Enhance kyverno-policies-ready checksum, to avoid redundant wait times

What does this MR do and why?

This MR is aiming to fix redundant wait times when doing an apply.sh with no direct changes to Kyverno. By default, JOB_CHECKSUM hashes all of .Values. Any values change re-created the Job, which is adding an additional 60s to the deployment time.

This MR overrides JOB_CHECKSUM for this unit, using interpret-and-hash as other units already do. The hash now covers only:

• the rendered kyverno-policies unit
• the Kyverno chart spec
• _internal.sylva_core_version

Test coverage

Tested this on my dev cluster deployed from main:

1. apply.sh on this branch: Job re-created once, new checksum computed
2. second apply.sh with no changes: Job untouched
3. enabling a random unit that doesn't create a new Kyverno policy: Job untouched
4. enabling descheduler, which adds components/descheduler to kyverno-policies: Job re-created

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.