Increase grafana mem/cpu in mgmt cluster

What does this MR do and why?

We have seen a lot of sso tests that failed on grafana check (502 error), looking on the state of the pod I have noticed that in most of the cases the pods are in OOMKilled state.

containerStatuses:
  - allocatedResources:
      cpu: 100m
      memory: 100Mi
    containerID: containerd://4f9962f9e3d3fd497db4720e8c256d2e8be685d0ce0a2cbf402f7f80be5c23a6
    image: docker.io/rancher/appco-grafana:12.3.1-1.12
    imageID: docker.io/rancher/appco-grafana@sha256:c4508fe1195b873268c29d370dbff16fa366e5ef10582ad84c5ce0f4698bb49a
    lastState:
      terminated:
        containerID: containerd://7f3e887f43f6c6a07f31355e5ef585ab2de2f24933c6b25deb7267d1dfcf736d
        exitCode: 137
        finishedAt: "2026-10-08T15:19:49Z"
        reason: OOMKilled
        startedAt: "2026-10-08T15:03:41Z"
    name: grafana

https://gitlab.com/sylva-projects/sylva-core/-/jobs/17029889967

The aim of this MR is to increase the memory & cpu on grafana pod.

Related to #4767

Test coverage

CI configuration

Below you can choose test deployment variants to run in this MR's CI.

Click to open to CI configuration

Legend:

Icon Meaning Available values
☁️ Infra Provider capd, capo, capm3
🚀 Bootstrap Provider kubeadm (alias kadm), rke2, okd, ck8s
🐧 Node OS ubuntu, suse, na, leapmicro
🛠️ Deployment Options Deployment option list and description
🎬 Pipeline Scenarios Available scenario list and description
🟢 Enabled units Any available units name, by default apply to management and workload cluster. Can be prefixed by mgmt: or wkld: to be applied only to a specific cluster type
🔴 Disabled units Any available units name, by default apply to management and workload cluster. Can be prefixed by mgmt: or wkld: to be applied only to a specific cluster type
🏗️ Target platform Can be used to select specific deployment environment Available platform list and description
⚡ Pipeline control autorun, manual or blocking. Can be used to override global config and start a deployment pipeline the required way
  • 🎬 preview ☁️ capd 🚀 kadm 🐧 ubuntu

  • 🎬 preview ☁️ capo 🚀 rke2 🐧 suse

  • 🎬 preview ☁️ capm3 🚀 rke2 🐧 ubuntu

  • ☁️ capd 🚀 kadm 🛠️ light-deploy 🐧 ubuntu

  • ☁️ capd 🚀 rke2 🛠️ light-deploy 🐧 suse

  • ☁️ capo 🚀 rke2 🐧 suse

  • ☁️ capo 🚀 rke2 🐧 leapmicro

  • ☁️ capo 🚀 kadm 🐧 ubuntu

  • ☁️ capo 🚀 kadm 🐧 ubuntu 🟢 neuvector,mgmt:harbor

  • ☁️ capo 🚀 rke2 🎬 rolling-update 🛠️ ha 🐧 ubuntu

  • ☁️ capo 🚀 kadm 🎬 wkld-k8s-upgrade 🐧 ubuntu

  • ☁️ capo 🚀 rke2 🎬 rolling-update-no-wkld 🛠️ ha 🐧 suse

  • ☁️ capo 🚀 rke2 🎬 sylva-upgrade 🛠️ ha 🐧 ubuntu

  • ☁️ capo 🚀 rke2 🎬 sylva-upgrade-from-1.6.x 🛠️ ha,misc 🐧 ubuntu

  • ☁️ capo 🚀 rke2 🛠️ ha,misc 🐧 ubuntu

  • ☁️ capo 🚀 rke2|okd 🎬 no-update 🐧 ubuntu|na

  • ☁️ capo 🚀 rke2 🛠️ misc 🐧 ubuntu 🟢 mgmt:harbor 🔴 neuvector

  • ☁️ capo 🚀 rke2 🛠️ ha,misc,openbao 🐧 suse

  • ☁️ capo 🚀 rke2 🐧 suse 🎬 upgrade-from-prev-tag

  • ☁️ capm3 🚀 rke2 🐧 suse

  • ☁️ capm3 🚀 kadm 🐧 ubuntu

  • ☁️ capm3 🚀 rke2 🛠️ external-openbao-no-tls 🐧 ubuntu

  • ☁️ capm3 🚀 rke2 🛠️ external-openbao 🐧 suse

  • ☁️ capm3 🚀 kadm 🛠️ external-openbao,openbao-namespace 🐧 ubuntu

  • ☁️ capm3 🚀 ck8s 🐧 ubuntu

  • ☁️ capm3 🚀 kadm 🎬 rolling-update-no-wkld 🛠️ ha,misc 🐧 ubuntu

  • ☁️ capm3 🚀 rke2 🎬 wkld-k8s-upgrade 🛠️ ha 🐧 suse

  • ☁️ capm3 🚀 kadm 🎬 rolling-update 🛠️ ha 🐧 ubuntu

  • ☁️ capm3 🚀 rke2 🎬 upgrade-from-prev-release-branch 🛠️ ha 🐧 suse

  • ☁️ capm3 🚀 rke2 🛠️ misc,ha 🐧 suse

  • ☁️ capm3 🚀 rke2 🎬 sylva-upgrade 🛠️ ha,misc 🐧 suse

  • ☁️ capm3 🚀 kadm 🎬 rolling-update 🛠️ ha 🐧 suse

  • ☁️ capm3 🚀 ck8s 🎬 rolling-update 🛠️ ha 🐧 ubuntu

  • ☁️ capm3 🚀 rke2|okd 🎬 no-update 🐧 ubuntu|na

  • ☁️ capm3 🚀 rke2 🐧 suse 🎬 upgrade-from-release-1.5

  • ☁️ capm3 🚀 rke2 🐧 suse 🎬 upgrade-to-main

Global config for deployment pipelines

  • autorun pipelines
  • allow failure on pipelines
  • record sylvactl events

Notes:

  • Enabling autorun will make deployment pipelines to be run automatically without human interaction
  • Disabling allow failure will make deployment pipelines mandatory for pipeline success.
  • if both autorun and allow failure are disabled, deployment pipelines will need manual triggering but will be blocking the pipeline

Be aware: after configuration change, pipeline is not triggered automatically. Please run it manually (by clicking the run pipeline button in Pipelines tab) or push new code.

Edited by Bogdan Antohe

Merge request reports

Loading
Loading