Open xigang opened 1 year ago
/cc @RainbowMango @XiShanYongYe-Chang @ikaven1024
We have test it with 100 clusters, and 2 millions pods. FYI: https://github.com/karmada-io/karmada/issues/2518.
If you have some other resources, having large quantity like pods, you can run searval karmada-search
group, each group cache one or some kinds resources. And add a new component (may call it karmada-search-gateway
), redirect client request to the target group due to the resource kind requested. Shows this architecture as below:
you can run searval karmada-search group, each group cache one or some kinds resources.
That sounds great, but how to achieve that goal?
May add some fields like group
in RR. karmada-search-gateway
and karmada-search-group
watch these RRs.
E.g.
apiVersion: search.karmada.io/v1alpha1
kind: ResourceRegistry
metadata:
name: rr_pods
spec:
group:
pods:
targetCluster:{}
---
apiVersion: search.karmada.io/v1alpha1
kind: ResourceRegistry
metadata:
name: rr_nodes_svcs
spec:
group:
nodes_svcs:
targetCluster:{}
---
apiVersion: search.karmada.io/v1alpha1
kind: ResourceRegistry
metadata:
name: rr_foos
spec:
group:
foo:
targetCluster:{}
Sounds like a good way to go.
@ikaven1024 But I understand that a single karmada-search
group uses the memory of one machine, and there will still be memory bottlenecks, such as a very large number of pods resources.
When search group reach its bottleneck, client informers also face the same problem. Our federation scale should have a upper bound, but we have not test it.
When search group reach its bottleneck, client informers also face the same problem. Our federation scale should have a upper bound, but we have not test it.
Thanks @ikaven1024 reply.
What do you think about this question?:
I have a question. Karmada will locally cache resource data defined by ResourceRegistry, such as pods, nodes, workloads, etc. If a federated cluster manages 100 member clusters, each with 5k nodes, will a single Karmada apiserver have a memory bottleneck?
How do we need to support larger federated clusters?
Environment: