Memory Limit too low results in OOMKilled

[haf-tech]

Installation of the operator in OpenShift is not successful, due the fact that the requested memory limit does not met the real memory consumption

the current config results in restart with OOMKilled signal

resources:
  limits:
    cpu: 100m
    memory: 175Mi
  requests:
    cpu: 100m
    memory: 20Mi

Changing to 255Mi results in a stable version

resources:
  limits:
    cpu: 100m
    memory: 255Mi
  requests:
    cpu: 100m
    memory: 20Mi

Affected version:
IBM Cloud Operator, 1.1.0

[greglanthier]

When I've installed ibmcloud-operator I've been using a subscription that looks like this:

apiVersion: operators.coreos.com/v1alpha1
kind: Subscription
metadata:
  name: ibmcloud-operator
spec:
  channel: stable
  name: ibmcloud-operator
  source: community-operators
  sourceNamespace: openshift-marketplace
  config:
    resources:
      limits:
        cpu: 400m
        memory: 700Mi
      requests:
        cpu: 400m
        memory: 40Mi

This is probably oodles more than the operator itself needs 🤷 .

The increased memory consumption in OpenShift when compared against other cluster types might be related to the number of namespaces present in the cluster itself - especially if your installing the operator with cluster-wide scope.

[JohnStarich]

Thanks for opening @haf-tech. I think this is likely a duplicate of #199

How many secrets are in your cluster? kubectl get secrets -A | wc -l

[JohnStarich]

If either of you are interested, we’re open to PRs for fine-tuned watches. It looks like they would significantly reduce memory usage.

[haf-tech]

@JohnStarich, have deleted the cluster in the meantime. I tested it today on totally fresh new cluster, but now the default resource limit is fine and enough
and yes, #199 could be the same (root) cause

regarding the PR, I have currently no clue about the topic :-D

[haf-tech]

after applying the first Service and Binding, seeing OOMKilled

oc get secrets -A | wc -l
 1258

the above edit (increasing resource limit) helps here

[JohnStarich]

Yeah, looks like the same issue. Let's focus our conversation in #199. @greglanthier you're welcome to take this on, if you're interested.