Hello,We used the tutorial for building an operator using helm. This is using the latest helm-operator v1.11.0.We are installing the operator on a non-small OpenShift 4.7 cluster (60 nodes, +2k Pods).While installing we had to go through multiple OOM crashes and constantly increase the memory limit.We finally got the operator manager running, but it is constantly using >1.2GB of memory.We believe there should be something weird. Can something be improved in the PROJECT or watches.yaml file?Are there known cases which could increase the memory usage?It looks like that the helm-operator manager is fetching all APIs on the cluster (or at least a huge fraction of those). Is this really needed? Could this be the bottleneck?Best,Michele--
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Product Manager Operator Framework & Quay
Red Hat OpenShift
selector | The conditions that a resource’s labels must satisfy in order to get reconciled. For additional information see labels and selectors documentation. |
Can you also describe how the Operator is deployed? if it's via OLM, what's the OperatorGroup configuration?On Fri, Sep 3, 2021 at 2:14 PM Michele Dolfi <d...@zurich.ibm.com> wrote:Sure, here is the content of the file.We also tried setting watchDependentResources to false, but it didn't help.# Use the 'create api' subcommand to add watches to this file.- group: apps.cps.deepsearch.ibm.comversion: v1alpha1kind: KgAmqpchart: helm-charts/kgamqpwatchDependentResources: false#+kubebuilder:scaffold:watch
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--Daniel MesserProduct Manager Operator Framework & Quay
Red Hat OpenShift
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