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[Music]
hello everyone welcome um to day five on
bits and boy stage it's so nice to see
all of you even though you look a bit
more tired than two days ago when I last
saw
you but um I hope we are all going to
look as sunny as this day when this talk
is over um speaking of a sunny day um
please take care too do you know drink
water yes and use sunscreen and uh be in
the shadow take breaks you know don't
just run from talk to talk take breaks
sit in the shade and um also look that
people around you are doing the
same um yes and if uh you have any
thoughts or comments you can also always
um post them on Mastodon using the hash
bits and Bo um Bo with a e
so and now I'm really happy that I can
announce our speaker Thomas Thomas uh is
mainly working with clouds and Cloud
security and when he was looking for
energy consumptions of data centers he
didn't find enough information so he
went looking for them and he's going to
present them to us today so give a warm
Applause and welcome to
thas thank you very
much so this is what I'm normally doing
kubernetes Cloud security and the
stuff uh but let's start so energy
consumption of data centers is
something which is not really well
published so the data center owner are
not necessarily publishing a lot of
numbers and you see there are a lot of
Articles and the best ones I have
presented here and uh this study here is
from
2020 so they show an energy forecast
this is which is exponentially growing
and always if you see something
exponentially growing you should be very
very careful and aware that something
could terribly go
wrong if you compare the data center
usage with the energy consumption of
entire countries you see all the data
centers are more or less in the range of
South Africa even comparable to the UK
or Indonesia so the if the data centers
would be a country you
see uh it's a bigger
country uh if you look into the German
numbers you see we are spending 16 tatt
hours on data
centers mostly the heat which is
produced by the CPUs
is not used
anymore there is no decarbonization
possible because it's just
heat and it is at the moment 3% of the
electric power
consumption and the dangerous part is uh
it's it has a annually growth of 6% this
means it will
double probably around every 12
years so if the data centers from now in
in the camp if you talk again it's a
camp in 12 years which which would be
2035 then the data centers have doubled
the energy consumption if this trend
continues for all of you who are not
familiar with exponential growth here is
something which is growing exponentially
the first thing first picture is uh
just radioactive decay so this is a
chain reaction or with other words it's
an it's an atomic bomb and the bomb
explosion stops if all the fuel is spent
or something other is limited another
example for exponential growth is a
spread of
covid uh in your body the virus
load also increases in the first steps
exponentially and the limit is your body
if your body
cannot um cannot provide more resources
for the virus uh then the exponential
growth stops the same with the
population we had this in in Co and this
is the danger of
something um increasing
exponentially that you simply have a
limit which you don't want to
hit and here you see this is the green
curve is the growth of the data centers
predicted for uh for the next
years and this m this makes it dangerous
and
so
something something limiting will happen
we don't know exactly
what it could simply be that they go out
of business because the price is too
high it could also be
oh
sorry it could also
be that is uh that it is competing with
other resources and that simply we
cannot uh spend the energy we use in
data centers and other things here you
see um the comparison of data centers
with Aviation shipping and here it it's
getting interesting it's even competing
with food production
so um and the range is because the data
is not really clear the data center um
owners do not really need to give out
the
data if you look into um if you run your
data center on your own or if you should
go to a cloud provider the cloud
providers are
hyperscalers sorry the hyperscale are
the best uh in terms of um energy saving
because they have the biggest data
centers this is
normal and so from an energy perspective
the advice would be go to the go to the
cloud and don't build your own data
center oh sorry this is obviously um
competing with privacy so you have the
option not to go into a cloud and uh
have gdpr
compliant colocation or your own data
center or you have to save
energy and go into the
cloud uh if you compare another thing um
then you see it's not only consuming
energy it's also consuming
water so the 15 megawatt
uh the 50 megabat data center is around
the energy consumption of a hospital on
alont
Orchid and not the energy consumption
sorry so the water
consumption or uh comparable to a golf
course so if you have the choice to
build a data center a hospital or a golf
course um then it depends on your
preferences
what what you
prefer data center is just for maybe
yeah Computing
gaming
um or for in the hospital yes this is
just for the normal population and this
if this competes you have immediately a
conflict and uh
normally uh the best lobbying wins
or
uh the
best uh use of of venture capital and
I'm I don't know how much Venture
Capital goes to the
hospitals if you see
here um there is some uh number which is
always used for advertising this is a
power usage
Effectiveness it has been evented from
from by Google because Google looks very
good with this and you see uh here it's
a
number and they improve all the
time um from and this number is simply
the total energy consumption by the real
uh load which is used for
computation this means if the number
would be one then it would be 100%
effective data
center uh without need of cooling and
energy for cooling and
infrastructure and if always if you see
the number it's like in the another
example is if it's in the do bar the do
bar train shows you only the speed if
it's fast it does not show you if your
IC is spending 30 km per hour it shows
you if you uh if it is uh spending if it
is going with 200 km and so if you see
the numbers normally they are you don't
ever see the bad
numbers and here is another curve which
shows how Google makes it the energy as
the water consumption of Google data
centers is much higher than uh the water
consumption of other Cloud
providers so and then they compare
obviously with others with countries
with other Cloud providers so you should
take these numbers with uh care because
on this scale uh renewable energy
consumption
Amazon is better as than Germany and I
simply don't believe this
numbers so resource conflicts
uh they are popping up everywhere where
data centers are
built in VG
people are gathering against an Amazon
facility with a consumption of 600
megawatt 600 megawatt is more or less
half um a power
plant in
Ireland the um the data centers
make um they take 18% of the energy
consumption of
Ireland and the national strategy of CO2
reduction now is uh going to
call um 65,000 cows because they want to
um limit their um carbon
dioxide production so you have here data
centers against
cows and if you remember Island In My
Memory Island was also very famous for
for for Hing C and and uh
sheep and comparable the data centers
are using as much energy as all the
private City
Homes in the
UK uh they have in East
London uh created a big um environmental
opposition movement
because uh they cannot do housing
anymore if you don't have energy for
housing because you want to sell the
energy to the data centers then this is
the next problem so always where these
huge data centers come on a local scale
you have this kind of Rec resource
conflict energy and or
water same in the
Netherlands um and
they even talk about that they need more
more more dkes so that they build higher
walls against the um the northy because
if they pump up uh this water for
cooling and
uh
um Vapor it then uh the the groundwater
is sinking and this this means um they
need to put more energy in in uh
moving uh and then then then the next
step is the salt water comes from the
ocean and then they have other conflicts
too this is another
example in the Dallas in the
US this is in on the on the local scale
is also an exponential grow so this
means typically you can compute you need
between 1.5 and three 2.3 lit water per
kilowatt hour
energy this is typically
15 to 30
23 cubic M for 100 for a 10 megawatt
Data
Center and yeah is this a big one or not
so I looked it up the typical sizes of
data center start from 15 Kow so this is
a the RX fit into a container the
typical things we have here from NT in
Berlin or otherwise are between 50
between 5 megawatt and 40 megawatt and
the hyperscalers have more or less No
Limit so the biggest I've read about is
600
megawatt and the typical water use is
between 4 and 7 million cubic M water
per year this is a medium large city for
a Data
Center and the first stops have arrived
so in Ireland Microsoft and Amazon have
to hold their plans in the Netherlands
too in Germany in branberg we had the
problem that uh alphabet so the company
behind
Google is not allowed to build a data
center where they originally have
planned it it has now moved to Mitten
valda the data center
in no haen would have been optimal by
energy energy usage because there is
a
uman so there is a power uh switch
station but where they build it now
there is it's more or less in the middle
of
nowhere um and they have no use for
their heat and something like this in uh
Noh they have planned a Poe value of
1.03 and in menal they don't tell the
number
and one remark all the studies I've seen
so far uh are before the artificial
intelligence boom took
off so what we know so far is that
training C gbt uses one do oh
go uh
1,00 287 gwatt hours so roughly uh the
equivalent of 100 20 us homes for a
single year this means this comes on top
of the situation here so the artificial
intelligence is in the training phase
using a lot of
energy and here you also can uh compute
this uh this uh Pue value and this is a
very bad one here you have you see what
you all have to take into consideration
so CPU rum and the gpus and the gpus are
normally very similar to the Nvidia
graphic cards you run in your gaming
computer at home and they are extremely
energy
hungry so here are some more
numbers and the interesting part is here
you on an average you can estimate by
the Computing cost uh the energy
consumption
so here are typical Hardwares tpus are
tensor processor unit so these are
special graphic um GPU like devices for
um artificial
intelligence and uh here you see the
price and here's the
equivalent for um carbon dioxide in um
IPS so this is an American things have
it's sometimes hard to um calculate it
in in normal
units more interesting is a comparison
uh with real life situations for example
here you see the consumption for an air
travel between New York and San
Francisco this is what you
normally consume in one year or one US
citizen consumes this is the next step
uh
36 uh
1,156 uh hips and a car
uh for the full Lifetime and here there
you see the training of one model with a
GPU this is a neurol lingual lingual
processing
pipeline uh it doesn't look so much but
you have to tune it and you have to do a
lot of experiments and this means this
increases to that number which is
comparable to a car in the entire
lifetime
so this means training in an artificial
intelligence
model is comparable to running a car for
the entire lifetime of a typical
car compared to that the Bitcoin is the
worst it's a total waste of uh
energy uh it is consuming more energy
than some uh even developed
countries uh from from my personal
experience we had always these things
some developers come with a
you Genius of an idea and they want to
go live in critical infrastructure so
there is no Cloud
involved for example a trading
software which should be run on open
shift the vendor came up with 10 nodes
of hbase edge Bas is this Google like
database you can host for free uh it's
an Apache project and then we tried to
measure the
load and calculated the real needs and
uh finally it was hard to detect the
load and this means even my SQL database
would be
oversized and finally we have we could
have run this on an SQL light database
on a rasbery
pi and this means uh we have a
trend in software that it has an
incentive that the team which
spends the most
resources is uh prefered so um another
experience some 10 years
ago
uh was I have uh
automated uh the database roll out for a
customer and then we don't need an
oracle team
anymore and uh yeah Oracle teams are
expensive expensive but they immediately
looked for Hadoop which means they have
a huge cluster solution for for a big
data file system and so they could use
more
resources um in their daily job and this
is a
problem uh I call it server
machism uh the more horsepower it's it's
the same as in in posing with expensive
cars the more horsepower the more
important is a
team and you should re sync your big
data Paradigm in most of the cases it's
completely
wrong if you have to um increase the
size of your data to compute it then
something is completely wrong I've seen
customers doing
this and uh on the other side this idea
Cuts totally into the business model of
data centers because they want to sell
you compute power storage Network
Power and not only the hyperscalers have
this problem also the normal isps and
the companies who do the
housing in the background you could
see uh one of these electric cars with
uh uh which can go a thousand kilometers
without loading is completely
useless because this is not the use case
we don't need these big things anymore
we need U electric bicycles but but not
electric car so but this is not really
visible at the
[Applause]
moment uh
yeah thank you another effect I'm
responsible for is this so-called
rebound effect if you make something
more accessible it's used more and then
the consumption increases and then the
energy consumption also
increases I looked it up and is known as
yon's paradox
it was detected
for uh steam engines in the beginning so
if the cost increases let's say from 100
to 80 then the usage increases more than
um this amount of 20% so it goes from 10
to 14 here so this is 40% this means if
you make something cheaper it's
immediately used more this is logical
and this uh absolutely um makes
everything complicated if you make
something
easier people are using it uh more than
proportional we have the same in in the
cloud and my personal observation is uh
I'm doing coetus so I try to make Cloud
access as easy as
possible uh and uh In This Cloud access
there are hidden costs which I without
exactly knowing them um shrink so we if
you can do self provisioning you are
enabl to use a cloud which is my daily
job or do virtualization containers
kubernetes and
automation uh finally um more people
have access to the resources and this
means effectively you are triggering an
increase
in uh resource consumption even if the
effective container might be smaller
than the virtual machine award you have
for
before finally uh the overall the total
energy consumption
my may
increase and this is a problem we should
have in in
mind uh further problems if we don't
have any transparent information on data
centers we only know roughly
hyperscalers are better than uh self rer
data centers here's another um bad old
example so this is Belin Spandau if you
know it here is the old e shelter data
center here is the finance arm so the
tech office span now and here is a lot
of cooling
devices and on the other side of the
channel there is a coal uh Coal Power
Plant which also produces heat for the
local heat Network and they are
completely disconnected so the heat of
the data center is wasted and on the
other side of the channel we produce uh
heat to um get our homes
SW
and I've criticized uh it even on the
last bits and boy conference um NTT has
now a new data center in Berlin Marine
Park where they have two buildings and
they have uh connected up with the gazak
so this is a they are not only
providing um gas but also heat for for
housing and for the industry and the
have a total uh renewable data center
with uh in the final Stage 48
megawatt the poe is smaller than
1.3 and they are based 100% of renewable
energy and this produces 29 gwatt hours
a year so this is a reasonable solution
so it at least it's not wasted but it is
not possible to use the old data centers
and simply attach um the heat
transform further topics here from from
Germany we have a drought everywhere so
problem is if I want to cool my data
center with with local water I need
water and if the the groundwater is
sinking I don't have this water so
Frankfurt has this problem at the
moment
um and they have uh all over this
reported these
problems in br Google had also these
problems and uh it is absolutely in
unclear if they can use it if it's in
the middle of nowhere of mid Val
probably there is no heat consumer so
definitely they will also waste the
energy so this is Mitten this is a
Google
case What You can conclude from the
public available
information um and they don't they don't
tell you the Poe value which means it's
a bad value otherwise they would tell
you probably it's in the ventage data
center location because Google is not
always hosting uh their own computers in
their own data
centers so the new energy law it is
valid only for new data centers not for
the old
[Music]
one and the poe must be below 1.2 but
only from 2026
on um by the way the poe can one I will
give an example
soon it must data center must have a
power of at least 200 kilow which is not
a
very big one uh it has been diluted by
lobbying
300 300 last one okay
so it's even worth 300 thank you
an and a lot of lobbyism took
over and they must integrate it into
local heating systems but in mid there
are no local heating systems on that
scale there is a Golem article on that
so we have this
problem and I don't want to I don't want
you to go uh without a positive hope we
have uh the ability of building very
small data centers which can integrated
in your local energy and heating system
for example by the Brook they have
created on their
compus uh data centers in real industry
containers so you can wre it you attach
it to energy and to the network and then
s it boots what what is booting form of
open stack from the suffing cloud stack
they reported it on the
summit and you can integrate these small
containers in your
local
um heating provider so you have uh they
call it near
warming uh it uses renewable energy it
is kind of cloud computing inside the
container but this only meets everything
is
automated uh it's done by two German
companies uh it's 100% open source and
it runs totally
automatically so the only problem uh if
you want to drop these containers
everywhere into your local heating
systems uh is security so you have
to build the containers in a way that
nobody has access or that it is turning
off everything if somebody gets access
but this is
solvable what did they do they have
upcycled the heat to 85 degree of
Celsius which is the lower level where
these heating systems accept the
energy it's
scalable between 50 kilowatt so this is
a small container and 50 megawatt which
is round about the same as entity it
makes economic sense they told me Beyond
250 kilowatt this means five containers
or something like
this uh this means you have 2 gwatt
hours or the equivalent of 400
houses but the customers want at least
500 megawatt data centers so uh if you
calculate this this means uh 40 gwatt
hours or you have to have 8,000 houses
or some kind of industrial usage for the
heat the good news is this is
not just science fiction because the
real estate companies are interested to
build it into
new Housing
Solutions so
this seems to have a
value uh another more science fiction
like project is in the tropical country
of
Finland uh they simply have a sand
battery for heat so they uh heat up
sunand sand in the summer or with
whatever uh um measure here they um at
the moment it's not really visible they
directly transform energy into heat into
the
sand and this means uh yeah you could
also include some CPU CPU Computing in
in the middle of this process that you
get a
better uh usage of the energy so this is
a v of energy in the term of yes it
could also uh compute something in
between
and it's a it's called the hot Heart
Project and um what we see here it it's
quite complicated we have seen this with
the hitting discussion in in Germany
where people um
even uh triggered a campaign which was
more or less a cops campaign against U
the the the green transformation of
hitting houses so this is more complex
in will take definitely
longer so in my conclusion what we can
think about and it is a a process will
take more or
less 10 years 20 years or 30 years we
should integrate data centers into the
infrastructure with a Poe of one and use
the
Heat and uh the gazak told definitely
yeah it's probably not the perfect
solution we have but it's better to
start now than wait for the perfect
solution because the perfect solution
could look different on every
location there's a lot of pressure
behind because otherwise we don't uh get
our car decarbonization goals and this
is uh really some um something we should
not miss so this was more less overview
uh I think it was not sufficient in that
term that you have now a plan to but I I
think I wanted to raise at least that we
have a problem here and that there are
people starting to have Solutions
but definitely not final so if you want
to contact me here is my contact data
and now we are open for
[Music]
[Applause]
Q&A so thank you so much Thomas for um
giving us all this knowledge um over
there is an angel if you have a question
please go over to the angel you can just
cue with the angel and the microphone
okay do we find a way to do this
wow good that we stopped early
so um as we only have like 13 minutes
for questions uh maybe not more people
cue so okay
um yeah I just uh read this week an
article about the Google data center
plant in brandonburg and uh they said
they will not really need much water
because like most big new uh data
centers they have closed um water cycles
combined with air Cooling and then they
just don't need that big water
consumption so what is your perspective
on this um normally um this this is Poe
value so normally you can get a good Poe
uh only with water and um you can
exchange but it's still a it's still a
water cooling system but it's a closed
system so you need to fill it
once but not yeah all of the time but
then it's not as efficient as they would
simply Vapor the water it's simply if it
is closed it it's better than than um
than air
Cooling
we have we have this
um but you can reach a Poe um of 1.2
that's possible it's possible and Google
has done it but at at the moment only
with a lot of water consumption and if
they can be better I think uh they uh
they're happy if they are below This 1.2
but they will not go down to 1.03 or or
something like this so this is an
improvement but it's not the thing uh
they could have if they would waste them
uh
energy I appreciate that there are
smaller options because I also don't
believe in the giant uh Solutions uh one
one last sentence we can reuse heat also
for other things not just for warming
houses we can exactly we can drive food
and agriculture we can have green houses
to to grow stuff in the middle of
nowhere like Mitten valder so are other
options too but it's a disaster that the
law has been uh exactly has been
destroyed to its core so it's not the
problem is then every solution is
individual so you cannot simply have
yeah we we use the heat for one Data
Center and scale it and run it
everywhere you have problem you it has
to be designed locally which can also be
an advantage for the local industry but
uh there is no single uh and if you
force them by law they they have to find
a solution and now they don't have to
anymore this is the
law so maybe short questions and short
answer so everyone can
um can ask their question yeah okay my
question is in the same direction isn't
there a law which forbids to use fresh
water with all the grouts and
water not at the moment so you need a
license like Tesla in brunborg or like
um
Brown coal in but but then if you have
this license you can do whatever you
want with the local
water hey thanks for the talk uh a
question about the software side of
things uh so you as you mentioned
there's a lot of opportunities uh to
especially when dimensioning a system to
reduce the size and therefore reduce the
consumption and make better use of the
resources that we already have in those
Data Centers do you think that working
on the foundational Technologies so for
example building more efficient
compilers with smaller software closures
that end up in all of our Docker
containers uh would make an actual
impact in the long term all this helps
even better CPUs would help uh and uh
you have to look into it for example
there are a lot of comparisons that
python is inefficient which is not true
because python is mostly a wrapper
around good old C or foron libraries so
you have to look into your application
and measure the energy and effectively
uh you would need somebody in your team
who is aware of this and can scale the
energy load uh down this is something
you have to learn it's not your daily
business probably as a developer but
somebody should have this knowledge in
your team or you should have somebody
this would be my proposal yeah take take
it as a small suggestion for people
interested take up open source projects
especially the ones that everyone uses
and try to make small improvements there
you can have a huge impact in the terms
yeah hey uh thanks for the talk really
interesting super cool um a very naive
question so one of the things that we
can actually do with the increasing
Computing demand that we will have is
recapturing the energy in terms of heat
um that's great but I very naive
question do we know what the fraction of
low xergy energy use of our society is
so you know heat compared to
electricity uh oh that's a good question
uh I have no numbers for that but I
think it it depends on the climate uh
and the local
situation uh affect and the isolation of
of the housing so Germany is uh very bad
on that Scandinavia is U because it's an
tropical area obviously is much better
on that so uh we have to improve on all
levels so isolation heat usage uh better
effective data center something like
this otherwise it would not work as as
soon as we we have to increase the exog
Again by by converting heat back to
electricity um it becomes really
inefficient so I mean it's better than
wasting it of course it's free in in
that sense but this is something that I
think we should look at yeah so it's
it's not very efficient to transform
this kind of energy in in in electricity
again this is thermodynamics yes entropy
is heat is entropy on
thank you hi thanks for the amazing and
much needed talk I was wondering uh you
identifi uh the main drivers for
electricity consumption in data centers
U being compute power I was wondering if
uh if storage also generates usage yes
it does but it's proportional so you
have more or less stor network uh is
some proportional and I did not want to
overload the talk with all these details
there are details somewhere in the
internet but yeah it also contributes hi
thanks for the great talk um are there
any conflicts expected between Mitten
valde and green hied Tesla because uh
Tesla is
also Tesla is also consumer I think the
real conflict is between uh coal and
Tesla the the coal consumption in in the
um Brown coal region is much higher the
water consumption is much higher this
has also an impact if they stop using
water in berin the river spray uh will
go down 75% which is uh more or less a
catastrophe for for qutb and Southern
Berlin um is it is it right to
say the cooling is the most important
and most um
inefficient point on on data center
energy
consumption uh it's one of the points
because it does not compute anything
useful so it's if you waste it it it's
gone if you can use it you have a saving
of some percent but if you can use the
entire CPU energy then you have a
major uh progress on on saving energy so
if we if we solve the cooling problem we
we are very much better I mean how we
can see in in the the comparison of
Google and Microsoft um there are
different approaches to cool and this is
the point on that we are can work
technically and um I'm working in an
absorption cooling using this very low
caloric um Heat and the temperatures are
about I I don't know 50 60° maximum and
this is something you cannot use in in
many ways not normally you can use waste
heed and that's why I I want to ask you
how you how you would say this kind of
absorption and absorption Technologies
are uh on the on the board you know to
solve this problem and a big scale uh
this is the idea of uh this um people
they have up cycl so they have a heat
exchange normally you get 35 degrees a
heat pump it's a heat pump yes and and
this is the lower threshold for being
useful for
warming
houses technology if you can do that
yeah this is ter the cooling it's not
the compression cooling it's it's
another kind of process you don't need
need electricity you use the heat to
cool the cop is uh
0.5 from 2 kilow heat you can get one
kilowatt Cooling and this is what I
think is a very good idea but the the
yeah I mean the the the main stream in
this uh question does not see this um
solution in a way I I would expect it I
would look to dive deeper into that
but not seen it so far it's definitely
interesting all right
so are you do you want to ask a
question yeah still two minutes actually
two questions one is um if you use the
heat for heating houses I always wonder
what happens in the 8 nine months maybe
here in Europe where you don't heat the
houses what do you do these numbers seem
theoretical yeah so idly you save the
heat somewhere in a sand and and then
consume it in the winter so this is a
Scandinavian
solution and this means that you need
certain scale that you need a certain
environment and you have to rethink this
solution carefully so if Finland can do
it probably we also can do
it but at the end you have to consider
every aspect of uh the environment the
local situation and so on and question
number two is Pue is um very much
focused on Hardware right I guess
because there you can measure the energy
but as you said you can save a lot of
power um by programming more efficiently
like you had the example 10 hbas CL
servers versus one is right do you know
of any measurement or metric that I can
advertise my software for being
efficient with uh so for commus
Microsoft has a framework I have not
looked deeper into it so you can measure
it but you have to also take into
account that the business model of the
data centers is to sell you more
computing power so they are not
interested in you saving energy they are
interested in you wasting energy so this
is this is uh some some this goes into
the opposite direction and I have no
idea about an incentive uh how how we
get this together that the data center
providers help you to save energy thanks
for the amazing
talk is it a short question it's super
short it's just Just one thought on this
if if they don't have any interest in
defining something to measure this we
should yes because this effectively this
is your money this is cost this is
directly proportional to the money you
spend to the
clouds so good then thank you all for
coming thank you Thomas for answering so
many
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questions