Remove loki chunk & results cache memory requests

What does this MR do and why?

Remove loki chunksCache & resultsCache memory request

loki chunkcache has a default memory request of 9Gi, which is very high. Remove that request, and reduce the allocated memory.

The new limits are computed using the same rule as in helm chart:

https://github.com/grafana/loki/blob/e3d10542fd5741be97ed4261a7ee00e75ab8e4cb/production/helm/loki/templates/memcached/\_memcached-statefulset.tpl#L94

Related reference(s)

Relates-to: #2048 (closed)

Closes: #2121 (closed)

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
🐧	Node OS	ubuntu, suse
🛠️	Deployment Options	light-deploy, oci, ha, misc
🎬	Pipeline Scenarios	rolling-update, mgmt-rolling-update, k8s-upgrade, sylva-upgrade-from-x.x.x, simple-update, preview, nightly

• 🎬 preview ☁️ capd 🚀 kadm 🐧 ubuntu 🛠️ oci
• 🎬 preview ☁️ capo 🚀 rke2 🐧 suse
• 🎬 preview ☁️ capm3 🚀 rke2 🐧 ubuntu
• ☁️ capd 🚀 kadm 🛠️ light-deploy 🐧 ubuntu
• ☁️ capd 🚀 rke2 🛠️ oci,light-deploy 🐧 suse
• ☁️ capo 🚀 rke2 🛠️ oci 🐧 suse
• ☁️ capo 🚀 kadm 🛠️ oci 🐧 ubuntu
• ☁️ capo 🚀 rke2 🎬 rolling-update 🛠️ ha 🐧 ubuntu
• ☁️ capo 🚀 kadm 🎬 k8s-upgrade 🐧 ubuntu
• ☁️ capo 🚀 rke2 🎬 mgmt-rolling-update 🛠️ ha,misc 🐧 suse
• ☁️ capo 🚀 rke2 🎬 sylva-upgrade-from-1.3.x 🛠️ ha,misc 🐧 ubuntu
• ☁️ capm3 🚀 rke2 🛠️ misc 🐧 suse
• ☁️ capm3 🚀 kadm 🛠️ oci,misc 🐧 ubuntu
• ☁️ capm3 🚀 kadm 🎬 mgmt-rolling-update 🛠️ ha,misc 🐧 ubuntu
• ☁️ capm3 🚀 rke2 🎬 k8s-upgrade 🛠️ ha 🐧 suse
• ☁️ capm3 🚀 kadm 🎬 rolling-update 🛠️ ha 🐧 ubuntu
• ☁️ capm3 🚀 rke2 🎬 sylva-upgrade-from-1.3.x 🛠️ misc,ha 🐧 suse
• ☁️ capm3 🚀 kadm 🎬 rolling-update 🛠️ ha 🐧 suse

Global config for deployment pipelines

• autorun pipelines

• allow failure on pipelines

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.