>> From theCube Studios in Palo Alto and Boston,
bringing you data-driven insights from theCUBE and ETR,
this is Breaking Analysis with Dave Vellante.
>> Slowing cloud growth has led some
to the conclusion that repatriation of workloads is a factor
in suppressing cloud spending.
While we've been skeptical about repatriation
as a broad-based movement, anecdotal evidence suggests
that it is happening in certain situations.
While we still don't see repatriation broadly
in the numbers, certain examples have caught our attention.
In addition,
the impact of AI raises some interesting questions
about where infrastructure should be
and will be physically located,
and causes us to revisit our premise
that repatriation is an isolated and negligible trend.
Hello and welcome to this week's Wikibon Cube Insights,
powered by ETR.
In this Breaking Analysis, we look at a number of sources,
including the experiences of 37signals,
which has documented its departure from public clouds.
We'll also examine the relationship
between repatriation and SRE ops capabilities.
And as always,
we'll look at survey data from our partners at ETR
and some recent FinOps data published by Vega Cloud.
Several credible sources have published
on this repatriation topic.
On the bottom left here,
IDC published a report in 2018 that said
over the next two years that the respondents expected 50%
of their public cloud applications to repatriate.
That is an astoundingly large figure.
Now this study was done
by Michelle Bailey and Matt Eastwood.
Two highly respected, incredible analysts.
I know them both personally and well.
And from what I can tell, this was not a sponsored study.
But this was a very surprising figure.
Now, of course, the most discussed report was,
and continues to be, the post from Sarah Wong
and Martin Casado of Andreesen,
which posited that cloud expenses
would become an increasingly large component
of cost of goods sold
for cloud native SaaS companies at scale.
And would become so onerous as to chew up its profits
and either force repatriation
or a large discount concession from cloud providers.
The authors used a Dropbox case study
as an example of the potential savings from repatriation,
where the company saved $75 million
by moving infrastructure back on-prem.
Now you'll find some evidence of this large cogs conundrum
in Snowflake's 10K.
In the most recent March 2023 filing,
you'll find a note that says, quote,
"in January 2023, we amended one
of our third party cloud infrastructure agreements,"
presumably AWS, "effective February 1st, 2023.
Under the amended agreement
we have committed to spend an aggregate
of at least 2.5 billion
from fiscal '24 to fiscal '28
on cloud infrastructure services."
And they're obligated, it said,
to pay any difference between the commitment
and what they used during that term,
so that sounds pretty onerous, right?
However, as you read on it says, quote,
"the remaining non-cancelable purchase commitments
under the agreement prior to the January 2023 amendment,
the aggregate amount of which was 732 million
as of January 31st, 2023,
is not reflected in the table above
as the company is no longer required
to fulfill such commitments."
So two points, that we've made before
and are going to reiterate here.
The second statement that Snowflake made
and that I just shared with you,
is an indication that Snowflake
has renegotiated its contract with AWS.
Again, presumably AWS,
and retired $732 million
from its previously committed spend.
Ostensibly to get a larger discount.
So, so far the quid pro quo between Snowflake
and AWS has been, and it's same with all their customers,
you buy more and we'll give you a break,
so it doesn't kill your cogs in the case
of a software company and you know, customer expense,
you know, from a customer standpoint.
Not that Snowflake's not a customer,
but a, you know, conventional customer.
And this is likely going to continue indefinitely.
Amazon's not likely to lose a customer
to repatriation on balance.
Now the second point relates to Dropbox.
Dropbox is kind of a bogus example
because you cannot build a third party storage service
on top of S3 and make money.
All you got to do is talk to David Friend,
he's the CEO of Wasabi.
Or Gleb Budman, he's the founder and CEO of Back Blaze,
the two storage companies, and they will confirm this,
S3 or storage service third party
on top of S3 can't make money.
So while it might make some sense to do some things on-prem,
such as what Zscaler or CrowdStrike have done
as was reported by Wong and Casado,
so far repatriation from SaaS companies like Datadog
and Snowflake has not been a factor.
But let's not call it game over for cloud just yet.
Lori MacVittie put out an interesting post late last year,
describing the relationship between site reliability,
engineering skills, SRE, and cloud repatriation.
We're showing this here, the curious connection
between cloud repatriation and SRE ops.
Her point was not that SRE causes repatriation,
rather that SRE skills make it easier for companies
to operate on-prem infrastructure
using a cloud operating model.
She cited an F5 report that was really interesting.
It showed a significant jump from 2021 to 2022
and customers repatriating apps.
And she asked the right question,
i.e., it's not whether or not repatriation happens,
we know it does, the question is,
what percentage of workloads are actually moving back?
Now it doesn't appear to be 50%
as the IDC study suggested based on the data we have,
but our point is that many more customers today
have SRE ops capabilities
and are in a much better position to repatriate,
if there is a business case.
Which brings us to the 37signals case study.
David Heinemeier Hansson is the co-founder of 37signals,
he is the developer of Rails,
and it's a company that I've long admired
and his products like Basecamp that I've loved.
He's published a couple of posts
on their departure from the cloud.
And he used this term, "sovereign cloud."
You could see we put here sovereign cloud in the upper left,
"why we're leaving the cloud,"
and he's put this term out as an alternative
to private cloud or on-prem.
Now, VMware has used this term for years,
I think going back maybe even before 2019.
And our colleague David Nicholson,
he loves this term as well, he basically says,
"look, it's all IT," and he's implying
that the off-prem and the on-prem worlds are converging
in some type of equilibrium,
which is a really interesting point.
And that's essentially what 37signals is saying.
A main point that he made is, he being David,
a main point he made is renting infrastructure
for a mid-size firm, like 37signals,
is more expensive now than when they were starting out
with new products like, hey, in the cloud.
The other key point is what Lori MacVittie was saying.
The skills overlap between what it takes to run software
in the cloud versus on-prem is like 80 to 90% correlated.
With some differences, of course.
First, you don't need ThinOps and forensic accounting
to understand your cloud bills,
and second, you have to replace failed hardware like disks.
And he said, "these differences are minor
and easier than learning Kubernetes," haha.
Here's a picture of the 37signal's sovereign cloud,
some nice shrink wrapped boxes on a pallet,
and you can see the infrastructure they bought on the right.
Now look, these guys are, they're geeking out
over their Dell R7625s.
They got two AMD Epic 9454 CPUs running it,
two, three quarter gigahertz
with the 48 cores and 96 threads.
So it's going to give them 4,000 virtual CPUs on-prem.
So, and they got seven terabytes of RAM,
they got 384 terabytes of Gen 4 NVMe storage
and then Gen 5 is coming,
that's going to go to 13 gigabytes a second soon,
so yeah, cool, sovereign cloud.
So why isn't everyone doing this?
Well, our friend over at Platformonomics,
Charles Fitzgerald,
created what he calls the cloud repatriation index.
In this chart, he plots the growth rates
of the big three cloud players against those
of Equinix and Digital Realty, the big colos.
And in the upper right,
we show Fitz's repatriation index,
and the way he calculates that,
he takes the revenue of the two leading colos
and divides by AWS's cloud revenue.
And you can see the steady downward trajectory
of the cloud guys.
And you'll notice in the chart below,
sorry, the steady downward trajectory
of the cloud repatriation index in the upper right,
and you can see it's kind of flattening there,
and we put in a little question mark, come back to that,
but you'll notice in the chart below,
the growth rates based on 2023 projections,
they're kind of converging between AWS in particular,
and both Equinix and Digital Realty,
which their growth rates are actually popping up
into the low teens.
So that flattening repatriation curve
in the upper right is probably going to uptick,
so we're going to keep an eye on that.
Now let's bring in some ETR survey data
and take a look at whether there's any evidence there
that repatriation is happening to a large degree.
In this recent ETR drilldown,
ETR asked 400 respondents
that said they were significantly cutting costs
how they were doing it.
And you can see here, they're delaying projects,
they're cutting staff, they're reducing consulting spend,
they're holding off on hardware purchases,
they're consolidating redundant vendors.
By the way, consolidating redundant vendors,
that was number one last quarter
and had been in previous quarters.
And then reducing excess cloud resources.
So reducing excess cloud resources
might include some repatriation.
We asked ETR to look into this
and dig into any of the open-ended comments,
and repatriation wasn't specifically mentioned.
That doesn't mean it's not happening in pockets,
it just doesn't appear to be, you know,
thing one as Stu Miniman likes to say.
Now, we recently received an inbound from Vega Cloud,
a firm specializing in cutting cloud costs,
and they just ran a survey on FinOps.
And this chart shows for customers concerned about costs,
they drilled down and said,
"well, what are you doing about it?"
And like the ETR data,
we see staff cuts, we see project delays,
we see, you know, vendor alternatives,
you know, kind of like consolidating vendors maybe,
but no specific evidence of repatriation as a callout.
And just as an aside,
what was really interesting was Vega asked respondents
which line items on the cloud bill
were giving them the most heartburn
from overages relative to expectations?
I would've thought compute and bandwidth
would be the big culprits because,
but you know, that's where the spending is, right?
But look at database, it's number one.
I wonder how many Snowflake customers were in this sample.
We asked because Snowflake is very popular
and charges customers for consumption as a bundle.
So they don't necessarily know they're spending on,
whether it's on compute or storage
and at least, that's the way I understand it.
They didn't have that level of granularity.
So the Snowflake customer doesn't see that granularity
of like I say, storage or compute,
they just see a consumption bill.
We couldn't get that level of,
they didn't know, Vega didn't know,
whether or not there were Snowflake customers
in there or not, so we'll leave that for now.
But the last bit of ETR data that we want to look at is
from a survey on cloud adoption relative to on-prem
and the preponderance of hybrid cloud.
Now we've shared this before,
but we'll take a little different look
at the data right now.
It's from another ETR drilldown from late last year,
which breaks down the percent usage
between public and private cloud.
And the key points are one,
61% of respondents cite the majority
of their usage is on-prem today.
So that means 40% have most
of their work being done in the cloud.
Which makes you question that claim
that 90% of all workloads are on-prem today.
That 61% figure, that drops to 42% in two years.
But the real callout stat to us,
that we've highlighted here in red,
is that only 14% of customers today say they're all in
on the public cloud and that is expected to remain flat
in this sample over the next two years.
So first, if there's repatriation happening
at a large scale, it's not on these numbers.
And two, the picture is very clearly hybrid
as the dominant model for this foreseeable future.
So the other question we pondered is
how will AI impact this picture?
'Cause, it's all we talk about, is AI these days.
Well, first of all, foundation models like GPT,
that's a tide that will lift all compute boats.
It was interesting to see the stock market's tepid reaction
to AMD's quarter.
They beat estimates despite the challenging environment
and soft PC market and the stock dropped.
But when it was announced
that Microsoft is helping finance AMD's AI chips,
the stock popped.
And while a lot of that is hype around ChatGPT,
it's also recognition that we're entering a new era
where AI is going to drive massive demand
for data center hardware.
Which begs the question,
where's that hardware going to live?
In the cloud or on-prem?
So we ask, where are OpenAI's servers?
Well, we know they're in Azure
with the deal they have with Microsoft,
but they're evidently also in Ohio on a supercomputer
where the training is done.
I actually asked ChatGPT and got a vague answer
but when you look at AI,
there's clearly an affinity between it
and high performance computing.
And many of those HPC workloads will land on-prem.
For example, if you're a university
and you have a supercomputing center,
you're going to want to show that off to people and donors
and versus having, you know,
hidden resources in a remote cloud.
And then you know,
renting infrastructure is economically viable
for bursty use cases and unpredictable swings in demand,
but like the cloud versus on-prem argument,
similar arguments apply here.
Especially with large scale implementations.
I mean, I'm just sort of picking a low watermark,
but think about like 50,000 cores or up.
Some supercomputers have millions of cores.
So economically, it's got to be more viable
to sort of keep 'em in your own data center.
There are also legitimate concerns about leaking IP.
We recently saw Samsung Electronics ban ChatGPT,
after an employee mistakenly put,
or I guess, unknowingly put proprietary code
into the software.
He did it on purpose but he didn't know
that he was giving his IP to, or her IP, to ChatGPT.
This makes AWS's announcement of Bedrock quite interesting.
AWS is not building a free service like Google Search,
or Bing, or OpenAI,
rather it's offering large language model services
and tools so you can build your own.
Presumably making IP leakage less likely.
But then of course, there's always Alexa,
so we'll see what happens with that.
And in fairness to OpenAI, CEO Sam Altman would tell you
that they don't want IP that shouldn't be in the model.
Rather they only want folks' IP who want to be in ChatGPT.
As an example,
at one time I was just working, you know, asking Chat,
what I was doing was ego-GPTing, I guess I'll call it,
just to see what it said about me,
and ChatGPT said I worked for the Wall Street Journal
at one point, which obviously I want to correct it.
It was quite a nice compliment but I wanted that corrected.
So oftentimes, you want your data in GPT models.
And the last point is,
as Matt Baker said in our LinkedIn post last week,
"this is batting practice for AI.
The game will be played at the edge
and in the world around us.
Adaptation and inferencing do not favor centralized models,
e.g., public cloud."
Now, while Matt is biased,
we agree, we think he's right on this front.
AI inferencing is going to explode at the edge.
It's not going to happen in today's public cloud.
Now, how the public cloud players approach this is going
to be very interesting.
They got autonomous vehicles,
they got robots, they have satellites,
and they have other edge infrastructure.
So yes, we're smacking GPT balls out of the park
before the first inning has even started.
So let the games begin and we'll see what happens.
Okay, that's it for now.
Many thanks to Alex Morrison,
who was on production with Ken Schiffman.
Alex also manages our podcast,
Kristen Martin and Cheryl Knight help get the word out
on social media and in our newsletters.
And Rob Hof is our editor-in-chief over at siliconangle.com.
He does some great work for us, thank you.
Remember, all these episodes are available as podcast.
Wherever you listen, just search Breaking Analysis podcast.
Published each week on wikibon.com and siliconangle.com.
I think we're up to episode 177 now, so check that out.
And you can also check out the cube.net
for all the video action on theCUBE.
Or you can email me directly if you want to get in touch,
david.vellante@siliconangle.com or DM me, @dvellante.
You can comment on our LinkedIn post,
pitch us if you got some good ideas.
You know, we'll listen, if not, don't take offense,
we get a lot of them, but keep trying.
And please do check out etr.ai,
they've got the best survey data
in the enterprise tech business.
This is Dave Vellante for theCube Insights powered by ETR.
Thanks for watching everybody
and we'll see you next time on Breaking Analysis.
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