This document discusses how the Kubernetes platform and cloud infrastructure can contribute to climate change through excessive resource usage and lack of efficiency. It identifies issues like "kubesprawl" where too many clusters are created, lack of visibility into resource usage that leads to "zombie workloads" consuming resources needlessly, and lack of automation and governance around the lifecycle of clusters. The document advocates for tools and practices that can improve resource utilization, add elasticity, limit creation of unnecessary clusters, help decommission zombie workloads, and make it easier for users to understand their resource usage and turn clusters off when not needed in order to reduce the environmental impact.

1. How to Love K8s and Not Wreck the Planet
Holly Cummins
IBM Garage
@holly_cummins

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we have a
problem.

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the earth is
getting warmer

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the earth is
getting warmer

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warmer

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uncomfortably warmer

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uncomfortably warmer
drought

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uncomfortably warmer
drought
floods

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uncomfortably warmer
drought
floods
submersion

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uncomfortably warmer
drought
floods
submersion
hurricanes

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uncomfortably warmer
drought
floods
submersion
hurricanes
fires

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there’s a bug in our 2030 flood
risk graph for Tokyo … isn’t there?

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uh … no.
there’s a bug in our 2030 flood
risk graph for Tokyo … isn’t there?

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our industry
contributes to
climate change

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data centres
1-2%
aviation
2.5%

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data centres
1-2%
aviation
2.5%

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data centres
1-2%
aviation
2.5%

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data centres
1-2%
aviation
2.5%

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the dream

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the dream

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the dream

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kubesprawl

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the cluster is the
unit of deployment

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21
clusters per
IBM Cloud
account

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21
clusters per
IBM Cloud
account

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utilisation
elasticity

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application

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control plane
application

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control plane
application
manual replica count
horizontal auto-scaling

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control plane
!
application
clusters are less elastic than applications
manual replica count
horizontal auto-scaling

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control plane
!
!
application
clusters are less elastic than applications
every cluster has overhead

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serverless?

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serverless?

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serverless?

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dr. malice

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namespaces

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namespace isolation
is not enough

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conway’s law is for clusters, too

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noisy neighbours

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name collisions
scope errors

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dev
staging
that weird experiment
prod

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control plane
lots of applications
is this a win?

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zombie
workload

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2017 survey
25%
of 16,000 servers
doing no useful work

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2017 survey
25%
of 16,000 servers
doing no useful work
“perhaps someone
forgot to turn them off”

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Hey boss, I created a
Kubernetes cluster.

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Hey boss, I created a
Kubernetes cluster.
I forgot it for 2 months.

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Hey boss, I created a
Kubernetes cluster.
I forgot it for 2 months.
… and it’s £1000 a month.

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€ ==

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is there a
solution?

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IT Department, UK Bank
let’s figure out what all
these cloud workloads are,
since I’m paying for them
long
meetings

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IT Department, UK Bank
let’s figure out what all
these cloud workloads are,
since I’m paying for them
long
meetings

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tags

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governance

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make it easiest to
do the right thing

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make it easiest to
do the right thing

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large bank, 2013
50%reduction in CPUs with a
lease system

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large bank, 2013
50%reduction in CPUs with a
lease system

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multicloud management

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traffic monitoring

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is K8s zombie-proof?

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shut it down?
but … what if I
need this
cluster later?

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gitops

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gitops
(infrastructure as code)

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spin it down

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spin it down
spin it up
kubectl apply -f all-my-cluster/

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spin it down
spin it up
kubectl apply -f all-my-cluster/

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spin it down
spin it up
kubectl apply -f all-my-cluster/

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spinning down clusters:
the new lights off?

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unsolved problem == opportunity

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1-2%

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tool creators, support
1-2%

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better utilisation
elasticity
multi-tenancy
de-zombification
visibility
disposability
tool creators, support
1-2%

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1-2%

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users …
1-2%

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up utilisation
aim for elasticity
limit kubesprawl
de-zombification
know what you’re using
turn it off
users …
1-2%