When dealing in storage space/capacity numbers, there are generally two ways of representing the numbers – base 2 (binary) and base 10 (decimal/metric). Originally, space was all done in base 2. But, over the years, decimal has crept in to the storage representation – probably due to easier math. After all, it’s easier/quicker to multiply by 1000 than by 1024.

What that has done, however, is introduce some confusion, as not all storage vendors follow the same standards when reporting capacity. Seagate has an excellent knowledge base article on this here:

Gebi, Tebi, Pebi

In an attempt to alleviate the confusion, a new measurement name was created that isn’t widely adopted. Most people still refer to everything as MB, GB, TB, etc. But that’s all base 10. Base 2 uses a little “i” in the abbreviation, so we get MiB, GiB, TiB, etc. That is intended to represent a capacity measured in 1024 vs. 1000. It gets even more fun when you consider the “b” vs. “B” to mean byte versus bit, but I digress.

This handy table on the wiki entry for Tebibyte shows how the math works for decimal vs. binary in storage terms.


What happens when you use decimal vs. binary to measure storage? Well, it can mean that what you thought was 316GB of storage is really only 288GiB – depending on how the vendor has decided to display it.

What does this mean for ONTAP?

So, some vendors use decimal because it reports more space available. Microsoft actually has a statement on this here:

Although the International Electronic Commission established the term kibibyte for 1024 bytes, with the abbreviation KiB, Windows Explorer continues to use the abbreviation KB. Why doesn’t Explorer get with the program?

Because nobody else is on the program either.

If you look around you, you’ll find that nobody (to within experimental error) uses the terms kibibyte and KiB. When you buy computer memory, the amount is specified in megabytes and gigabytes, not mebibytes and gibibytes. The storage capacity printed on your blank CD is indicated in megabytes. Every document on the Internet (to within experimental error) which talks about memory and storage uses the terms kilobyte/KB, megabyte/MB, gigabyte/GB, etc. You have to go out of your way to find people who use the terms kibibyte/KiB, mebibyte/MiB, gibibyte/GiB, etc.

In other words, the entire computing industry has ignored the guidance of the IEC.

NetApp ONTAP uses binary because it’s closer to what is accurate with regards to how computers operate. However, ONTAP, while showing the correct *numbers* (in decimal) doesn’t show the correct *units*. ONTAP shows, by default, GB, TB, etc.  Bug 1078123 covers this.



For example, my Tech ONTAP Podcast FlexGroup volume is 10TB:

cluster::*> vol show -fields size -vserver DEMO -volume Tech_ONTAP
vserver volume     size
------- ---------- ----


cluster::*> df /vol/Tech_ONTAP
Filesystem       kbytes      used     avail       capacity Mounted on Vserver
/vol/Tech_ONTAP/ 10200547328 58865160
                                      10141682168       0% /techontap DEMO
                 536870912   466168   536404744         0% /techontap/.snapshot DEMO

If we use TB to mean base 10, then 10200547328 + 536870912 (10737418240) kbytes is actually 10.737TB! If we use base 2, then yes, it’s 10TB.

There is a way to change the unit displayed to “raw,” but that basically just shows the giant number you’d see with “df.” If you’re interested:

cluster::> set -units
 auto raw B KB MB GB TB PB

Why should you care?

Ultimately, you probably don’t care. But it’s good to know when you’re trying to figure out where that extra X number of GB went, as well as how much capacity you’re buying up front. And it’s a good idea to make it a best practice to ask *every* vendor how they measure capacity, so they don’t try to shortchange you.


Storage Efficiency Transparency: Powered by Data

Recently, NetApp has started to publicly display storage efficiency ratios on AFF systems on the product pages. You can see for yourself here.

The initial results look pretty good:


That’s over 4:1 average capacity savings on our AFF systems, which is possible due to storage efficiency features that are currently only available on NetApp AFF platforms. It also falls in line with NetApp’s All-Flash Guarantee program.

Storage efficiencies add great value to AFF systems by way of allowing more data to be stored in ONTAP systems, which reduces the $/GB cost of the storage system. So even though you may pay more for SSD drives, you get that money back as you add data to the storage because you need less of a footprint to store it, less power and cooling and better overall performance.

I like to think of storage efficiency value in comparison to this guy:

Where does that ratio come from?

The numbers publicly shown on the NetApp site aren’t pulled out of thin air; they’re updated regularly from real-world data captures of capacity savings from NetApp’s Active IQ back end. The ratio factors in the same standard values most of NetApp’s competitors use (provided they have those features):

  • Deduplication
  • Compression
  • Compaction
  • Clones

They left out snapshots from the main calculation, but do include what that ratio looks like on the same page (spoiler alert: it’s an insane 22:1).

For more info on Active IQ, check out the following podcast:

NetApp is using data mining, machine learning and analytics more and more to enhance how we deliver information.

Check the NetApp site periodically and see how the numbers adjust based on real data!

Case study: Using OSI methodology to troubleshoot NAS

Recently, I installed some 10GB cards into an AFF8040 so I could run some FlexGroup performance tests (stay tuned for that). I was able to install the cards myself, but to get them connected to a network here at NetApp’s internal labs, you have to file a ticket. This should sound familiar to many people, as this is how real-world IT works.

So I filed the ticket and eventually, the cards were connected. However, just like in real-world IT, the network team has no idea what the storage team (me) has configured, and the storage team (me) has no idea how the network team has things configured. So we had to troubleshoot a bit to get the cards to ping correctly. Turns out, they had a vlan tag on the ports that weren’t needed. Removed those and fixed the port channel and cool! We now had two 10GB LACP interfaces on a 2 node cluster!

Not so fast…

Turns out, ping is a great test for basic connectivity. But it’s awful for checking if stuff *actually works.* In this case, I could ping via the 10GB interfaces and even mount via NFSv3 and list directories, etc. But those are lightweight metadata operations.

Whenever I tried a heavier operation like a READ, WRITE or READDIRPLUS (incidentally, tab completion for a path when typing a command on an NFS mount? READDIRPLUS call), the client would hang indefinitely. When I would CTL + C out of the command, the process would sometimes also hang. And subsequent operations, including the GETATTR, LOOKUP, etc operations would also hang.

So, now I had a robust network that couldn’t even perform tab completions.

Narrowing down the issue

I like to start with a packet trace, as that gives me a hint where to focus my efforts. In this issue, I started a packet capture on both the client ( and the cluster ( In the traces, I saw some duplicate ACKs, as well as packets being sent but not replied to:


In the corresponding filer trace, I saw the READDIRPLUS call come in and get replied to, and then re-transmitted a bunch of times. But, as the trace above shows, the client never receives it.


That means the filer is doing what it’s supposed to. The client is doing what it’s supposed to. But the network is blocking or dropping the packet for some reason.

When troubleshooting any issue, you have to start with a few basic steps (even though I like to start with the more complicated packet capture).

For instance…

What changed?

Well, this one was easy – I had added an entire new network into the mix. End to end. My previous ports were 1GB and worked fine. This was 10GB infrastructure, with LACP and jumbo frames. And I had no control over that network. Thus, I was left with client and server troubleshooting for now. I didn’t want to file another ticket before I had done my due diligence, in case I had done something stupid (totally within the realm of possibility, naturally).

So where did I go from there?

Start at layers 1, 2 and 3

The OSI model is something I used to take for granted as something interviewers asked because it seemed like a good question to stump people on. However, over the course of the last 10 years, I’ve come to realize it’s useful. What I was troubleshooting was NFS, which is all the way at layer 7 (the application layer).


So why start at layers 1-3? Why not start where my problem is?

Because with years of experience, you learn that the issue is rarely at the layer you’re seeing the issue manifest. It’s almost always farther down the stack. Where do you think the “Is it plugged in?” joke comes from?


Layer 1 means, essentially, is it plugged in? In this case, yes, it was. But it also means “are we seeing errors on the interfaces that are plugged in?” In ONTAP, you can see that with this command:

ontap9-tme-8040::*> node run * ifstat e2a
Node: ontap9-tme-8040-01

-- interface e2a (8 days, 23 hours, 14 minutes, 30 seconds) --

 Frames/second: 1 | Bytes/second: 30 | Errors/minute: 0
 Discards/minute: 0 | Total frames: 84295 | Total bytes: 7114k
 Total errors: 0 | Total discards: 0 | Multi/broadcast: 0
 No buffers: 0 | Non-primary u/c: 0 | L2 terminate: 9709
 Tag drop: 0 | Vlan tag drop: 0 | Vlan untag drop: 0
 Vlan forwards: 0 | CRC errors: 0 | Runt frames: 0
 Fragment: 0 | Long frames: 0 | Jabber: 0
 Error symbol: 0 | Illegal symbol: 0 | Bus overruns: 0
 Queue drop: 0 | Xon: 0 | Xoff: 0
 Jumbo: 0 | JMBuf RxFrames: 0 | JMBuf DrvCopy: 0
 Frames/second: 82676 | Bytes/second: 33299k | Errors/minute: 0
 Discards/minute: 0 | Total frames: 270m | Total bytes: 1080g
 Total errors: 0 | Total discards: 0 | Multi/broadcast: 4496
 Queue overflows: 0 | No buffers: 0 | Xon: 0
 Xoff: 0 | Jumbo: 13 | TSO non-TCP drop: 0
 Split hdr drop: 0 | Pktlen: 0 | Timeout: 0
 Timeout1: 0 | Stray Cluster Pk: 0
 Rx MBuf Sz: Large (3k)
 Current state: up | Up to downs: 22 | Speed: 10000m
 Duplex: full | Flowcontrol: none

In this case, the interface is pretty clean. No errors, no “no buffers,” no CRC errors, etc. I can also see that the ports are “up.” The up to downs are high, but that’s because I’ve been adding/removing this port from the ifgrp multiple times, which leads me to the next step…

Layer 2/3

Layer 2 includes the LACP/port channel, as well as the MTU settings.  Layer 3 can also include pings and some switches, as well as routing.

Since the port channel was a new change, I made sure that the networking team verified that the port channel was configured properly, with the correct ports added to the channel. I also made sure that the MTU was 9216 on the switch ports, as well as the ports on the client and storage. Those all checked out.

However, that doesn’t mean we’re done with layer 2; remember, basic pings worked fine, but those operate at 1500 MTU. That means we’re not actually testing jumbo frames here. The issue with the client was that any NFS operation that was not metadata was never making it back to the client; that suggests a network issue somewhere.

I didn’t mention before, but this cluster also has a properly working 1GB network on 1500 MTU on  the same subnet, so that told me routing was likely not an issue. And because the client was able to send the information just fine and had the 10GB established for a while, the issue likely wasn’t on the network segment the client was connected to. The problem resided somewhere between the filer 10GB ports and the new switch the ports were connected to. (Remember… what changed?)

Jumbo frames

From my experience with troubleshooting and general IT knowledge, I knew that for jumbo frames to work properly, they had to be configured up and down the entire stack of the network. I knew the client was configured for jumbo frames properly because it was a known entity that had been chugging along just fine. I also knew that the filer had jumbo frames enabled because I had control over those ports.

What I wasn’t sure of was if the switch had jumbo frames configured for the entire stack. I knew the switch ports were fine, but what about the switch uplinks?

Luckily, ping can tell us. Did you know you could ping using MTU sizes?

Pinging MTU in Windows

To ping using a packet size in Windows, use:

ping -f -l [size] [address]

-f means “don’t fragment the packet.” That means, if I am sending a jumbo frame, don’t break it up into pieces to fit. If you ping using -f and a large MTU, the MTU size needs to be able to squeeze into the network MTU size. If it can’t, you’ll see this:

C:\>ping -f -l 9000

Pinging with 9000 bytes of data:
Packet needs to be fragmented but DF set.
Packet needs to be fragmented but DF set.
Packet needs to be fragmented but DF set.
Packet needs to be fragmented but DF set.

Ping statistics for
 Packets: Sent = 4, Received = 0, Lost = 4 (100% loss)

Then, try pinging with only -l (which specifies the packet size). If that fails, you have a good idea that your issue is MTU size. Note: My windows client didn’t have jumbo frames enabled, so I didn’t bother trying to use it to troubleshoot using it.

Pinging MTU in Linux

To ping using a packet size in Linux, use:

ping [-M do] [-s <packet size>] [host]

-f, again, means “don’t fragment the packet.” That means, if I am sending a jumbo frame, don’t break it up into pieces to fit. If you ping using -f and a large MTU, the MTU size needs to be able to squeeze into the network MTU size.

-M <hint>: Select Path MTU Discovery strategy.

<hint> may be either “do” (prohibit fragmentation, even local one), “want” (do PMTU discovery, fragment locally when packet size is large), or “dont” (do not set DF flag).

Keep in mind that the MTU size you specify won’t be *exactly* 9000; there’s some overhead involved. In the case of Linux, we’re dealing with about 28 bytes. So an MTU of 9000 will actually come across as 9028 and complain about the packet being too long:

# ping -M do -s 9000
PING ( 9000(9028) bytes of data.
ping: local error: Message too long, mtu=9000

Instead, ping jumbo frames using 9000 – 28 = 8972:

# ping -M do -s 8972
PING ( 8972(9000) bytes of data.
--- ping statistics ---
2 packets transmitted, 0 received, 100% packet loss, time 1454ms

In this case, I lost 100% of my packets. Now, let’s ping using 1500 – 28 = 1472:

# ping -M do -s 1472
PING ( 1472(1500) bytes of data.
1480 bytes from icmp_seq=1 ttl=249 time=0.778 ms
--- ping statistics ---
1 packets transmitted, 1 received, 0% packet loss, time 590ms
rtt min/avg/max/mdev = 0.778/0.778/0.778/0.000 ms

All good! Just to make sure, I pinged a known working client that has jumbo frames enabled end to end:

# ping -M do -s 8972
PING ( 8972(9000) bytes of data.
8980 bytes from icmp_seq=1 ttl=64 time=1.12 ms
8980 bytes from icmp_seq=2 ttl=64 time=0.158 ms
--- ping statistics ---
2 packets transmitted, 2 received, 0% packet loss, time 1182ms
rtt min/avg/max/mdev = 0.158/0.639/1.121/0.482 ms

Looks like I have data pointing to jumbo frame configuration as my issue. And if you’ve ever dealt with a networking team, you’d better bring data. 🙂


Resolving the issue

The network team confirmed that the switch uplink was indeed not set to support jumbo frames. The change was going to take a bit of time, so rather than wait until then, I switched my ports to 1500 in the interim and everything was happy again. Once the jumbo frames get enabled on the cluster’s network segment, I can re-enable them on the cluster.

Where else can this issue crop up?

MTU mismatch is a colossal PITA. It’s hard to remember to look for it and hard to diagnose, especially if you don’t have access to all of the infrastructure.

In ONTAP, specifically, I’ve seen MTU mismatch break:

  • CIFS setup/performance
  • NFS operations
  • SnapMirror replication

Pretty much anything you do over a network can be affected, so if you run into a problem all the way up at the application layer, remember the OSI model and start with the following:

  • Check layers 1-3
  • Ask yourself “what changed?”
  • Compare against working configurations, if possible

Behind the Scenes: Episode 76 – Customer Chat with Yahoo’s Jeff Mohler

Welcome to the Episode 76, part of the continuing series called “Behind the Scenes of the NetApp Tech ONTAP Podcast.”


This week on the podcast, we bring in a NetApp customer for a candid chat about how they use NetApp’s portfolio in their environment and what sort of challenges they face in day to day operations. Join us as we talk with Jeff Mohler (, a principal Global Storage Architect at Yahoo and get a feel for how an enterprise customer manages thousands of NetApp systems.

If you’re a NetApp customer and you’re interested in appearing on the podcast to chat about how you’re using NetApp, be sure to shoot us an email to!

Finding the Podcast

The podcast is all finished and up for listening. You can find it on iTunes or SoundCloud or by going to

Also, if you don’t like using iTunes or SoundCloud, we just added the podcast to Stitcher.

I also recently got asked how to leverage RSS for the podcast. You can do that here:

You can listen here:

Behind the Scenes: Episode 61 – Security and Storage

Welcome to the Episode 61, part of the continuing series called “Behind the Scenes of the NetApp Tech ONTAP Podcast.”


This week on the podcast, we discuss security in storage systems with the new security TME Andrae Middleton and NetApp A-Team member Jarett Kulm (@JK47theweapon) of High Availability, Inc. We cover security at rest, in-flight, methodologies, ransomware and much more!

Also be sure to check out our podcast on NetApp Volume Encryption.

Finding the Podcast

The podcast is all finished and up for listening. You can find it on iTunes or SoundCloud or by going to

Also, if you don’t like using iTunes or SoundCloud, we just added the podcast to Stitcher.

I also recently got asked how to leverage RSS for the podcast. You can do that here:

You can listen here:

TECH::Zynga, Innovation and the Storage Startup Bubble

Full disclosure: I work for NetApp (so, yes, I am biased in some capacity). But this post is not in any way related to the opinion of NetApp.

The recent history of the IT economy in the past 20 years or so has been pockmarked with scars of bubbles that have burst in grand fashion. The first one I remember was the bubble of 2000. This was back when all of these internet-based startups were getting crazy amounts of VC cash and spending it like it was going to disappear the next day. That’s when you started seeing “corporate culture” taking priority over things like “making a profit.”

Stories abound of Gatsby-esque “dot com parties” – companies buying yachts for corporate functions, expensive A-list music acts and expensive Super Bowl ads from infamous companies like


Then, the bubble burst. Companies went under. The out of hand spending caught up with companies and we saw an economic downturn.

The Great Recession

The next bubble I remember was the housing and financial crisis in 2007-2008. That led to the “Great Recession,” which had reverberating effects on the IT industry. People lost jobs and companies slowed or stopped buying. Stocks absolutely tanked.

I remember these bubbles mostly because they both affected me. The dot com bubble affected me because it happened just as I graduated from college. Finding a job in IT was tough and when I did find one, it was far from lucrative.

The Great Recession affected me because it was right at the start of my NetApp career and I saw a lot of co-workers and colleagues move on to other places.

But this blog is not about economics. It’s about innovation…

The Storage Bubble and Innovation

I’m going to be purposely vague here and not name names. I don’t want to turn this into a pissing contest, and honestly, I can’t make criticisms of specific startups as I don’t have a full understanding of their offerings. It’s not fair to them and is intellectually dishonest. I just go by what I read in press releases and their marketing. This doesn’t apply to all storage startups, as there are definitely some real innovative products out there and some real good talent working at these companies. I have a lot of friends and ex co-workers at startups. But there is also a lot of redundancy disguised as innovation.

They call it a bubble because it is destined to burst.


What I’ve seen in the past few years is a huge increase in companies that are attempting to re-invent storage. Many of these companies were started by people who worked at the big storage companies like EMC, HP, NetApp, etc. Nearly all of them claim to be innovating in some manner that their bigger competitors are not.

The question is, what do they mean by innovation?

The basic definition of “innovation” is a new way of doing something. For me, I’d say that doing things a different way is fine, but it should be done better. For example, Tesla has innovated automobiles by creating an EV that people actually want. But how are startups innovating storage?

Some of them are coming from the angle of all-flash. Others are using hyper converged architecture. Some are doing hybrid arrays. Almost all of them are trying to incorporate scale out. And, right now, you can’t move without tripping over a new storage startup.

They’re bursting into the room like the this guy:


And like that guy, they’re bringing a whole lot of Kool-Aid with them.

But how many of them are truly innovating? Most of what is out there is already offered in some capacity by the bigger vendors the startups claim aren’t innovating any more. Is offering the same stuff in a different package innovation?

Not only that, as these “innovative” startups offer new releases, you are starting to see that the features they are adding are precisely the same things many of them had been preaching were legacy offerings in the first place. And as they grow, they start to become what they hate – legacy.

Matt Watts has written two fantastic posts covering these concepts:

When Purity is diluted by the Investment Innovation Challenge

A Legacy is something to be very proud of

Another one to check out is Gerald Coon’s “Why am I so hard on startups?


When I think about the notion of innovation, I think about what motivates it. I think it comes down to two things.

  1. The desire to invent and create something better
  2. The desire to make money

Some startups feel an awful lot like Zynga. If you’re not familiar with them, they’re a game company that basically took other game ideas and re-branded them as their own, with the “innovation” of implementing them on social media platforms like Facebook. Ever get a Mafia Wars or Farmville request? You can thank Zynga for that.

Not only do they take other game ideas as their own, they buy companies that do the same. Words with Friends, the Scrabble rip-off, is a prime example. Hasbro is a big company and probably did not see the opportunity in making a mobile app for their games. Another company did, stole the game idea and then Zynga bought them.

The innovation was presenting a new platform, but is that true innovation?

Does it matter? Zynga cashed in, partnered with Hasbro and Words with Friends remains insanely popular.

Consumers didn’t care. They got what they wanted – cheap, easy access games that they loved. Hasbro got what they wanted in the end – some one to push them to into a new space and keep making money off of their intellectual property. But it’s hard to call what Zynga is doing true innovation by doing something identical to someone else, but just slightly differently.

Are startups learning from past mistakes?

If we do not learn from our history, we are destined to repeat it.

As these startups grow and become more and more popular, they start to face a lot of the same challenges every growing company faces. Those big companies that they are targeting? Guess who they’re now hiring people from.

The people they’re hiring? Some are pretty good. But some might just be chasing the IPO cash out. That hurts the carefully constructed culture that made them successful and appealing to start with.

The culture? Some of it feels an awful lot like the same mistakes we saw with the dot com parties. Startups are burning through cash faster than they are making it. VC firms are opening the wallets left and right. Is it a mirage? Is it sustainable? How much work/life balance is being traded for the promise of stock options?

Don’t believe me? Go read some of the Glassdoor employee reviews of these companies. Keep in mind also that some companies’ HR departments encourage employees to write glowing reviews.

What startups are also starting to see is that growing is not easy. As your customer base grows, so do their demands. That agility you had as a startup begins to vanish as you start acquiring enterprise customers that require stability that you can’t get by spinning up a patch for your software every time you hit a bug. Being “disruptive” starts taking on more than one meaning (and not in a good way).

That innovation you tout disappears as 15 other “innovative” startups come out of stealth, selling the same ideas your company is selling. Zynga gets Zynga’d.

Oh, and those large legacy companies? They’ve noticed the market share you’ve stolen and the uninformed insults/FUD you hurled their way and they are PISSED.

They focus their lasers at you and intend to annihilate you.


Meanwhile, startups start looking towards IPO and have to open up the books to investors and the public. Which includes their competitors.

I don’t envy the startups, especially not the ones that aren’t as successful and innovative as they claim to be.

What happens from here?

The question, of course, is if we are really in a storage startup bubble. I think we are. There are too many offerings doing the same or similar things, which dilutes the market and often leads customers to just go back to what they were most comfortable with.

This is especially true when the story the startup is selling is not compelling enough to cause the admin to want to use a new solution that is relatively unproven. I’ve heard stories of startups that are burning through VC cash by essentially giving product away just to get their foot in the door. It’s a risky gamble and has paid off somewhat for these companies, as they get to reap the benefits of the “vendor lock-in” from other vendors they warned their customers about during the sales pitch. (See what they did there?)

I think the storage market is going to self-correct and adjust for growing trends. These startups will either fold, consolidate or get bought up. What was once cutting edge is already falling to legacy as new storage technology rolls out, such as Intel’s 3D Xpoint and Seagate’s 16TB SSD drives.

The bubble will burst, but hopefully, for everyone involved, it’s a gentle one.

TECH::Jurassic IT – Is NetApp a dinosaur?

Google “netapp dinosaur” and you get some… interesting articles.

You’ll find quotes like:

“a business in stagnation”

“obsessed with Data ONTAP”

“ONTAP showing its age”

I always find it funny when someone says a software company is overly obsessed with their own OS. I assume Apple is too obsessed with iOS, Microsoft too obsessed with Windows, etc.

But I digress…

Jurassic IT


Calling a company a dinosaur is essentially implying that company is doomed for extinction. It’s suggesting that the company is slow, plodding, unable to get out of its own way.

It’s also an AWFUL analogy, if you know your dinosaurs.

There are essentially two types of people that know dinosaurs better than anyone else: paleontologists and parents of small children.


I have a two year old son. So that makes me an expert*. 🙂

* On the internet, you can call yourself an expert at pretty much anything without repercussion.


Dinosaurs lived on the planet roughly 165 million years. Humans have lived on Earth for around 200,000 years. Data storage? Maybe 70-75 years? (Punchcards count!)

It’s a little silly for a human to mock how long dinosaurs lived on Earth, just like it’s silly for any storage startup to call NetApp a “dinosaur.”

As for extinction, the implication is that dinosaurs were so stupid and plodding, they offed themselves – and it’s supposed to be some sort of analogy to what NetApp is doing to themselves. However, that’s not at all the case with dinosaurs (nor NetApp).

For the entirety of those 165 million years, dinosaurs were at the top of the food chain. They evolved over the course of time to adjust and adapt to their environment. The general consensus from scientists is that a catastrophic world event took the dinosaurs out – an Ice Age, a meteor shower, Deccan traps… but it’s not like the dinosaurs decided that they weren’t going to change and avoid extinction.

Plus, let’s think a little more on extinction – dinosaurs aren’t really extinct, Their descendants are birds and reptiles. So the whole notion that a dinosaur is destined for extinction and that using it as a metaphor for a company is based on false pretense.

Slow and steady

Another implication of calling a company a dinosaur is that they are slow to innovate (evolve) and so big that they can’t get out of their own way. Which, in the world of dinosaurs, is more fallacy.

Sure, the brontosaurus was massive and slow.


But what about the velociraptor? Or the ornithomimids, which were the fastest dinos (and small) and ran faster than Usain Bolt in his prime?

There were definitely dinosaurs out there that were agile, fast and able to maneuver as their surroundings dictated.

Tiny brains?

The notion that dinosaurs were kind of stupid? Yeah, that’s accurate.

But implying that a company that’s been around nearly 30 years, contributing to new SNIA and IETF standards every year, filing hundreds of patents, evolving with products like All Flash FAS and adding value to the storage industry is somehow “stupid” is just intellectually dishonest.

NetApp is a dinosaur

When you think about it for awhile, the critics are right – NetApp is a dinosaur. A massive, fast, deadly, top of the food chain, evolving dinosaur. They face the same challenges the rest of the storage industry faces, just like Earth faced when whatever world event wiped out the original dinos.

And guess what? People kind of love dinosaurs.


Jurassic World is setting box office records (it surpassed Avengers 2 this weeked) and is showing us all just what dinosaurs can do. My son’s favorite animal on Old MacDonald’s farm is a stegosaurus. Yes, that’s ridiculous, but that’s kids for you.

I’ll take being called a dinosaur any day.