EMC’s VNX2 forklift: The importance of hardware re-use, slowing down obsolescence, and maximizing your investment

It was with interest that I watched the launch of EMC’s VNX refresh. The updated boxes got some long-awaited features, EMC talked a lot about how some pretty severe single-threaded bottlenecks were removed, more CPU and memory was put in, and there was much rejoicing.

Not really trying to pick on the new boxes (that will be in a future post, relax :)), but what I thought was interesting was that the code that makes most of the new features a possibility cannot be loaded on current-gen VNX boxes (not even the biggest, the 7500, which has plenty of CPU and RAM juice even compared to the next gen boxes).

Software-defined storage indeed.

The existing VNX disk shelves also seemingly can’t be re-used at the moment (correct me if I’m wrong please).

This forced obsolescence has been a theme with EMC: Clariion -> VNX -> VNX2 are all complete forklift upgrades. When the original VNX was released, it was utterly incompatible with the CX (Clariion) shelves (SAS replaced FC connectivity). Despite using the exact same code (FLARE).

Other vendors are guilty of this too – a new controller is released, and all prior investments on disk shelves are rendered useless (HDS did this with several iterations of AMS, maybe even with AMS -> HUS, HP with EVA…)

I understand that as technology progresses we sometimes have to abandon the old to make room for the new but, at the same time, customers make significant investments in N-1 technology – and often want to be able to re-use some of their investment with N (and sometimes N+1).

I just had this conversation with a customer, and he said “well, I throw away my gear every 3 years, why should I care?

Let’s try a thought experiment.

Imagine you just bought a system that’s running the fastest controllers a company sells today, and you got 1PB of storage behind it.

Now, imagine that a mere month after you purchased your controllers, new ones are released that are significantly faster. OK, that stuff happens.

Your gear is not 3 years old yet. It’s 1 month old. It’s running OK.

Now, imagine that your array runs out of steam 6 months later due to unprecedented performance growth. Your system is now 7 months old. You can’t just throw it away and start fresh.

You could buy a new storage system and migrate some of the data to share the load. However, you don’t need more space – you just ran out of controller headroom. Indeed, you still have tons of free space.

But what if you could replace the controllers with the new, beefier ones? And maintain your investment in the 1PB of storage, cache etc? Wouldn’t that be nice?

Or at least be able to move some of the storage pools you may have to the new family of controllers? Even if you had to reformat the disk?

Well – most vendors will tell you “sorry, no, you need to migrate your data to the new box”.

Let’s try another thought experiment.

You bought a storage system a year ago. It performs fine, but it lacks true deduplication capabilities. You have determined it would save you a lot of storage space (= money) if your array had deduplication.

The vendor you purchased the system from announces the refreshed storage OS that finally includes deduplication. And that same vendor made a truly gigantic fuss about software-defined storage, which made everyone feel software would be the big enabler and that coolness was a mere firmware upgrade away.

However, you are eventually told they will not allow the code that enables deduplication to be loaded to your array, and, instead, they ask you to migrate to the refreshed array that supports deduplication. Since the updated code somehow only runs on the new box. Something to do with unicorn milk.

But your array has plenty of CPU headroom to handle deduplication… and you could reformat the disks given some swing storage shelves if the underlying disk format is the issue. But the option is not provided.

How NetApp does things instead

At NetApp we sort of take it for granted so we don’t make a big fuss about software-defined storage, but hardware was always considered an enabler for the software and not the other way around. 

For instance: deduplication was released as a free software upgrade for Data ONTAP (the OS for our main line of storage). Back in 2007. For all storage protocols.

In general, we try to let systems be able to load at a minimum N+1 software releases, but most of the time we utterly spoil customers and go far above and beyond, unless we’re talking about the smallest boxes, which naturally have less headroom.

For example, the now aging FAS 3070 I have in the local lab (the bigger of the older midrange boxes, released in 2006) supports anything from ONTAP 7.2.1 (what it was released with) to ONTAP 8.1.3 (released in mid-2013).

This spans multiple major ONTAP releases – huge changes in the code have happened during those releases: 7.3, 8.0, 8.1… Multiple newer arrays were also released as replacements for the 3070: 3170, 3270, 3250.

Yet the 3070 soldiers on with a fully supported, modern OS, 7 years later.

What arrays did our competitors have back then? What is the most modern OS those same arrays can run today? What is that OS missing vs the OS that competitor’s more modern arrays have?

Let’s talk disk shelves.

We used FC loop connectivity for the older shelves (DS14). We then switched to fancy multi-channel SAS and totally different shelves and disks, but never stopped supporting the older shelf technology, even with newer controllers.

That’s the big one. I have customers with DS14 shelves that they purchased for a 3070 that they now have on a 3270 running 8.2. It all works, all supported. Other vendors cut support off after the transition from FC to SAS.

Will we support those older shelves forever? No, that’s impossible, but at least we give our customers a lot of leeway and let them stretch their hardware investments significantly longer than any other major storage vendor I can think of.

Think long term

I encourage customers to always think long term. Try to stop thinking in 3-year increments. Start thinking of other ways you can stretch your investment, other ways to deploy older gear while still keeping it interoperable with newer hardware.

And start thinking about what will happen to your investment once newer gear is released.

D

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What is hard disk short stroking?

This is going to be a short post, to atone for my past sins of overly long posts but mostly because I want to eat dinner.

On storage systems with spinning disks, a favorite method for getting more performance is short-stroking the disk.

It’s a weird term but firmly based on science. Some storage vendors even made a big deal about being able to place data on certain parts of the disk, geometrically speaking.

Consider the relationship between angular and linear velocity first:

Linearvsangular

 

 

 

 

 

 

 

 

 

Assuming something round that rotates at a constant speed (say, 15 thousand revolutions per minute), the angular speed is constant.

The linear speed, on the other hand, increases the further you get away from the center of rotation.

Which means, the part furthest away from the center has the highest linear speed.

Now imagine a hard disk, and let’s say you want to measure its performance for some sort of random workload demanding low latency.

What if you could put all the data of your benchmark at the very outer edge of the disk?

You would get several benefits:

  1. The data would enjoy the highest linear speed and
  2. The disk tracks at the outer edge store more data, further increasing speeds, plus
  3. The disk heads would only have to move a small amount to get to all the data (the short-stroking part). This leads to much reduced seek times, which is highly beneficial for most workloads.

I whipped this up to explain it pictorially:

Short stroking

 

Using a lot of data in a benchmark would not be enough to avoid short-stroking. One would also need to ensure that the access pattern touches the entire disk surface.

This is why NetApp always randomizes data placement for the write-intensive SPC-1 benchmark, to ensure we are not accused of short-stroking, no matter how much data is used in the benchmark.

Hope this clears it up.

If you are participating at any vendor proof-of-concept involving performance – I advise you to consider the implications of short-stroking. Caching, too, but I feel that has been tackled sufficiently.

D

NetApp delivers 2TB/s performance to giant supercomputer for big data

(Edited: My bad, it was 2TB/s, up from 1.3TB/s, the solution has been getting bigger and upgraded, plus the post talks about the E5400, the newer E5600 is much faster).

What do you do when you need so much I/O performance that no one single storage system can deliver it, no matter how large?

To be specific: What if you needed to transfer data at over 1TB per second? (or 2TB/s, as it eventually turned out to be)?

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 2TB/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 2TB/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… 🙂 (Update: the newer E5600 can go up to 12GB/s in 2U with SSDs!)

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:

 

Lustre Scaled Cluster

 

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: 1.3TB/s sustained performance was demonstrated to the NetApp block devices. Work is ongoing to finalize the testing with the complete Lustre environment. 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

 

 

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NetApp posts world-record SPEC SFS2008 NFS benchmark result

Just as NetApp dominated the older version of the SPEC SFS97_R1 NFS benchmark back in May of 2006 (and was unsurpassed in that benchmark with 1 million SFS operations per second), the time has come to once again dominate the current version, SPEC SFS2008 NFS.

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-pricelist.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.

EMC NetApp Difference
Cost (approx. USD List) 11,800,000 6,280,000 NetApp is almost half the cost while offering much higher performance
SPEC SFS2008 NFS operations per second 1,112,705 1,512,784 NetApp is over 35% faster, while using potentially better RAID protection
Average Latency (ORT) 2.54 1.53 NetApp offers almost 40% better average latency without using costly SSDs, and is usable for challenging random workloads like DBs, VMs etc.
Space (TB) 864 (out of which 128889GB was used in the test) 574 (out of which 176176GB was used in the test) Isilon offers about 50% more usable space (coming from a lot more drives, 28% more raw space and potentially less RAID protection – N+2 results from Isilon would be different)
$/SPEC SFS2008 NFS operation 10.6 4.15 Netapp is less than half the cost per SPEC SFS2008 NFS operation
$/TB 13,657 10,940 NetApp is about 20% less expensive than EMC per usable TB
RAID Per-file protection. Files < 128K are at least mirrored. Files over 128K are at a 13+1 level protection in this specific test. RAID-DP Ask EMC what 13+1 protection means in an Isilon cluster (I believe 1 node can be completely gone but what about simultaneous drive failures that contain the sameprotected file?)NetApp RAID-DP is mathematically analogous to RAID6 and has a parity drive penalty of 2 drives every 16-20 drives.
Boxes needed to accomplish result 140 nodes, 3,360 drives (incl. 25TB of SSDs for cache), 1,120 CPU cores, 6.7TB RAM. 24 unified controllers, 1,728 drives, 12.2TB Flash Cache, 192 CPU cores, 1.2TB RAM. NetApp is far more powerful per node, and achieves higher performance with a lotless drives, CPUs, RAM and cache.In addition, NetApp can be used for all protocols (FC, iSCSI, NFS, CIFS) and all connectivity methods (FC 4/8Gb, Ethernet 1/10Gb, FCoE).

 

Notice the response time charts:

IsilonVs6240response

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.

 

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NetApp vs EMC usability report: malice, stupidity or both?

Most are familiar with Hanlon’s Razor:

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

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