Yep, we are doing pretty much the same.

We creating limitrange for every projects with defaults
We creating quota for every project and using it as cost model for CPU, memory, 
storage
We configured cluster overcommit 50 % for memory and 10 % for CPU

    ClusterResourceOverride:
      configuration:
        apiVersion: v1
        cpuRequestToLimitPercent: '10'
        kind: ClusterResourceOverrideConfig
        memoryRequestToLimitPercent: '50'

monitorin resources uage and adding more nodes

we are trying to tune CPU a little bit as CPU is little confussign and 
uncompress resource

Thanks for your information. It was really useful to clear some doubts around 
CPU request Vs limits


--
Srinivas Kotaru
From: Frederic Giloux <[email protected]>
Date: Friday, March 23, 2018 at 11:55 AM
To: Srinivas Naga Kotaru <[email protected]>
Cc: users <[email protected]>
Subject: Re: Limits for CPU worth? Vs benefits

In the previous example we looked at setting a limit at the pod having the 
lower request but you may rather want it for the pod having the higher request. 
In this extreme scenario (node with 32 cores) pod A was gaining 21 cores on top 
of its request where pod B only 3 when no limit was set. You may find that out 
of proportion and may want to cap what a pod with high request may get.
Another aspect is resource fragmentation, CPU in this case. Basically you get 
better density (you can place more pods/containers not just in number but also 
as a some of requested CPU) with smaller CPU request/limit chunks. The rests 
are smaller. A cluster administrator may want to address this aspect by 
creating a limit range with a max CPU and potentially MaxLimitRequestRatio. If 
a max CPU limit range is set then you have to set a CPU limit.
That said my advice would be not to over engineer it. Start with simple and 
tolerant settings: make requests mandatory or provide defaults for all your 
pods or containers (otherwise the scheduler has a hard time), have quotas so 
that a single project does not starve your complete cluster. Monitor your 
cluster, the resource consumption and its pattern and react where needed.
Regards,
Frédéric
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