Environment:

- ray 1.0.0、python 3.6.9
- k8s cluster

In order to use as much resources as possible, I tried these combinations, and didn’t run any code, but the network transmit in ray head node is so large (sent).

(1) each worker pod has 4 cpus (1119 cpus in total)

head node: 15 CPUs, 16Gi Memory

worker node: 4 CPUs, 2Gi Memory, 276 replicas

(2) each worker pods has 6 cpus (1119 cpus in total)

head node: 15 CPUs, 16Gi Memory

worker node: 6 CPUs, 4Gi Memory, 184 replicas

(3) each worker pods has 8 cpus (959 cpus in total)

head node: 15 CPUs, 16Gi Memory

worker node: 8 CPUs, 6Gi Memory, 118 replicas

(4) each worker pods has 15 cpus (1200 cpus in total)

head node: 15 CPUs, 16Gi Memory

worker node: 15 CPUs, 8Gi Memory, 79 replicas

So, I want to know:

- why the head node sent so many packets per seconds? I didn’t run any code yet.
- if I use nfs to share codes, how can I do to read code from local instead of distribute by GCS?