you add up the total number of mouse clicks, NetApp needed 92 vs EMC’s 111. Since the whole point of this usability report is to show overall ease of use by measuring the total number of clicks to do stuff, it’s interesting that they didn’t do a simple total to show who won in the end…

I could keep going but I need to pay attention to my meeting now since it suddenly became interesting.

Ultimately, when it comes to ease of use, it’s simple to just do a demo and have the customer decide for themselves which approach they like best. Documents such as this one mean less than nothing for actual end users.

I should have another similar list showing clicks and TIME needed to do certain other things. For instance, using RecoverPoint (or any other method), kindly show the number of clicks and time (and disk space) for creating 30 writable clones of a 10TB SQL DB and mounting them on 30 different DB servers simultaneously. Maintaining unique instance names etc. Kinda goes a bit beyond LUN creation, doesn’t it?

All this BTW doesn’t mean any vendor should rest on their laurels and stop working on improving usability. It’s a never-ending quest. Just stop it with the FUD, please…

Finishing with something funny: Check this video for a good demonstration of something needing few clicks yet not being that easy to do.

Comments welcome.

D

Technorati Tags: EMC, NetApp, performance, snapshot, NAS

I went for an Intel 320 model, since it includes extra capacitors for flushing the cache in the event of power failure, and has RAID-4 onboard for protection beyond sparing (there are other, faster SSDs but I need the reliability and can’t afford large-sized SLC).

I used the trusty postmark (here’s a link to the OS X executable) to generate a highly random workload with varying file sizes, using these settings:

set buffering false
set size 500 100000
set read 4096
set write 4096
set number 10000
set transactions 20000
run

All testing was done on OS X 10.6.7.

Here’s the result with the original 7200 RPM HDD:

Time:
198 seconds total
186 seconds of transactions (107 per second)

Files:
20163 created (101 per second)
Creation alone: 10000 files (1111 per second)
Mixed with transactions: 10163 files (54 per second)
10053 read (54 per second)
9945 appended (53 per second)
20163 deleted (101 per second)
Deletion alone: 10326 files (3442 per second)
Mixed with transactions: 9837 files (52 per second)

Data:
557.87 megabytes read (2.82 megabytes per second)
1165.62 megabytes written (5.89 megabytes per second)

I then replaced the internal drive with SSD, popped the old internal drive into an external caddy, plugged it into the Mac, reinstalled OS X and simply told it to move the user and app stuff from the old drive to the new (Apple makes those things so easy – on a PC you’d probably need something like an imaging program but that wouldn’t take care of very different hardware). I spent a ton of time testing to make sure it was all OK, in disbelief it was that easy. Kudos, Apple.

Here are the results with SSD (2/3rds full FWIW):

Time:
19 seconds total
13 seconds of transactions (1538 per second)

Files:
20163 created (1061 per second)
Creation alone: 10000 files (2500 per second)
Mixed with transactions: 10163 files (781 per second)
10053 read (773 per second)
9945 appended (765 per second)
20163 deleted (1061 per second)
Deletion alone: 10326 files (5163 per second)
Mixed with transactions: 9837 files (756 per second)

Data:
557.87 megabytes read (29.36 megabytes per second)
1165.62 megabytes written (61.35 megabytes per second)

A fair bit of improvement… The perceived difference is amazing. For some things I’ve caught it doing over 200MB/s sustained writes.

I also disabled the sudden motion sensor since there’s no point stopping I/O to a SSD if one shakes the laptop. From the command line:

sudo pmset -a sms 0 (this disables it)
sudo pmset –g (to verify it was done)

And since I don’t need hotfile adaptive clustering on a SSD, I decided to disable access time updates (noatime in UNIX parlance).

You need to put the script from here: http://dl.dropbox.com/u/5875413/Tools/com.my.noatime.plist

into /Library/LaunchDaemons

And make sure it has the right permissions:

sudo chown root:wheel com.my.noatime.plist

Then reboot, type mount from the command line, and see if the root filesystem shows noatime as one of the mount arguments.

For example mine shows

/dev/disk0s2 on / (hfs, local, journaled, noatime)

I then re-ran postmark, here are the results with noatime:

Time:
16 seconds total
11 seconds of transactions (1818 per second)

Files:
20163 created (1260 per second)
Creation alone: 10000 files (2500 per second)
Mixed with transactions: 10163 files (923 per second)
10053 read (913 per second)
9945 appended (904 per second)
20163 deleted (1260 per second)
Deletion alone: 10326 files (10326 per second)
Mixed with transactions: 9837 files (894 per second)

Data:
557.87 megabytes read (34.87 megabytes per second)
1165.62 megabytes written (72.85 megabytes per second)

Even better.

Now here comes the part that I hoped would work better than it did:

OS X doesn’t support the TRIM command for SSDs yet (unless you have a really new Mac with an Apple SSD). Fortunately, some enterprising users found out that it is possible to turn TRIM on OS X. There are various ways to do it but someone already automated the process. Be sure to do a backup first (both system backup and through the TRIM enabler application).

The process does work. However, it seems it tries to run TRIM too aggressively, messing up with the random access optimizations some drives have.

Benchmark after TRIM enabled:

Time:
39 seconds total
31 seconds of transactions (645 per second)

Files:
20163 created (517 per second)
Creation alone: 10000 files (3333 per second)
Mixed with transactions: 10163 files (327 per second)
10053 read (324 per second)
9945 appended (320 per second)
20163 deleted (517 per second)
Deletion alone: 10326 files (2065 per second)
Mixed with transactions: 9837 files (317 per second)

Data:
557.87 megabytes read (14.30 megabytes per second)
1165.62 megabytes written (29.89 megabytes per second)

This kind of performance loss is unacceptable to me, so I restored the kext file through the TRIM app, rebooted and re-ran the benchmark and all was fine again.

My recommendations:

1. Always test before and after the tweaks – my results may only apply to Intel drives. Please post your results with other drives
2. Always do backups before serious tweaks
3. If TRIM seems to slow down random I/O on your Mac SSD, don’t keep it running, maybe enable it once a month, go to disk utility, and ask it to erase the free space. This will ensure the drive stays in good shape without adversely affecting normal random I/O.

D

Since SPEC doesn’t require prices to be listed, I did my own analysis.

The NetApp numbers are simply 4x the existing 6240 result, which is what EMC did with their submission, they used 4x separate VNX systems and aggregated the result.

I used this clarifying analogy over at Nigel’s blog to explain why this makes sense before anyone yells “but this is not published”:

A storage system typically has some kind of bottleneck – cluster interconnect, number of drives, bandwidth to the controller, etc.

When you’re testing a single system, you’re ultimately hitting one of those bottlenecks.

If you’re testing multiple systems independent of each other, they do not share the bottlenecks (since they’re separate), and your performance will scale linearly as you add systems.

For example, if 1 truck can hold 10 tons of stuff, 4 like trucks will hold 40 tons of stuff, 10 trucks 100 tons, etc. There’s no limit.

Once you inject a limiting factor (“the trucks all have to fit on a bridge and the bridge can take this much load and it’s this big”) then you will have a limitation on how many trucks you can load and put on that bridge.

EMC tested 4 separate “trucks”. In that same way, I can add up the result of 4 separate NetApp “trucks”. Here are the results:

Who can spot the better deal?

I added the latency in the chart, thanks to my buddy Mark Twomey for pointing it out.

You see, people needing enterprise NAS with that kind of performance usually need speed, plenty of space and high reliability. Not just one of the three. BTW, here’s a paper on relative RAID reliability.

NetApp provides all three, in spades, plus great value for money, a truly simple, flexible unified system, and efficiency.

Most customers want to see how a real configuration performs. I refer customers to our SPEC and SPC results constantly since quite frequently their desired configuration is very similar.

Which makes benchmarking realistic configurations actually useful – imagine that.

Maybe EMC needs to submit results with VNX the way they sell it to people, for example:

• A mix of SSD cache, SSD, high-speed SAS and high-capacity SAS
• Autotiering
• RAID6
• A typical amount of space for a configuration that size

Then submit results.

Keep your existing result of course, but also show the people how what you actually sell them really performs.

I still don’t understand why this is such a hard concept.

D

Allow me to elaborate.

EMC posted a new SPEC SFS result as part of a marketing stunt (which is working, look at what I’m doing – I’m talking about them, if only to clear the air).

In simple terms, EMC got almost 500,000 SPEC SFS NFS IOPS (not to be confused with, say, block-based SPC-1 IOPS) with the following configuration:

1. Four (4) totally separate VNX arrays, each loaded with SSD storage, utterly unaware of each other (8 total controllers since each box has 2)
2. Five (5) Celerra VG8 NAS heads/gateways (1 spare), one on top of each VNX box
3. 2 Control Stations
4. 8 exported filesystems (2 per VG8 head/VNX system)
5. Multiple pools of storage (at least 1 per VG8) – not shared among the various boxes, no data mobility between boxes
6. Only 60TB NAS space with RAID5 (or 15TB per box)

Now, this post is not about whether this configuration is unrealistic and expensive (almost nobody would pay $6m for merely 60TB of NAS, not today). I get it that EMC is trying to publish the best possible number by loading a bunch of separate arrays with SSD. It’s OK as long as everyone understands the details.

My beef has to do with how it’s marketed.

EMC is very vague about the configuration, unless you look at the actual SPEC website. In the marketing materials they just mention VNX, as in “The EMC VNX performed at 497,623 SPECsfs2008_nfs.v3 operations per second”. Kinda like saying it’s OK to take 3 5-year olds and a 6-year old to a bar because their age adds up to 21.

No – the far more accurate statement is “four separate VNXs working independently and utterly unaware of each other did 124,405 SPEC fs2008_nfs.v3 operations per second each“.

All EMC did was add up the result of 4 boxes.

Heck, that’s easy to do!

NetApp already has a result for the 6240 (just 2 controllers doing a respectable 190,675 SPEC NFS ops taking care of NAS and RAID all at once since they’re actually unified, no cornucopia of boxes there) without using Solid State Drives (common SAS drives plus a large cache were used instead – a standard, realistic config we sell every day, and not a “lab queen”).

If all we’re doing is adding up the result of different boxes, simply multiply this by 4 (plus we do have Cluster-Mode for NAS so it would count as a single clustered system with failover etc. among the nodes) and end up with the following result:

1. 762,700 SPEC SFS NFS operations
2. 8 exported filesystems
3. 343TB usable with RAID-DP (thousands of times more resilient than RAID5)

So, which one do you think is the better deal? More speed, 343TB and better protection, or less speed, 60TB and far less protection?

Customers curious about other systems can do the same multiplication trick for other configs, the sky is the limit!

The other, more serious part, and what prompted me to title the post the way I did, is that EMC’s benchmarking made pretty clear the fact that the VNX is the bottleneck, only able to really support a single VG8 head at top speed, necessitating the need for 4 separate VNX systems to accomplish the final result. So, the fact that a VNX can have up to 8 Celerra heads on top of it means nothing since the back-end is your limiting factor. You might as well stick to a dual-head VG8 config (1 active 1 passive) since that’s all it can comfortably drive (otherwise why benchmark it that way?)

But with only 1 active NAS head you’d be limited to just 256TB max NAS capacity, since that’s how much total space a Celerra head can address as of the time of this writing. Which is probably enough for most people.

I wonder if the NAS heads that can be bought as a package with VNX are slower than VG8 heads, and by how much. You see, most people buying the VNX will be getting the NAS heads that can be packaged with it since it’s cheaper that way. How fast does that go? I’m sure customers would like to know, since that’s what they will typically buy.

I also wonder how fast it would be with RAID6.

Here’s a novel idea: benchmark what customers will actually buy!

So apples-to-apples comparisons can become easier instead of something like this:

For the curious: on the left you see an “Autumn Glory” Malus Floribunda (miniature apple). Photo courtesy of John Fullbright.

D

Technorati Tags: benchmark, EMC, flash cache, NetApp, NFS, performance, RAID-DP, SPEC SFS, RAID5

I do have some advice for EMC (and all other vendors that have already posted results):

1. Do show results for your various supported RAID types, not just RAID10 – after all, if most of your customers don’t just deploy RAID10, it makes sense to show RAID5 and RAID6, especially if you want to compare results with NetApp RAID-DP (that’s the protection equivalent of RAID6). This will increase your credibility. The argument that you only show RAID10 since that’s the best performing doesn’t hold water – everyone knows the other RAID types will have different performance levels, providing results for everything will at least enable customers to get an idea of how much of a performance hit they’ll have with the different RAID types with a write-intensive workload.
2. Do show long-running benchmarks with auto-tiering enabled. After all, if you are claiming your auto-tiering implementation doesn’t hurt and can even improve results, this is your chance to show it.
3. Enable features like snapshots.
4. Use your large cache if you have one, especially if you keep advertising that it accelerates writes. It will just solidify your claims.

Welcome to the club!

D

Technorati Tags: benchmark, EMC, FAST, FAST Cache, FASTv2, Flash Cache, NetApp, RAID, RAID-6, RAID-DP, RAID10, RAID6, SPC

To the uninitiated, a stack is what you can get when a vendor is able to offer multiple products under a single umbrella. For instance, being able to get servers, an OS, a DB, an email system, storage and network switches from a single manufacturer (not a VAR) is an example of a single-sourced stack.

The proponents of stacks maintain that with stacks, customers potentially get simpler service and better integration – a single support number to call, “one throat to choke”, no finger-pointing between vendors. And that’s partially true. A stack potentially provides simpler access to support. On the “better integration” part – read on.

My main problem with stacks is that nobody really offers a complete stack, and those that are more complete than others, don’t necessarily offer best-of-breed products (not even “good enough”), nor do they offer particularly great integration between the products within the stack.

Personal anecdote: a few years ago I had the (mis)fortune of being the primary backup and recovery architect for one of the largest airlines in the world. Said airline had a very close relationship with a certain famous vendor. Said vendor only flew with that airline, always bought business class seats, the airline gave the vendor discounts, the vendor gave the airline discounts, and in general there was a lot of mutual back-scratching going on. So much so that the airline would give that vendor business before looking at anyone else, and only considered alternative vendors if the primary vendor didn’t have anything that even smelled like what the airline was looking for.

All of which resulted in the airline getting a backup system that was designed for small businesses since that’s all that vendor had to offer (and still does).

The problem is, that backup product simply could not scale to what I needed it to. I ended up having to stop file-level logging and could only restore entire directories since the backup database couldn’t handle the load, despite me running multiple instances of the tool for multiple environments. Some of those directories were pretty large, so you can imagine the hilarity that ensued when trying to restore stuff…

The vendor’s crack development team came over from overseas and spent days with me trying to figure out what they needed to change about the product to make it work in my environment (I believe it was the single largest installation they had).

Problem is, they couldn’t deliver soon enough, so, after much pain, the airline moved to a proper enterprise backup system from another vendor, which fixed most problems, given the technology I had to work with at the time.

Had the right decision been made up front, none of that pain would have been experienced. The world would have been one IT anecdote short, but that’s a small price to pay for a working environment. And this is but just one way that single vendor stacks can fail.

How does one decide on a stack?

Let’s examine a high-level view of a few stack offerings. By no means an all-inclusive list.

Microsoft: They offer an OS (catering from servers to phones), a virtualization engine, a DB, a mail system, a backup tool and the most popular office apps in the world, among many other things. Few will argue that all the bits are best-of-breed, despite being hugely popular. Microsoft doesn’t like playing in the hardware space, so they’re a pure software stack. Oh, there’s the XBox, too.

EMC: Various kinds of storage platforms (7-10 depending on how you count), all but one (Symmetrix) coming from acquisition. A virtualization engine (80% owner of VMware – even though it’s run as a totally separate entity). DB, many kinds of backup, document management, security and all other kinds of software. Some bits are very strong, others not so much.

Oracle: They offer an OS, a virtualization engine, a DB, middleware, servers and storage. An office suite. No networking. Oracle is a good example of an incomplete software/hardware stack. Aside from the ultra-strong DB and good OS, few will say their products are all best-of-breed.

Dell: They offer servers desktops, laptops, phones, various flavors of storage, switches. Dell is an example of a pure hardware stack. Not many software aspirations here. Few will claim any of their products are best-of-breed.

HP: They offer servers desktops, laptops, phones, even more flavors of storage, a UNIX OS with its own type of virtualization (can’t run x86), switches, backup software, a big services arm, printers, calculators… All in all, great servers, calculators and printers, not so sure about the rest. Fairly complete stack.

IBM: Servers, 2 strong DBs, at least 3 different OSes, CPUs, many kinds of storage,  email system, middleware, backup software, immense services arm. No x86 virtualization (they do offer virtualization for their other platforms). Very complete stack, albeit without networking.

Cisco: All kinds of networking (including telephony), servers. Limited stack if networking is not your bag, but what it offers can be pretty good.

Apple: Desktops, laptops, phones, tablets, networking gear, software. Great example of a consumer-oriented hardware and software stack. They used to offer storage and servers but they exited that business.

Notice anything common about the various single-vendor stacks? Did you find a stack that can truly satisfy all your IT needs without giving anything up?

The fact of the matter is that none of the above companies, as formidable as they are, offers a complete stack – software and hardware. You can get some of the way there, but it’s next to impossible to single-source everything without shooting yourself in the foot. At a minimum, you’re probably looking at some kind of Microsoft stack + server/storage stack + networking stack – mixing a minimum of 3 different vendors to get what you need without sacrificing much (the above example assumes you either don’t want to virtualize or are OK with Hyper-V).

Most companies have something like this: Microsoft stack + virtualization + DB + server + storage + networking – 6 total stacks.

So why do people keep pushing single-vendor stacks?

Only a few valid reasons (aside from it being fashionable to talk about). One of them is control – the more stuff you have from a company, the tighter their hold on you. The other is that it at least limits the support points you have to deal with, and can potentially get you better pricing (theoretically). For instance, Dell has “given away” many an Equallogic box. Guess what – the cost of that box was blended into everything else you purchased, it’s all a shell game. But if someone does buy a lot of gear from a single vendor, there are indeed ways to get better deals. You just won’t necessarily get best-of-breed or even good enough gear.

What about integration?

One would think that buying as much as possible from a single vendor gets you better integration between the bits. Not necessarily. For instance, most large vendors acquire various technologies and/or have OEM deals – if one looks just at storage as an example, Dell has their own storage (Equallogic and Compellent – two different acquisitions) plus an OEM deal with EMC. There’s not much synergy between the various technologies.

HP has their own storage (EVA, Lefthand, Ibrix, Polyserve, 3Par – four different acquisitions) and two OEM deals with Dot Hill for the MSA boxes and HDS for the high-end XP systems. That’s a lot of storage tin to keep track of (all of which comes from 7 different places and 7 totally different codebases), and any HP management software needs to be able to work with all of those boxes (and doesn’t).

IBM has their own storage (XIV, DS6000, DS8000, SONAS, SVC – I believe three homegrown and two acquisitions) and two different OEM deals (NetApp for N Series and LSI Logic for DS5000 and below). The integration between those products and the rest of the IBM landscape should be examined on a case-by-case basis.

EMC’s challenge is that they have acquired too much stuff, making it difficult to provide proper integration for everything. Supporting and developing for that plethora of systems is not easy and teams end up getting fragmented and inconsistent. Far too many codebases to keep track of. This dilutes the R&D dollars available and prolongs development cycles.

Aren’t those newfangled special-purpose multi-vendor stacks better?

There’s another breed of stack, the special-purpose one where a third party combines gear from different vendors, assembles it and sells it as a supported and pre-packaged solution for a specific application. Such stacks are actually not new – they have been sold for military, industrial and healthcare applications for the longest time. Recently, Netapp and EMC have been promoting different versions of what a “virtualization stack” should be (as usual, with very different approaches, check out FlexPod and Vblock).

The idea behind the “virtualization stack” is that you sell the customer a rack that has inside it network gear, servers, storage, management and virtualization software. Then, all the customer has to do is load up the gear with VMs and off they go.

With such a stack, you don’t limit the customer by making them buy their gear all from one vendor, but instead you limit them by pre-selecting vendors that are “best of breed”. Not everyone will be OK with the choice of gear, of course.

Then there’s the issue of flexibility – some of the special-purpose stacks literally are like black boxes – you are not supposed to modify them or you lose support. To the point where you’re not allowed to add RAM to servers or storage to arrays, both limitations that annoy most customers, but are viewed as a positive by some.

Is it a product or a “kit”?

Back to the virtualization-specific stacks: This is the main argument, do you buy a ready-made “product” or a “kit” some third party assembles after following a detailed design guide. As of this writing (there have been multiple changes to how this is marketed), Vblock is built by a company known as VCE – efectively a third party that puts together a custom stack made of different kinds of EMC storage, Cisco switches and servers, VMware, and a management tool called UIM. It is not built by EMC, VMware or Cisco. VCE then resells the assembled system to other VARs or directly to customers.

NetApp’s FlexPod is built by VARs. The difference is that more than one VAR can build FlexPods (as long as they meet some specific criteria) and don’t need to involve a middleman (also translating to more profits for VARs). All VARs building FlexPods need to follow specific guidelines to build the product (jointly designed by VMware, Cisco and NetApp), use components and firmware tested and certified to work together, and add best-of-breed management software to manage the stack.

The FlexPod emphasis is on sizing and performance flexibility (from tiny to gigantic), Secure Multi Tenancy (SMT – a unique differentiator), space efficiency, application integration, extreme resiliency and network/workload isolation – all highly important features in virtualized environments. In addition, it supports non-virtualized workloads.

Ultimately, in both cases the customer ends up with a pre-built and pre-tested product.

What about support?

This has been both the selling point and the drawback of such multi-vendor stacks. In my opinion, it has been the biggest selling point for Vblock, since a customer calls VCE for support. VCE has support staff that is trained on Cisco, VMware and EMC and can handle many support cases via a single support number – obviously a nice feature.

Where this breaks down a bit: VCE has to engage VMware, EMC and Cisco for anything that’s serious. Furthermore, Vblock support doesn’t support the entire stack but stops at the hypervisor.

For instance, if a customer hits an Enginuity (Symmetrix OS) bug, then the EMC Symm team will have to be engaged, and possibly write a patch for the customer and communicate with the customer. VCE support simply cannot fix such issues, and is best viewed as first-level support. Same goes for Cisco or VMware bugs, and in general deeper support issues that the VCE support staff simply isn’t trained enough to resolve. In addition, Vblocks can be based on several different kinds of EMC storage, that itself requires different teams to support it.

Finally – ask VCE if they are legally responsible for maintaining the support SLAs. For instance, who is responsible if there is a serious problem with the array and the vendor takes 2 days to respond instead of 30 minutes?

FlexPod utilizes a cooperative support model between NetApp, Cisco and VMware, and cases are dealt with by experts from all three companies working in concert. The first company to be called owns the case.

When the going gets tough, both approaches work similarly. For easy cases that can be resolved by the actual VCE support personnel, Vblock probably has an edge.

Who needs the virtualization stack?

I see several kinds of customers that have a need for such a stack (combinations are possible):

1. The technically/time constrained. For them, it might be easier to get a somewhat pre-integrated solution. That way they can get started more quickly.
2. The customers needing to hide behind contracts for legal/CYA reasons.
3. The large. They need such huge amounts of servers and storage, and so frequently, that they simply don’t have the time to put it in themselves, let alone do the testing. They don’t even have time to have a PS team come onsite and build it. They just want to buy large, ready-to-go chunks, shipped as ready to use as possible.
4. The rapidly growing.
5. Anyone wanting pre-tested, repeatable and predictable configurations.

Interesting factoid for the #3 case (large customer): They typically need extensive customizations and most of the time would prefer custom-built infrastructure pods with the exact configuration and software they need. For instance, some customers might prefer certain management software over others, and/or want systems to come preconfigured with some of their own customizations in-place – but they are still looking for the packaged product experience. FlexPod is flexible enough to allow that without deviating from the design. Of course, if the customer wants to dramatically deviate (i.e. not use one of the main components like Cisco switches or servers, for instance) – then it stops being a FlexPod and you’re back to building systems the traditional way.

What customers should really be looking for when building a stack?

In my opinion, customers should be looking for a more end-to-end experience.

You see – even with the virtualization stack in place, you will need to add:

• OSes
• DBs
• Email
• File Services
• Security
• Document Management
• Chargeback
• Backup
• DR
• etc etc.

You should partner with someone that can help you not just with the storage/virtualization/server/network stack, but also with:

• Proper alignment of VMs to maintain performance
• Application-level integration
• Application protection
• Application acceleration

In essense, treat things holistically. The vendor that provides your virtualization stack needs to be able to help you all the way to, say, configuring Exchange properly so it doesn’t break best practices, and ensuring that firmware revs on the hardware don’t clash with, say, software patch levels.

You still won’t avoid support complexity. Sure, maybe you can have Microsoft do a joint support exercise with the hardware stack VAR, but, no matter how you package it, you are going to be touching the support of the various vendors making up the entire stack.

And you know what?

It’s OK.

D

Technorati Tags: EMC, NetApp, VMware, Vblock, FlexPod, Cloud

It’s hosted on a large, famous service provider, and they use NetApp gear.

I was able to recover my file through NetApp snapshots – The provider makes this trivial by giving all users a GUI for it that looks like a normal file manager. All self-service.

No Vblocks, Avamar or Data Domain were harmed in the process that literally took all of one second to complete, most of which time was probably spent on Javascript doing its thing and the browser refreshing. BTW, I hadn’t touched that file since 2006.

This is a good example of storage for service providers doing more than just storing data.

With alternative solutions, a ticket would have to be opened, a helpdesk person would have to use a backup tool to find my file and restore it, then let me know. A whole lot more effort than what happened in this case.

In other news, I’m running the latest WordPress code, the site is now auto-optimized for mobile devices, and things are smooth again. Oh, and the old theme that most seemed to hate is gone. I’ll see if I can find a suitable picture for the header, for now this is OK.

If only that old version of WordPress I was using had a clean way of exporting stuff, if you look at older articles you’ll notice weird characters here and there. I might fix it. Probably not.

D

Technorati Tags: NetApp, snapshot

(NEWSFLASH: Watching the webcast now, the record they kept saying they would break ended up being some guy jumping over a bunch of EMC arrays with a motorcycle – and here I was hoping to see some kind of performance record…)

I’m not usually one to rain on anyone’s parade, but I keep seeing the “unified” word a lot, but based on what I’m seeing, it’s all more of the same, albeit with newer CPUs, a different faceplate, and (join the club) SAS. I’m sure the new systems will be faster courtesy of faster CPUs, more RAM and SAS. But are they offering something materially closer to a unified architecture?

Note that I’m not attacking anything in the EMC announcement, merely the continued “unified” claim. I’m sure the new Data Domain, Isilon and Vmax systems are great.

So here are some questions to ask EMC regarding VNX – I’ll keep this as a list instead of a more verbose entry to keep things easy for the ADD-afflicted and allow easier copy-paste into emails

1. Let’s say I have a 100TB VNX system. Let’s say I allocate all 100TB to NAS. Then let’s say that all the 100TB is really chewed up in the beginning but after a year my real data requirements are more like 70TB. Can I take that 30TB I’m not using any more and instantly use it for FC? Since it’s “unified” and all? Without breaking best practices for LUN allocation to Celerra? Or is it forever tied to the NAS part and I have to buy all new storage if I don’t want to destroy what’s there and start from scratch?
2. Is the VNX (or even the NS before it) 3rd-party verified as an over 5-nines system? (I believe the CX is but is the CX/NS combo?)
3. How is the architecture of these boxes any different than before? It looks like you still have 2 CX SPs, then some NAS gateways. Seems like very much the same overall architecture and there’s (still) nothing unified about it. I call for some truth in advertising! Only the little VNXe seems materially different (not in the software but in the amount of blades it takes to run it all).
4. Are the new systems licenced by capacity?
5. Can the new systems use more than the 2TB of FAST Cache?
6. On the subject of cache, what is the best practice regarding the minimum number of SSDs to use for cache? Is it 8? How many shelves/buses should they be distributed on?
7. What is the best practice regarding cache oversubscription and how is this sized?
8. Since the FAST Cache can also cache writes, what are the ramifications if the cache fails? How many customers have had this happen? After all, we are talking about SSDs, and even mirrored SSDs are much less reliable than mirrored RAM.
9. What’s the granularity for using RecoverPoint to replicate the NAS piece? Seems like it needs to replicate everything NAS as one chunk as a large consistency group, with Celerra Replicator needed for more granular replication.
10. What’s the granularity for recovering NAS with RecoverPoint? Seems like you can’t do things by file or by volume even. The entire data mover may need to be recovered in one go, regardless of the volumes within.
11. When using RecoverPoint, does one need to not use storage pools for certain operations? And what does that mean regarding the complexity of implementation?
12. Speaking of storage pools, when are they recommended, when not, and why? And what does that mean about the complexity of administration?
13. What functionality does one lose if one does not use pools?
14. Can one prioritize FAST Cache in pool LUNs or is cache simply on or off for the entire pool?
15. Can I do a data-in-place upgrade from CX3 or CX4 or is this a forklift upgrade?
16. Why is FASTv2 not recommended for Exchange 2010 and various other DBs?
17. If Autotiering is not really applicable to many workloads, what is it really good for?
18. What is the percentage of flash needed to properly do autotiering on VNX? (it’s only 3% on VMAX since it uses a 7MB page, but VNX uses a 1GB page, which is far more inefficient). Why is FAST still at the grossly inefficient 1GB chunk?
19. Can FAST on the VNX exclude certain time periods that can confuse the algorithms, like when backups occur?
20. Is file-level FAST still a separate system?
21. Why does the low-end VNXe not offer FC?
22. Can I upgrade from VNXe to VNX?
23. Does the VNXe offer FAST?
24. Can a 1GB chunk span RAID groups or is performance limited to 1 RAID group’s worth of drives?
25. Why are functions like block, NAS and replication still in separate hardware and software?
26. Why are there still 2 kinds of snapshotting systems?
27. Are the block snaps finally without a huge write performance impact? How about the NAS snaps?
28. Are the snaps finally able to be retained for years if needed?
29. Why are there 4 kinds of replication? (Mirrorview, Celerra Replicator, Recoverpoint, SAN copy)
30. Why are there still all these OSes to patch? (Win XP in the SPs, Linux on the Control Station and RecoverPoint, DART on the NAS blades, maybe more if they can run Rainfinity and Atmos on the blades as well)
31. Why still no dedupe for FC and iSCSI?
32. Why no dedupe for memory and cache?
33. Why not sub-file dedupe?
34. Why is Celerra still limited to 256TB per data mover?
35. Is Celerra still limited to 16TB per volume? Or is yet another, completely separate system (Isilon) needed to do that?
36. Is Celerra still limited to not being able to share a volume between data movers? Or is, again, Isilon needed to do that?
37. Can Celerra non-disruptively move CIFS and NFS volumes between data movers?
38. Why can there not be a single FCoE link to transfer all the protocols if the boxes are “unified”?
39. Have the thin provisioning performance overheads been fixed?
40. Have the pool performance bottlenecks been fixed? Or is it still recommended to use normal RAID LUNs for highest performance?
41. Can one actually stripe/restripe within a FLARE pool now? When adding storage? With thin provisioning?
42. What is the best practice for expanding, say, a 50 drive pool? How many drives do I have to expand by? Why?
43. Does one still need to do a migration to use thin provisioning?
44. Does one need to do yet another migration to “re-thin” a LUN once it gets temporarily chunky?
45. Have the RAID5 and RAID6 write inefficiencies been fixed? And how?
46. Will the benchmarks for the new systems use RAID6 or will they, again, show RAID10? After all, most customers don’t deploy RAID10 for everything, and RAID5 is thousands of times less reliable than RAID6. How about some SPC-1 benchmarks?
47. Why is EMC still not fessing up to using a filesystem for their new pools? Maybe because they keep saying doing so is not a “real” SAN, even in recent communication?
48. Since EMC is using a filesystem in order to get functionality in the CX SPs like pools, thin provisioning, compression and auto-tiering (and probably dedupe in the future), how are they keeping fragmentation under control? (how the tables have turned!)

What I notice is a lack of thought leadership when it comes to technology innovation – EMC is still playing catch-up with other vendors in many important architectural areas,  and keeps buying companies left and right to plug portfolio holes. All vendors play catch-up to some extent, the trick is finding the one playing catch-up in the fewest areas and leading in the most, with the fewest compromises.

Some areas of NetApp leadership to answer a question in the comments:

• First Unified architecture (since 2002)
• First with RAID that has the space efficiency of RAID5, the performance of RAID10 and the reliability of RAID6
• First with block-level deduplication for all protocols
• FIrst with zero-impact snapshots
• First with Megacaches (up to 16TB cache per system possible)
• First with VMware integration including VM clones
• First with space- and time-efficient, integrated replication for all protocols
• First with snapshot-based archive storage (being able to store different versions of your data for years on nearline storage)
• First with Unified Connect and FCoE – single cable capability for all protocols (FC, iSCSI, NFS, CIFS)

However, EMC is strong when it comes to marketing, messaging and – wait for it – the management part. Since it’s amazingly difficult to integrate all the technologies EMC has acquired over the years (heck, it’s taking NetApp forever to properly integrate Spinnaker and that’s just one other architecture), EMC is focusing instead on the management of the various bits (the current approach being Unisphere, tying together a subset of EMC’s acquisitions).

So, Unified Storage in EMC-speak really means unified management. Which would be fine if they were upfront about it. Somehow, “our new arrays with unified management but not unified architecture” doesn’t quite roll off the tongue as easily as “unified storage”.

Mike Riley eloquently explains whether it’s easier to fix an architecture or fix management here. Ultimately, unified management can’t tackle all the underlying problems and limitations, but it does allow for some very nice demos.

A cool GUI with frankenstorage behind it is like putting lipstick on a pig, or putting a nice shell on top of a car cobbled together from disparate bits. The underlying build is masked superficially, until it’s not… usually, at the worst possible time.

Sure, ultimately, management is what the end user interfaces with. Many people won’t really care about what goes on inside, nor have the time or inclination to learn. I merely invite them to start thinking more about the inner bits, because when things get tricky is also when something like a portal GUI meshing 4-5 different products together also stops working as expected, and that’s also when you start bouncing between 3-4 completely different support teams all trying to figure out which of the underlying products is causing the problem.

Always think in terms of what happens if something goes wrong with a certain subsystem and always assume things will break – only then can you have proper procedures and be prepared for the worst.

And always remember that the more complex a machine, the more difficult it can be to troubleshoot and fix when it does break (and it will break – everything does). There’s no substitute for clean and simple engineering.

Of course, Rube Goldberg-esque machines can be entertaining… if entertainment is what you’re after

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Technorati Tags: benchmark, EMC, FAST, FAST Cache, FASTv2, Flash, NetApp, performance, RAID-DP, RAID6, SSD, VNX

One of the features of NetApp storage is that by using Converged Network Adapters (CNAs) one can use a single wire and transport over that FC, iSCSI, NFS and CIFS, at the same time.

You see, since NetApp storage is truly unified, we don’t need cables coming out of 5 different boxes running 3 or more different OSes to do something (which is what, say, a certain competitor’s “unified” box is like – actually it’s even more boxes if one counts the external replication devices).

You might say “OK, that’s cool but how does it affect my bottom line?”

Just a few benefits that immediately come to mind:

1. Far less cables to run in your datacenter for both storage and all the servers (each server needs 2 cables for redundancy vs 4 or more)
2. No compromises since there’s no need to be forced to choose between iSCSI, NAS and FC – each server can happily use whatever’s best for the task at hand yet retain the exact same connectivity
3. Less switches (no need for both FC and Ethernet switches)
4. Less OpEx since it’s a simpler solution to manage
5. Very high speeds (each link is 10Gbit) and low latency (FCoE is similar to FC – no need to do iSCSI if the same link can do both)
6. Overall a far simpler and cleaner Datacenter

The other part is also important: Single OS. Inherently, something running a single OS has 3x less moving parts than something running 3 totally different OSes, regardless of packaging.

Here are some cool throughput results. Line speeds

One can dance around such concepts with marchitecture and fancy Powerpoint slides, but, in the end, just use your head. It’s pretty simple.

Food for thought…

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SPEC SFS is more cache-friendly than the brutal SPC-1, click here for some more information regarding this industry-standard NAS benchmark. The idea is that thousands of CIFS and NFS servers have been profiled and the benchmark reflects real-life NAS usage patterns.

In the same vein as the SPC-1 benchmarks, the configurations we submit to the standard benchmarking authorities are based on realistic systems customers could buy, not $7m lab queens. So, NetApp SPEC and SPC submissions:

• Are always tested with RAID-DP (RAID-6 protection equivalent) – other vendors test with RAID10 most of the time, and never with RAID-6 (ask them why this is, BlueArc gets respect for being the only other one in the list doing our level of protection)
• Have a target of using the most cost-effective configuration possible
• Provide not just high IOPS but also very low latency
• Are a realistic, deployable configuration, not just the fastest box we have (we still have the 1 million SPEC ops record for a 24-node system, that’s kind of pricy plus the result is old and can’t be compared with the current benchmark code – still, look at the rankings).

So, with those lofty goals in mind, we have 3 new submissions:

1. CIFS benchmark, 3210 w/ SATA drives – typical low/mid-range system
2. NFS benchmark, 3270 w/ SAS drives – typical mid-range system, no Flash Cache used in this one.
3. NFS benchmark, 6240 w/ SAS drives – typical high-end (but not highest) system.

All NetApp systems included some Flash Cache memory boards to provide further acceleration (EDIT: aside from the 3270). We have an even faster system (6280) that we will be submitting later on as a special treat (there’s a certain degree of red tape and ceremony to even do one submission…)

Here’s an abbreviated chart in easily digestible form – showing the most recent results from perennial rivals NetApp and EMC (BTW – of all the systems in the chart, only one of them is truly unified and can provide block and NAS on the same architecture without the need for contortions).

Guide to reading the chart, and lessons learned:

• A “puny” NetApp 3210 with SATA gets better overall response time than an all-SSD V-Max costing well over 10x
• Notice the amount of usable space on NetApp systems, with even better protection than RAID10
• The 6240 scored far higher even though it had less disks
• The NetApp systems have “just” 2 controllers that do everything, vs. the EMC submissions with 4 V-Max engines, plus extra Celerra Data Movers and Control Stations on top. What do you think is more efficient?

In slide format:

I do have some questions to ask certain other vendors as a parting shot:

1. Sun/Oracle – you keep saying your new boxes are a cheaper way to get NetApp-type functionality, you’ve had them for a while, why not submit to SPEC or SPC? (there is not a single SPEC result from Sun).
2. EMC – maybe show the world how a system not based on V-Max runs? With RAID-6? (Even V-Max with RAID6, no problem…)
3. EMC: What’s the deal with the exported capacity, even with 312x drives?
4. All of you with large striped pools of RAID5 – have you bothered explaining to your customers what will happen to the pool if you have a dual-drive failure in any RAID group? Unacceptable.

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SPC-1 is one of the worst things you can do to a disk array. The benchmark itself does a lot of writes, is highly random and is hostile to most caching systems. Which neatly explains why IBM has all kinds of system submissions but doesn’t show XIV, and the complete absence of another prominent vendor (look at the submissions, you’ll figure it out – the big boys of storage are NetApp, IBM, HDS, HP and one more ).

That same vendor might complain that SPC-1 is not always representative of real-life workloads but, short of putting all possible systems in your datacenter, nothing really will represent exactly how you massage your data. At least SPC-1 is a well-established standard and a great torture test for systems. All the other vendors are participating after all. And, interestingly, the SPEC SFS NAS benchmark doesn’t seem to bother said vendor’s anti-SPC crew none (spec.org). How come that one is more “real”? (NetApp participates in both block and NAS standard benchmarks BTW, since our systems all do both).

Some things to look for when trying to decipher SPC-1 results:

• Type of RAID used (RAID-DP, RAID10, RAID5, RAID6)
• How many drives were used to get the final result
• The cost for the configuration
• The price/performance
• How much of the storage was usable, how much was unused…

For instance – a system that can do 50,000 SPC-1 IOPS with 100 disks and RAID6, is far more efficient than one that needs 200 disks and RAID10 to achieve the same result.

My favorite way of reading the results is figuring out the effective IOPS per drive, see how close (or far) it is from the 220 IOPS a normal modern 15K drive can sustain without RAID, with good response times.

So, without further ado, looky here… it’s the link to the results page showing all the vendors. Or here for the full details. 68,000 sustained IOPS with 120 ordinary 300GB drives and just 2 Flash Cache modules, with 84% of the usable space occupied.

What this means to you:

The effective IOPS per drive for the NetApp 3270 submission are 567. Next best is around 400, most vendors can’t break 300, and the highest scoring systems (relying on thousands of drives and many controllers) don’t break 200.

It is important to note that NetApp is the only vendor in the list showing results with dual-parity RAID-DP (RAID6 equivalent protection). All other vendors are doing RAID10! If your vendor is selling you RAID5, that’s not representative of their systems in the chart!

The NetApp result boils down to 13,600 sustained IOPS per shelf of 15K drives, and a system cost that’s very reasonable for the reliability, performance and features provided.

What this means to the anti-NetApp FUD club with their complex auto-tiering schemes that need 15 types of drives…

You really need to figure out how to present a decent result with:

• RAID6 (otherwise your RAID1 or RAID5 protection is inferior to NetApp RAID-DP, especially when talking about large pools)
• Your fancy auto-tiering algorithm showing no performance degradation on the unpredictable SPC-1 workload while still storing data on all drive tiers (otherwise, it’s single-tiering, and not auto-tiering)
• Large caches. If your competitive product can use Megacaches, and you claim you can do efficient write caching with them, how about we all see how effective that is? After all, you claim that’s a huge benefit. We show the world ours, show yours. Otherwise, your product is only fast on Powerpoint slides, and I’ve yet to see a product fail on Powerpoint.

Stand by for more results from the bigger boxes, this wasn’t one of them, but it is a realistic system companies could actually afford and not a $7m all-SSD config like some others have…

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Technorati Tags: benchmark, EMC, FAST, FAST Cache, FASTv2, Flash, Flash Cache, NetApp, performance, RAID-DP, RAID6, SSD

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The question was raised in public forums such as Twitter – someone mentioned that this figure may be more usable Solid State storage than all other enterprise disk vendors have sold combined (whether it’s used for caching or normal storage – I know we have greatly outsold anyone else that does it for caching alone ).

I don’t know if it is, maybe the boys from the other vendors can chime in on this and tell us, after RAID, how much usable SSD they’ve sold, but the facts remain:

• NetApp has demonstrated thought leadership in pioneering the pervasive use of Megacaches
• The market has widely adopted the NetApp Flash Cache technology (I’d say 3PB of usable cache is pretty wide adoption)
• The performance benefits in the real world are great, due to the extra-granular nature of the cache (4KB blocks vs 64+ KB for others) and extremely intelligent caching algorithms
• The cost of entry is extremely reasonable
• It’s a very easy way to add extra performance without forcing data into faster tiers.

Comments welcome…

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Technorati Tags: EMC, FAST, FAST Cache, FASTv2, Flash, Flash Cache, NetApp, RAID-DP, RAID6, SSD

Before anyone starts frothing at the mouth, notice that in the categories this post is part of FUD Always do your own analysis… I just wanted to give people some food for thought, like I did when FASTv1 came out. I didn’t make this up, it’s all based on various EMC documents available online. I advise people looking at this technology to ask for extensive documentation regarding best practices before taking the leap.

As a past longtime user and sometimes pusher of EMC gear, some of the enhancements in FASTv2 seemed pretty cool to me, and potentially worrisome from a competitive standpoint. So I decided to do some reading to see how cool the new technology really is.

Summary of the new features:

• Large heterogeneous pools (a single pool can consist of different drive types and encompass all drives in a box minus the vault and spares)
• FASTv2 – sub-LUN movement of hot or cold chunks of data for auto-tiering between drive types
• FAST Cache – add plain SSDs as cache
• Much-touted feature: ability to use SSD as a write cache
• LUN compression
• Thin LUN space reclamation

It all sounds so good and, if functional, could bring Clariions to parity with some of the more advanced storage arrays out there. However, some examination of the features reveals a few things (I’m sure my readers will correct any errors). In no particular order:

EMC now uses a filesystem

It finally had to happen, thin LUN pools at the very least live on a filesystem laid on top of normal RAID groups (and I suspect all new pools on both Symm and CX now live on a filesystem). So is it real FC or some hokey emulation? Not that it matters if it provides useful functionality impossible to achieve otherwise, it’s just an about-face. But how mature is this new filesystem? Does it automatically defragment itself or at least provide tools for manual defragmentation? Filesystem design is not trivial.

LUN compression

1. Best practices indicate compression should not be used for anything I/O intensive and is best suited for static workloads (i.e. not good for VMs or DBs). However, new data is compressed as a post-process, which theoretically doesn’t penalize new writes – which I find interesting. Also: What happens with overwrites? Do compressed blocks that need to be overwritten get uncompressed and re-laid down uncompressed until the next compression cycle? Do the blocks to be overwritten get overwritten in their original place or someplace new? What happens with fragmentation? It all sounds so familiar
2. The read performance hit is reported to be about 25% – makes sense since the CPU has to work harder to uncompress the data.
3. Turning on compression for an existing traditional LUN means the LUN will need to be migrated to a thin LUN in a pool (not converted, migrated – indeed, you need to select where the new LUN will go). Not an in-place operation, it seems.
4. Does data need to be migrated to a lower tier in order to be compressed?
5. It follows you need enough space for the conversion to take place… (can you do more than one in parallel? If so, quite a bit of extra space will be needed).
6. How does this work with external replication engines like RecoverPoint? Does data need to be uncompressed? (probably counts as a normal “read” operation which will uncompress the data).
7. Does this kind of compression mess with alignment of, say, VMs? This could have catastrophic consequences regarding performance of such workloads…

Thin LUN space reclamation

1. Another case where migration from thick to thin takes place (doesn’t seem like the LUN is converted in-place to thin)
2. Unclear whether an already thin LUN that has temporarily ballooned in size can have its space reclaimed (NetApp and a few other arrays can actually do this). You see, LUNs don’t only grow in size… several operations (i.e. MS Exchange checking) can cause a LUN to temporarily expand in space consumption, then go back down to its original size. Thin provisioning is only truly useful if it can help the LUN remain thin

Dual-drive ownership, especially when it pertains to pool LUNs

Dual-drive ownership is not strictly a new feature, but best practices is for a single CX controller (SP) to own a drive, and not have it shared. Furthermore, with pool LUNs, if you change the controller ownership of a pool LUN, I/O will see much higher latencies – it’s recommended to do a migration to a new LUN controlled by the other SP (yet another scenario that needs migration). I’m mentioning this since EMC likes to make a big deal about how both controllers can use all drives at the same time… obviously this is not nearly as clean as it’s made to appear. The Symmetrix does it properly.

Metadata used per thin LUN

3GB is the minimum space a thin LUN will occupy due to metadata and other structures. Indeed, LUN space is whatever you allocate plus another 3GB. Depending on how many LUNs you want to create, this can add up, especially if you need many small LUNs.

Loss of performance with thin LUNs and pools in general

It’s not recommended to use pools and especially thin LUNs for performance-sensitive apps, and in general old-style LUNs are recommended for the highest performance, not pools. Which is interesting, since most of the new features need pools in order to work… I heard 30% losses if thin LUNs are used in particular, but that’s unconfirmed. I’m sure someone from EMC can chime in.

Expansion, RAID and scalability caveats with pools

1. To maintain performance, you need to expand the pool by adding as many drives as the pool already has – I suspect this has something to do with the way data is striped. This could cause issues as the system gets larger (who will really expand a CX4-960 by 180 drives a pop? Because best practices state that’s what you have to do if you start with 180 drives in the pool) .
2. Another thing that’s extremely unclear is how data is load-balanced among the pool drives. Most storage vendors are extremely open about such things. All I could tell is that there are maximum increments at which you can add drives to a pool, ranging from 40 on a CX4-120 to 180 on a CX4-960. Since a pool can theoretically encompass all drives aside from vault and spares, does this mean that striping happens in groups of 180 in a CX4-960 and if you add another 180 that’s another stripe and the stripes concatenated?
3. What if you don’t add drives by the maximum increment, and you only add them, say, 30 at a time? What do you give up, if anything?
4. RAID6 is recommended for large pools (which makes total sense since it’s by far the most reliable RAID at the moment when many drives are concerned). However, RAID6 on EMC gear has a serious write performance penalty. Catch-22?

FAST Cache (includes being able to cache writes)

1. Cache only on or off for the entire pool, can’t tune it per LUN (can only be turned on/off per LUN if old-style RAID groups and LUNs are used).
2. 64KB block size (which means that a hot 4K block will still take 64K in cache – somewhat inefficient).
3. A block will only be cached if it’s hit more than twice. Is that really optimal for the best hit rate? Can it respond quickly to a rapidly changing working set?
4. Unclear set associativity (important for cache efficiency).
5. No option to automatically optimize for sequential read after random write workloads (many DB workloads are like that).
6. Flash drives aren’t that fast for writes as confirmed by EMC’s Barry Burke (the Storage Anarchist) in his comment here and by Randy Loeschner here. Is the write benefit really that significant? Maybe for Clariions with SATA, possibly due to the heavy RAID write penalties, especially with RAID6.
7. It follows that highly localized overwrites could be significantly optimized since the Clariion RAID suffers a great performance degradation with overwrites, especially with RAID6 (something other vendors neatly sidestep).
8. EMC Clariions don’t do deduplication so the cache isn’t deduplicated itself, but is it at least aware of compression? Or do blocks have to be uncompressed in cache? Either way, it’s a lot less efficient than NetApp Flash Cache for environments where there’s a lot of block duplication.
9. The use of standard SSDs versus a custom cache board is a mixed blessing – by definition, there will be more latency. At the speeds these devices are going, those latencies add up (since it’s added latency per operation, and you’re doing way more than one operation). All high-end arrays add cache in system boards, not with drives…
10. Smaller Clariions have severely limited numbers of flash drives that can be used for caching (2-8 depending on the model, with the smaller ones only able to use very small cache drives). Only the CX4-960 can do 20 mirrored cache drives, which I predict will provide good performance even for fairly heavy write workloads. However, that will come at a steep price. The idea behind caches like NetApp’s Flash Cache is to reduce costs…

For a very detailed discussion regarding megacaches in general read here.

I can see FAST Cache helping significantly on a system with lots of SATA in a well-configured CX4-960. And I can definitely see it helping with heavy read workloads that have good locality of reference, since SSDs are very good for reads.

And finally, the pièce de résistance,

FASTv2

This is EMC’s sub-LUN auto-tiering feature. Meaning that a LUN is chopped up into 1GB chunks, and that the 1GB chunks move to slower or faster disks depending on how heavily accessed they are. The idea being that, after a little while, you will achieve steady state and end up with the most appropriate data on the most appropriate drives.

Other vendors (most notably Compellent and now also 3Par, IBM and HDS) have some form of that feature (Compellent pioneered this technology and has the smallest possible chunks I believe at 512KB).

The issues I can see with the CX approach of FASTv2:

1. Gigantic 1GB slice to be moved. EMC admits this was due to the Clariion not being fast enough to deal with the increased metadata of many smaller slices (the far more capable Symmetrix can do 768KB per slice, offering far more granularity). It follows that the bigger the slice the less optimal the results are from an efficiency standpoint.
2. All RAID groups within the pool have to be of the same RAID type (i.e, RAID6). So you can’t have, say, SATA as RAID6 and SSD as RAID5 in the same pool. Important since RAID6 on most arrays has a big performance impact.
3. Unknown performance impact for keeping track of the slices (possibly the same as using thin provisioning – 30% or so?)
4. The most important problem in my opinion: Too much data can end up in expensive drives. For instance, imagine a 1TB DB LUN. That LUN will be sliced into 1,000x 1GB chunks. Unless the hotspots of the DB are extremely localized, even if a few hundred blocks are busy per slice, that entire slice will get migrated to SSD the next day (it’s a scheduled move). Now imagine if, say, half the slices have blocks that are deemed busy enough – half the LUN (512GB in this example) will be migrated to SSD, even if the hot data in those slices were more like 5GB (say a 10% working set size, quite typical). Clearly, this is not the most effective use of fast disks. EMC has hand-waved this objection away in the past, but if it’s not important, why does the Symmetrix go with the smaller slice?
5. Extremely slow transactional performance for the data that has been migrated to SATA, especially with RAID6 – EMC says you need to pair this with FAST Cache, which makes sense… Of course, come next day that data will move to SSD or FC drives, but will that be fast enough? Policies will have to be edited and maintained per application (often removing the auto-tiering by locking an app at a tier), which removes much of the automation on offer.
6. The migration is I/O intensive, and we’re talking about migrations of 1GB slices (on a large array, many thousands of them). What does that mean for the back-end? After all, once a day all the migrations need to be processed… and will need to contend with normal I/O activity.
7. Doesn’t support compressed blocks, data needs to be uncompressed in order to be moved.
8. I still think this technology is most applicable to fairly predictable, steady workloads with good locality of reference.

Messaging inconsistencies

As I’ve mentioned before, I don’t have an issue with EMC’s technology, merely with the manner in which the capabilities and restrictions are messaged (or not, as the case may be). For instance, I’ve seen marketing announcements and blog entries talking about doing VMware on thin LUNs with compression etc. – sure, that could be space-efficient, but will it also be fast?

Now that the limitations of the new features are more understood, EMC’s marketing message loses some of its punch.

• Will compression really work with busy VMware or DB setups?
• Will thin LUNs be OK for busy systems?
• Unless 20 disks are used for FAST Cache (only with a CX4-960), is the performance really enough to accelerate highly random writes on large systems?
• What is the performance impact of thin LUNs for highly-intensive workloads?
• What is the performance of a large system all running RAID6?
• Last but not least – does the filesystem EMC uses allow defragmentation? By definition, features such as thin provisioning, compression and FAST will create fragmentation.

Moreover – what all the messaging lacks is some comparison to other people’s technology. Showing a video booting 1000 VMs in 50 minutes where before it took 100 is cool until you realize others do it in 12.

And why is EMC (I’m picking on them since they’re the most culpable in this aspect) ridiculing technologies such as NetApp’s Flash Cache and Compellent’s Data Motion only to end up implementing similar technologies and presenting things to the world as if they are unique in figuring this out? “You see, none of the other guys did it right, now that we did it it’s safe”.

Too many of the new features are extremely obscure in their design, if storage professionals can’t easily figure them out, how is the average consumer expected to? I think more openness is in order, otherwise it just looks like you have something to hide.

Ultimately – the devil is in the details, so why would you have to choose between space OR performance, and not be able to optimize space utilization AND performance?

I think it has to do with the original design of your storage system. Not all systems lend themselves to advanced features because of the way they started.

But that’s a subject for another day.

D

In a nutshell: We have numbers (published only after VMware engineering themselves approved the paper as accurate and gave their permission) proving that, compared to traditional arrays, running virtualized workloads on NetApp gear needs less resources while providing excellent performance.

If you don’t want to spend time reading Vaughn’s article, this link has the goods in impressive detail.

It’s worth noting the “traditional” array had a lot more disks and RAM, but the NetApp array had a Flash Cache module. We are not allowed to publish the vendor of the “traditional” array due to licensing restrictions, but, as mentioned, VMware engineering verified the results – the test was legit (no vendor is allowed to publish VMware performance data unless VMware engineering has verified all testing was aboveboard and accurate).

Some pictures for the impatient:

Key take-aways:

1. A lot less disk space needed with NetApp
2. A lot quicker to provision the VMs
3. Faster performance than RAID10 even without the Flash Cache (and dramatically higher with)
4. No-compromise RAID-DP offers same protection as RAID6 without the penalty
5. NFS for VMware can be pretty fast inded given the appropriate storage behind!

D

It’s funny how some vendors won’t hesitate to wholeheartedly agree when some “independent” blogger criticizes their competition (before I get flamed, independent in quotes since, as I discussed before, there ain’t no such thing whether said blogger realizes it or not – being biased is a basic human condition).

The equivalent of someone posting in an Audi forum about excessive brake dust, and having guys from Mercedes and BMW chime in and claim how they “tested” Audis and indeed they had issues (but of course!) and how their cars are better now and indeed maybe Audi doesn’t have as much of a lead any more (if, indeed, they ever did). I think the term for that is “shill” but I can understand taking every opportunity to harm an opponent.

So the “Storage Architect” posted entries asking about certain features to be implemented on NetApp storage, one of them being able to reduce the size of an aggregate. Then everyone and their mum jumped on and complained how on earth such an important feature isn’t there BTW I’m not saying such a thing wouldn’t be useful to have from time to time. I’ll just try to explain why it’s tricky to implement and maybe ways to avoid problems.

For the uninitiated, a NetApp aggregate is a collection of RAID-DP RAID groups, that are pooled, striped and I/O then hits all the drives from all RAID groups equally for performance. You then carve out volumes out of that aggregate (containers for NFS, CIFS, iSCSI, FC).

A pretty simple structure, really, but effective. Similar constructs are used by many other storage vendors that allow pooling.

So, the question was, why not be able to make an aggregate smaller? (you can already make it bigger on-the-fly, as well as grow or shrink the existing volumes within).

An HP guy them proceeded to complain about how he put too few drives in an aggregate and ended up with an imbalanced configuration while trying to test a NetApp box.

So, some basics:  the following picture shows a well-balanced pool – notice the equal number of drives per RAID group:

The idea being that everything is load-balanced:

Makes sense, right?

You then end up with pieces of data across all disks, which is the intent. Growing it is easy – which is, after all, what 99.99% of customers ever want to do.

However, the HP dude didn’t have enough disks to create a balanced config with the default-sized RAID group (16). So he ended up with something like this, not performance-optimal:

So what the HP dude wanted to do, was to reduce the size of the RAID group and remove drives, even though he expanded the aggregate (and by extension the RAID group) originally.

Normally, before one starts creating pools of storage (with any storage system), one also knows (or should) what one has to play with in order to get the best overall config. It’s like “I want to build a 12-cylinder car engine, but I only have 9 cylinders”. Well – either buy more cylinders, or build an 8-cylinder engine! Don’t start building the 12-cylinder engine and go “oops” This is just Storage 101. Mistakes can and do happen, of course.

So, with the current state of tech, if I only had 20 drives to play with (and no option to get more), assuming no spares, I’d rather do one of the following:

1. Aggregate with 10 + 10 RAID groups inside or
2. Use all 20 drives in a single RAID group for max space
3. Ask someone that knows the system better than I do for some advice

This is common sense and both doable and trivial with a NetApp system. The idea is you set the desired RAID group size for that aggregate BEFORE you put in disks. Not really difficult and pretty logical.

For instance, aggr options HPdudeAggr raidsize 10 before adding the drives would have achieved #1 above. Graphically, the Web GUI has that option in there as well, when you modify an aggregate. The option exists and it’s well-known and documented. Not knowing about it is a basic education issue. Arguing that no education should be needed to use a storage device (with an extreme number of features) properly even for deeply involved, low-level operations, is a romantic notion at best. Maybe some day. We are all working hard to make it a reality. Indeed, a lot of things that would take a really long time in the past (or still, with other boxes) have become trivialized – look at SnapDrive and the SnapManager products, for instance.

Back to our example: if, in the future, 10 more disks were purchased, and approach #1 above was taken, one would simply add the ten disks to the aggregate with aggr add HPdudeAggr 10. Resulting in a 10+10+10 config.

But what if I had done #2 above (make a 20-drive RAID group the default for that aggregate)?

Then, simply, you’d end up imbalanced again, with a 20+10. Some thought is needed before embarking on such journeys.

Maybe a better approach would be to add, say, a more reasonable number of drives to achieve good balance? Adding 12 more drives, for example, would allow for an aggregate with 16+16 drives. So, one could simply change the raidsize using aggr options HPdudeAggr raidsize 16, then, add the 12 disks to the aggregate with aggr add HPdudeAggr -g all 12.

This would expand both RAID groups contained within the aggregate dynamically to 16 drives per, resulting in a 16+16 configuration. Which, BTW, is not something you can easily do with most other storage systems!

Having said all that, I think that for people that are not storage savvy (or for the storage savvy that are suffering from temporary brain fog), a good enhancement would be for the interfaces to warn you about imbalanced final configs and show you what will be created in a nice graphical fashion, asking you if you agree (and possibly providing hints on how it could be done better).

I’m not aware of any other storage system that does that degree of handholding but hey, I don’t know everything.

Indeed, maybe the nature of the other posts was being bait so I’ll obligingly take the bait and ask the question so you can advertise your wares here:

Is anyone aware of a well-featured storage system from an established, viable vendor that currently (Aug 7, 2010, not roadmap or “Real Soon Now”) allows the creation of a wide-striped pool of drives with some RAID structures underneath; then allows one to evacuate and then destroy some of those underlying RAID groups selectively, non-disruptively, without losing data, even though they already contain parts of the stripes; then change the RAID layout to something else using those same existing drives and restripe without requiring some sort of data migration to another pool and without needing to buy more drives? Again, NOT for expansion, but for the shrinking of the pool?

To clarify even further: What the HP guy did was exactly this: He had 20 drives to play with, he created by mistake a pool with 2 RAID groups, 14+2 and a 2+2, how would your solution take those 2 RAID groups, with data, and change the config to something like 10 + 10 without needing more drives or the destruction of anything?

Can you dynamically reduce a RAID group? (NetApp can dynamically expand, but not reduce a RAID group).

I’m not implying such a thing doesn’t exist, I’m merely curious. I could see ways to make this work by virtualizing RAID further. Still, it’s just one (small) part of the storage puzzle.

The one without sin may cast the first stone!

D

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