Jenkins® pipeline shared library for automating deployments via GitOps.
Take a look at cloudogu/k8s-gitops-playground to see a fully
working example bundled with the complete infrastructure for a GitOps deep dive.
See also our blog post that describes the challenges leading to this
library and some of the features it offers.
- Use Case
- Features
- Examples
- Usage
- Default Folder Structure in source repository
- GitOps-Config
- Stages
- Deployment
- Folder Structure in destination GitOps repository
- Extra Files
- SCM-Provider
- Validators
- License
- Written Offer
Use Case realised by this library:
- Separation of app repo and GitOps repo
- Infrastructure as Code is maintained in app repo,
- CI Server writes to GitOps repo and creates PullRequests.
- Lots of convenience features
- Same Pipeline API for different GitOps tools
- Write Kubernetes resources to a git™ repo (for a GitOps operator to pick them up) and creates PRs.
- Opinionated conventions for folder structures and workflows.
- Support for multiple stages within the same GitOps Repo
- Push to application branch and create PR (production) or
- Push to main branch (e.g. "main") directly for staging deployment
- Support for different GitOps tools/operators/vendors
- ArgoCD
- Flux v1
- Deployment methods
- Plain Kubernetes resources - write image tag into kubernetes deployments dynamically
- add files to deployment which will be generated to a configmap
- Helm deployments - set values (e.g. image tag) dynamically
- add custom k8s resources
- Support for different Helm-Repository types: Helm, Git
- Plain Kubernetes resources - write image tag into kubernetes deployments dynamically
- Convert files into Kubernetes config maps. This way you can edit them using full highlighting and linting support of your IDE.
- Fail early: Validate YAML syntax (yamllint) and against Kubernetes schema (kubeval) as well as Helm charts (helmKubeval)
- Pluggable validators: Simply add your own validators
- Extensible SCM providers
- SCM-Manager
- Other can easily be added due to an abstraction layer
The following examples range from simple to real-life and should help you get started.
Detailed instructions about the attributes can be found here.
This will simply validate and deploy the resources from the source repo's k8s
folder (see
folder structure into the GitOps
repo, implementing two stages (see stages)
using SCM-Manager (see SCM provider).
def gitopsConfig = [
scm: [
provider: 'SCMManager',
credentialsId: 'scmm-user',
baseUrl: 'http://scmm-scm-manager/scm',
repositoryUrl: 'gitops'
],
application: 'spring-petclinic',
gitopsTool: 'FLUX' /* or 'ARGO' */,
stages: [
staging: [
namespace: 'staging',
deployDirectly: true
],
production: [
namespace: 'production',
deployDirectly: false
]
],
deployments: [
plain : []
]
]
]
deployViaGitops(gitopsConfig)
The following is an example shows all options of a GitOps-config for a helm-deployment of an application. This would lead to a deployment of your staging environment by updating the resources of "staging" folder within your GitOps-folder in git. For production it will open a PR with the changes.
def gitopsConfig = [
k8sVersion: '1.24.8', /* Default: '1.24.8' */
scm: [
provider: 'SCMManager',
credentialsId: 'scmm-user',
baseUrl: 'http://scmm-scm-manager/scm',
repositoryUrl: 'gitops'
],
cesBuildLibRepo: <cesBuildLibRepo> /* Default: 'https://github.com/cloudogu/ces-build-lib' */ ,
cesBuildLibVersion: <cesBuildLibVersion> /* Default: a recent cesBuildLibVersion see deployViaGitops.groovy */ ,
cesBuildLibCredentialsId: <cesBuildLibCredentialsId> /* Default: '', empty due to default public github repo */,
application: 'spring-petclinic',
gitopsTool: 'FLUX' /* or 'ARGO' */
mainBranch: 'master' /* Default: 'main' */,
deployments: [
sourcePath: 'k8s' /* Default: 'k8s' */,
destinationRootPath: '.' /* Default: '.' */,
/* See docs for helm or plain k8s deployment options */
helm : [
repoType : 'HELM',
credentialsId : 'creds',
mainBranch : 'main', /* Default: 'main' */,
repoUrl : <helmChartRepository>,
chartName: <helmChartName>,
version : <helmChartVersion>,
updateValues : [[fieldPath: "image.name", newValue: imageName]]
]
],
folderStructureStrategy: 'GLOBAL_ENV', /* or ENV_PER_APP */
stages: [
staging: [
namespace: 'my-staging',
deployDirectly: true
],
production: [
namespace: 'my-production',
deployDirectly: false
],
],
validators : [
/* Enalbed by default. Example on how to deactivate one.
* See docs for more info on validators */
yamllint: [
enabled : false
]
]
deployViaGitops(gitopsConfig)
FluxV1:
- using petclinic with helm and extra k8s-resources and extra files
- using petclinic with plain-k8s and extra files
- using nginx with helm and extra files
ArgoCD:
- using petclinic with helm and extra k8s-resources and extra files
- using petclinic with plain-k8s
- using nginx with helm and extra files
Two parts need completion in order to get up and running with the library:
- Trigger the library in your build, which writes infrastructure code into your GitOps-repo.
- Set up the GitOps-tool, so it deploys the infrastructure code from your GitOps-repo.
At first you have to import the library. You can either use one of the following options:
library()
when the library is being loaded from a private git@Library
works out of the box with pipeline-github-lib plugin to load the library from github
First option can be used when the build-lib is mirrored or cloned onto your own git. You only need to provide the remote url and the desired version.
gitOpsBuildLib = library(identifier: "gitops-build-lib@<gitOpsBuildLibVersion>",
retriever: modernSCM([$class: 'GitSCMSource', remote: <gitOpsBuildLibRepo>])
).com.cloudogu.gitops.gitopsbuildlib
If you can access the internet or just dont want to mirror the repo you can just import it directly from github using the pipeline-github-lib plugin plugin.
@Library('github.com/cloudogu/gitops-build-lib@0.0.8')
import com.cloudogu.gitops.gitopsbuildlib.*
To utilize the library itself, there is little to do:
- Setup a
gitopsConfig
containing the following sections- properties (e.g. remote urls to scm, application, GitOps-tool, etc.)
- stages
- deployments
- validators
- fileConfigMaps
- Call
deployViaGitops(gitopsConfig)
Having the library write the configuration into your GitOps-repository is the first part. Next, make your GitOps-tool deploy it. Obviously this setup depends on the GitOps-tool used.
The library hides some implementation specifics of the individual tools. For example, for Flux, it creates HelmRelease
CRs, for argo it calls helm template
, see Helm.
You can make this library work with Flux v1 with the following steps:
- Create a repository in your SCM for the payload of your applications
- Configure the Flux operator to use this repository
- If you want to use Helm applications you will need a Helm operator because this library is creating
HelmRelease
CRs
See Example for operator configurations in GitOps Playground
See Example application with Flux v1
You can make this library work with your ArgoCD with the following steps:
- Create a repository in your SCM for the payload of your applications
- Add this repository to your ArgoCD configuration
- Add application definitions for the different stages of your application e.g. (your staging application):
apiVersion: argoproj.io/v1alpha1 kind: Application metadata: name: petclinic-staging namespace: argocd spec: destination: namespace: argocd-staging server: https://kubernetes.default.svc project: petclinic source: path: staging/spring-petclinic repoURL: http://scm/repo/gitops targetRevision: main directory: recurse: true syncPolicy: automated: {}
- Configure the payload repository through the
scm
key in your gitopsconfig
See Example of ArgoCD configuration in GitOps Playground
See Example of ArgoCD application in GitOps Playground
A default project structure in your application repo could look like the examples below. Make sure you have your k8s
and/or helm resources bundled in a folder. This specific resources folder (here k8s
) will later be specified by the
sourcePath
within the deployments section of your GitOpsConfig
.
├── application
├── config.yamllint.yaml // not necessarily needed
├── Jenkinsfile
└── k8s
├── production
│ ├── deployment.yaml
│ └── service.yaml
└── staging
├── deployment.yaml
└── service.yaml
├── application
├── config.yamllint.yaml // not necessarily needed
├── Jenkinsfile
└── k8s
├── production
│ ├── configMap.yaml
│ └── secrets
│ ├── secret2.yaml
│ └── secret.yaml
├── staging
│ ├── configMap.yaml
│ └── secrets
│ ├── secret2.yaml
│ └── secret.yaml
├── values-production.yaml
├── values-shared.yaml
└── values-staging.yaml
The GitOps-config is basically a groovy map following conventions to have a descriptive way of defining deployments. You can find a complete yet simple example here.
Properties
First of all there are some mandatory properties e.g. the information about your GitOps-repository, the application repository and the GitOps-tool to be used.
application: 'spring-petclinic'
- Name of the application. Used as a folder in GitOps-repogitopsTool: 'ARGO'
- Name of the GitOps tool. Currently supporting'FLUX'
(for now only fluxV1) and'ARGO'
.- and some optional parameters (below are the defaults) for the configuration of the dependency to the ces-build-lib or the default name for the git branch:
cesBuildLibRepo: 'https://github.com/cloudogu/ces-build-lib'
cesBuildLibVersion: '1.62.0'
mainBranch: 'main'
- Optional:
k8sVersion: '1.24.8'
Is used for target k8s version in helm template in Argo CD deployments with helm. Is also used to determine the kubectl version, when no specific buildImage is specified.
It is recommended to use a Jenkins environment variable to specify the version, so that you don't have to bump every pipeline after a k8s version upgrade in your cluster, e.g.
def gitopsConfig = [
k8sVersion: env.K8S_VERSION_TEAM_A
]
The GitOps-build-lib uses some docker images internally (To run Helm or Kubectl commands and specific Validators inside a docker container).
All of these have set default images, but you can change them if you wish to.
def gitopsConfig = [
buildImages: [
// These are used to run helm and kubectl commands in the core logic
helm: 'ghcr.io/cloudogu/helm:3.11.1-2',
// if you specify k8sVersion parameter, then by default bitnami/kubectl:${k8sVersion} will be used
kubectl: 'bitnami/kubectl:1.24.8',
// These are used for each specific validator via an imageRef property inside the validators config. See [Validators] for examples.
kubeval: 'ghcr.io/cloudogu/helm:3.11.1-2',
helmKubeval: 'ghcr.io/cloudogu/helm:3.11.1-2',
yamllint: 'cytopia/yamllint:1.25-0.9'
]
]
Optional - if image is in a private repository, you can pass a credentialsId
for pulling images.
def gitopsConfig = [
buildImages: [
helm: [
image: 'ghcr.io/cloudogu/helm:3.11.1-2',
credentialsId: 'myCredentials'
],
// ...
]
]
The GitOps-build-lib supports builds on multiple stages. A stage is defined by a name and contains a namespace (used to generate the resources) and a deployment-flag:
def gitopsConfig = [
stages: [
staging: [
namespace: 'staging',
deployDirectly: true
],
production: [
namespace: 'production',
deployDirectly: false
]
]
]
If it is set to deploy directly it will commit and push to your desired GitOps-folder
and therefore triggers a deployment. If it is set to false
it will create a PR on your GitOps-folder
. Remember there are important conventions regarding namespaces and the folder structure (see namespaces).
You need to specify a namespace for each stage for Helm deployments. For Plain you just need it if you add extra Files.
If no namespace is specified, the library uses the gitopsConfig.stages.${yourStage}
as the namespace. But beware if you use special characters then you need to use single ticks:
def gitopsConfig = [
stages: [
'xx-staging': [],
'xx-production': []
]
]
Otherwise every stage can be defined with an additional namespace
property:
def gitopsConfig = [
stages: [
staging: [
namespace: 'xx-staging'
],
production: [
namespace: 'xx-production'
]
]
]
Important note
Under your gitopsConfig.deployments.sourcePath
(here k8s
) the subfolders have to be named exactly as the stages
under gitopsConfig.stages
. The same applies to the values-*
files if you have a Helm application.
So if you have a config looking like:
def gitopsConfig = [
stages: [
'xx-staging': [],
'xx-production': []
]
]
Then your folder structure has to look like: For Plain:
├── application
├── config.yamllint.yaml // not necessarily needed
├── Jenkinsfile
└── k8s
├── xx-production
│ ├── deployment.yaml
│ └── service.yaml
└── xx-staging
├── deployment.yaml
└── service.yaml
For Helm:
├── application
├── config.yamllint.yaml // not necessarily needed
├── Jenkinsfile
└── k8s
├── xx-production
│ ├── {extraResources}
└── xx-staging
├── {extraResources}
├── values-shared.yaml
├── values-xx-production.yaml
├── values-xx-staging.yaml
Or if you use namespaces:
def gitopsConfig = [
stages: [
staging: [
namespace: 'xx-staging'
],
production: [
namespace: 'xx-production'
]
]
]
Then your folder structure has to look like:
For Plain:
├── application
├── config.yamllint.yaml // not necessarily needed
├── Jenkinsfile
└── k8s
├── production
│ ├── deployment.yaml
│ └── service.yaml
└── staging
├── deployment.yaml
└── service.yaml
For Helm:
├── application
├── config.yamllint.yaml // not necessarily needed
├── Jenkinsfile
└── k8s
├── production
│ ├── {extraResources}
└── staging
├── {extraResources}
├── values-shared.yaml
├── values-production.yaml
├── values-staging.yaml
- Stage name is used to identify the yamls to be used:
${deployments.sourcePath}/values-<stage>.yaml
+${deployments.sourcePath}/values-shared.yaml
For now we only support onevalues-shared.yaml
which will be used for all namespaces and one additional values file for each namespacevalues-${stage}.yaml
The deployment has to contain the path of your k8s resources within the application and either a config section for plain-k8s
resources or for helm
resources.
def gitopsConfig = [
deployments: [
sourcePath: 'k8s', // path of k8s resources in application repository. Default: 'k8s'
destinationRootPath: '.', // Root-Subfolder in the gitops repository, where the following folders for stages and apps shall be created. Default: '.'
// Either "plain" or "helm" is mandatory
plain: [], // use plain if you only have, as the name suggests, plain k8s resources
helm: [] // or if you want to deploy a helm release use `helm`
]
You can utilize the build-lib to enable builds based on plain k8s resources
def gitopsConfig = [
deployments: [
plain: [
updateImages: [
[
filename: "deployment.yaml", // the files need to be in the gitopsConfig.deployments.sourcePath folder and in each of their own namespace folder e.g. k8s/staging/deployment.yaml
containerName: 'application',
imageName: 'imageName'
]
]
]
]
]
In plain pipelines, the library creates the deployment resources by updating the image tag within the deployment.
Note that this works with Kubernetes Deployment
s, StatefulSet
s and CronJob
s. For all other kinds of resources the
library tries to find the containers
at the following YAML path: spec.template.spec.containers
. This might fail, of course. If you encounter a case
like this, please create an issue. Eventually, we're planning to provide a fieldPath
option just like in helm releases.
Besides plain k8s resources you can also use helm charts to generate the resources. You can choose between these types of helm-repository-types:
- Helm Repository
- Git Repository
- Local
The repoType: HELM
, which is used to load tgz from helm-repositories.
def gitopsConfig = [
deployments: [
helm: [
repoType: 'HELM',
repoUrl: 'https://charts.bitnami.com/bitnami',
credentialsId: 'creds',
version: '7.1.6',
chartName: 'nginx',
updateValues: [[fieldPath: "image.name", newValue: imageName]]
]
]
]
The repoType: GIT
can be used to load charts from a specific Git-Repository.
def gitopsConfig = [
deployments: [
helm: [
repoType: 'GIT',
repoUrl: "https://git-repo/namespace/name", // git-repo must have a 'main' branch due to limitations of the git-step within jenkins
credentialsId: 'creds',
version: '1.2.3', // tag, commit or branch
chartPath: 'chart', // the path relative to root in the git repo. If the chart is at root level you can ommit this property
updateValues: [[fieldPath: "image.name", newValue: imageName]]
]
]
]
Note:
Due to limitations in the git-step of Jenkins, we have to clone from a specific branch rather then having the
git client checkout the default branch given within the HEADs meta information. This specific branch is the
main
branch. Make sure the git-repository has a main-branch, else the deployment step will fail. After a successful clone
it checks out the given version as expected.
The repoType: LOCAL
can be used if you store the helm repository locally, i.e. in the same Git Repository where your Jenkins Job runs from.
A common pattern used in this context would be the "Umbrella pattern".
def gitopsConfig = [
deployments: [
helm : [
repoType : 'LOCAL',
chartPath: 'helm/chart' /* Must be relative to jenkins WORKSPACE */,
updateValues: [[fieldPath: "image.name", newValue: imageName]]
]
]
]
-
Application name is used as the release-name in Flux (not for argo, argo creates plain resources using
helm template
)Helm Release name =
${application}
-
Extra k8s resources can also be deployed if you choose to have a Helm deployment
extraResources get copied into the GitOps-folder without being changed - can be used e.g. sealed-secrets extraResources are always relative to the
${gitopsConfig.deployments.sourcePath}/${stage}
, you can specify files or directoriese.g. in stage production =>
copies '/k8s/production/configMap.yaml' and '/k8s/production/secrets' to the GitOps-folder where every k8s resource in ./secrets will be copied to the GitOps-folder
We decided to generate plain k8s Resources from Helm applications before we push it to the GitOps-Repository for the following reasons:
- With ArgoCD you can only set one source for your application. In case of helm it is common to have a source Repository for your chart and a scource Repository for your configuration files (values.yaml). In order to use two different sources for your helm application you will need some sort of workaround (e.g. Helm dependencies in
Chart.yaml
). - ArgoCD itself uses
helm template
to apply plain k8s Resources to the cluster. By templating the helm application before pushing to the GitOps-repository, we have the same resources in our repository as in our cluster. Which leads to increased transparency. The parameterk8sVersion
from the GitOps-config is used as a parameter with--kube-version
in order to template version-specific manifests such as changed api versions.
You can customize in which path the final manifests of the application will be created in the GitOps-repository. For this, you can modify the following parameters:
def gitopsConfig = [
deployments: [
destinationRootPath: '.' /* Default: '.' */
],
folderStructureStrategy: 'GLOBAL_ENV' /* Default: 'GLOBAL_ENV', or ENV_PER_APP */
]
destinationRootPath
: Specifies in which subfolder the following folders offolderStructureStrategy
are created. Defaults to the root of the repository.folderStructureStrategy
: Possible values:GLOBAL_ENV
: The manifests will be commited into$DESTINATION_ROOT_PATH/STAGE_NAME/APP_NAME/
in the destination GitOps-repositoryENV_PER_APP
: The manifests will be commited into$DESTINATION_ROOT_PATH/APP_NAME/STAGE_NAME/
in the destination GitOps-repository
Example for Global Environments vs Environment per App (Source):
If extra files are needed and are not k8s resources there is the fileConfigMaps
property.
def gitopsConfig = [
fileConfigmaps: [
[
name : "index",
sourceFilePath : "../index.html", // relative to deployments.sourcePath
stage: ["staging", "production"] // these have to match the `gitopsConfig.stages`
]
]
]
This will generate a k8s ConfigMap with the content of this file as data:
Name: index
Namespace: staging │
Data
====
index.html:
----
<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes">
<title>k8s-gitops-playground</title>
</head>
<body>
<h2>Hello cloudogu gitops playground!</h2>
</body>
</html>
The scm-section defines where your 'GitOps-repository' resides (url, provider) and how to access it (credentials):
def gitopsConfig = [
...
scm: [
provider: 'SCMManager', // This is the name of the scm-provider in use, for a list of supported providers watch below!
credentialsId: 'scmm-user', // ID of credentials defined in Jenkins used to authenticated with SCMM
baseUrl: 'http://scmm-scm-manager/scm', // this is your gitops base url
repositoryUrl: 'fluxv1/gitops' // this is the gitops repo
],
...
]
It currently supports the following scm-provider:
To empower people to participate and encourage the integration of other scm-software (e.g. github), we decided to implement an abstraction for the scm-provider. By extending the SCM-Provider class you can integrate your own provider! Please feel free to contribute!
Example:
import com.cloudogu.gitopsbuildlib.scm.SCMProvider
class GitHub extends SCMProvider {
@Override
void setBaseUrl(String baseUrl) { this.baseUrl = baseUrl }
@Override
void setRepositoryUrl(String repositoryUrl) { this.repositoryUrl = repositoryUrl }
@Override
void setCredentials(String credentialsId) { this.credentials = credentialsId }
@Override
String getRepositoryUrl() { return "${this.baseUrl}/${repositoryUrl}"}
@Override
void createOrUpdatePullRequest(String stageBranch, String mainBranch, String title, String description) {
// TODO: this is a specific implementation for github
// 1. creating a pr on the given repo with the given details
// 2. update a pr on the given repo if it already exists
//
// Note: Credentials given are credentialsId from Jenkins!
}
}
The library itself provides three validators yamllint
, kubeval
and helmKubeval
to validate the generated resources.
You can disable the built-in operators and/or add your own.
The operators are processed sequentially in no particular order.
Example: Disable all built-ins and add a custom validator.
node {
stage('Deploy') {
def gitopsConfig = [
// ...
validators : [
yamllint: [
enabled : false,
],
kubeval: [
enabled : false,
],
myVali: [
validator: new MyValidator(this),
enabled : true,
config : [
some: 'thing'
]
]
]
]
deployViaGitops(gitopsConfig)
}
}
Each Validator has a property called imageRef
and image
inside the config
property.
imageRef
's value defaults to the key in the buildImages
property and will replace the key-name with the actual image corresponding to the value.
def gitopsConfig = [
validators: [
kubeval: [
enabled: true,
config: [
imageRef: 'kubeval' // this corresponds to the key/value pair in buildImages which internally will become imageRef: 'ghcr.io/cloudogu/helm:3.5.4-1'
]
]
]
]
If you wish to change the image, you can do so by changing the image in the corresponding key/value pair in buildImages
or by setting the image directly via the image
property.
First, the library will check if the image
property is set and if so, will use its value as the image.
def gitopsConfig = [
validators: [
kubeval: [
enabled: true,
config: [
image: 'ghcr.io/cloudogu/helm:3.5.4-1'
]
]
]
]
If the image
value is not set, it resorts to the imageRef
property.
The library offers a convenient base class com.cloudogu.gitops.gitopsbuildlib.Validator
.
However, this seems impossible to use with neither dynamic library loading via the library()
nor with @Library
,
because the library is loaded after the class is evaluated.
If you need to use library()
or @Library
then your validator needs to implement the following three methods:
void validate(boolean enabled, String targetDirectory, Map config)
SourceType[] getSupportedSourceTypes()
GitopsTool[] getSupportedGitopsTools()
import com.cloudogu.gitopsbuildlib.deployment.GitopsTool
import com.cloudogu.gitopsbuildlib.deployment.SourceType
class MyValidator extends Validator {
MyValidator(def script) {
super(script)
}
@Override
void validate(boolean enabled, String targetDirectory, Map validatorConfig, Map gitopsConfig) {
script.echo "Enabled: $enabled; targetDirectory: $targetDirectory; validatorConfig: $validatorConfig; gitopsConfig: $gitopsConfig"
}
@Override
SourceType[] getSupportedSourceTypes() {
return [SourceType.HELM, SourceType.PLAIN]
}
@Override
GitopsTool[] getSupportedGitopsTools() {
return [GitopsTool.ARGO, GitopsTool.FLUX]
}
}
In general a custom validator may implement the Validator class. You therefore have to implement the following methods:
void validate(boolean enabled, String targetDirectory, Map config)
- Here lies your validation code or the entrypoint for more complex validation processes
SourceType[] getSupportedSourceTypes()
- This method returns a collection of supported Source Types.
The SourceType determines which resources are going to be validated. There are two locations where resources can be validated.
They are differentiated by the resource-type of which there are two right now.- Helm resources
- Plain k8s resources
Visual representation of the folder structure on the Jenkins agent
├── jenkinsworkdir/
└── .configRepoTempDir/
└── ${stage}/
└── ${application}/
├── extraResources/
├── generatedResources/
├── deployment.yaml
└── ...
└── .helmChartTempDir/
└── chart/
└── ${chartPath}/ (for git repo) or ${chartName}/ (for helm repo)
└── mergedValues.yaml
Helm resources - .helmChartTempDir
:
This location is only temporary and is being used for the helm chart to be downloaded and the mergedValues.file (values-shared.yaml + values-${stage}.yaml)
Only Validators which support Helm schemas should operate on this folder
Plain k8s resources - .configRepoTempDir
:
This location is for your plain k8s resources. This folder is also the GitOps-folder which will be pushed to the scm.
It contains your k8s resources in the root and two extra folders for additional k8s resources:
extraResources
: Only needed for a Helm deployment if you whish to deploy plain k8s resources in addition to the helm deployment. See: Important note in Namespaces
generatedResources
: If you have files which need to be deployed as a configMap. See: Extra Files
GitopsTool[] getSupportedGitopsTools()
This determins on which GitopsTool the validator will run. We implemented this feature since Argo already uses helm template
and kubeval
internally so we don't need helm kubeval
since it does exactly the same.
So we defined HelmKubeval
as only needed to be executed on a FLUX
operator.
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