Hi, thanks for that suggestion. I took a look, but tit seems it isn't
quite what's needed.
It looks likes pod (anti)affinity is a binary thing. It works for the
first pod on the node with/without the specified label, but it doesn't
ensure an even spread when you schedule multiple pods.
In my case I scheduled pods using an antiaffinity
preferredDuringSchedulingIgnoredDuringExecution rule applying across 3
nodes and that made sure that the first 3 pods went to separate nodes as
expected, but after that the rule seemed to not be applied (there were
no nodes that satisfied the rule, but as the rule was 'preferred' not
'required' the pod was scheduled without any further preference). So
that by the time I had 6 pods running 3 other them were on one node, 2
on another and only 1 on the third.
So I suppose the anti-affinity rule is working as designed, but that its
not designed to ensure an even spread when you have multiple pods on the
nodes.
On 04/07/18 12:16, Joel Pearson wrote:
Here’s an OpenShift reference for the same thing.
https://docs.openshift.com/container-platform/3.6/admin_guide/scheduling/pod_affinity.html
On Wed, 4 Jul 2018 at 9:14 pm, Joel Pearson
<[email protected] <mailto:[email protected]>>
wrote:
You’re probably after pod anti-affinity?
https://kubernetes.io/docs/concepts/configuration/assign-pod-node/#affinity-and-anti-affinity
That lets you tell the scheduler that the pods aren’t allowed to
be on the same node for example.
On Wed, 4 Jul 2018 at 8:51 pm, Tim Dudgeon <[email protected]
<mailto:[email protected]>> wrote:
I've got a process the fires up a number of pods (bare pods,
not backed
by replication controller) to execute a computationally
demanding job in
parallel.
What I find is that the pods do not spread effectively across the
available nodes. In my case I have a node selector that restricts
execution to 3 nodes, and the pods run mostly on the first
node, a few
run on the second node, and none run on the third node.
I know that I could specify cpu resource requests and limits
to help
with this, but for other reasons I'm currently unable to do this.
It looks like this is controllable through the scheduler, but the
options for controlling this look pretty complex.
Could someone advise on how best to allow pods to spread
evenly across
nodes rather than execute preferentially on one node?
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