T4K GitHub Runner

Why?
IAC is very important in Kubernetes Streamline ops from dev to production as much as possible. You want runners that can automate tasks around application development and delivery T4K has built a runner for GH that can do the following**.**
Assumptions
1.Source and destination kubernetes clusters are setup
2.T4K installed on the source and destination clusters with appropriate licenses
3.A backup location is created and available for use
High-level Steps with Flowchart
High Level Data Flow for T4K GitHub Runner
Pre-requisites
In order to get started with the T4K runner ensure the following prerequisites are met:
1.Install T4K on the source and destination clusters with appropriate licenses
2.Ensure a backup location is created and available for use.
System Setup
Ref. Link - **** https://github.com/actions-runner-controller/actions-runner-controller​
1.actions-runner-controller uses cert-manager for certificate management of Admission Webhook. Install cert-manager using below command:$ kubectl apply -f https://github.com/jetstack/cert-manager/releases/download/v1.3.1/cert-manager.yaml
2.Install the custom resource and actions-runner-controller with kubectl. This will create actions-runner-system namespace in the Kubernetes cluster and deploy the required resources.
$ kubectl apply -f https://github.com/actions-runner-controller/actions-runner-controller/releases/download/v0.18.2/actions-runner-controller.yaml
3.Setup authentication for actions-runner-controller to authenticate with GitHub using PAT (Personal Access Token). Personal Access Tokens can be used to register a self-hosted runner by actions-runner-controller.
1.Log-in to a GitHub account that has admin privileges for the repository, and create a personal access token with the appropriate scopes listed below:
1.Required Scopes for Repository Runners : repo (Full control)
4.Deploy the token as a secret to the Kubernetes cluster $ GITHUB_TOKEN="<token>"
$ kubectl create secret generic controller-manager -n actions-runner-system --from-literal=github_token=${GITHUB_TOKEN}
5.Deploy a repository runner
1.Create a manifest file including Runner resource as follows:
# runner.yaml
apiVersion: actions.summerwind.dev/v1alpha1
kind: Runner
metadata:
name: example-runner
spec:
repository: summerwind/actions-runner-controller
env: []\
2.Apply the created manifest file to your Kubernetes
$ kubectl apply -f runner.yaml runner.actions.summerwind.dev/example-runner created
3.You can see that the Runner resource has been created
$ kubectl get runners
NAME REPOSITORY STATUS
example-runner summerwind/actions-runner-controller Running
4.You can also see that the runner pod has been running
$ kubectl get pods
NAME READY STATUS RESTARTS AGE
example-runner 2/2 Running 0 1m
5.The runner you created has been registered to your repository
Executing the Runners
1.Create a workflow with 2 jobs - Backup and Restore
2.User Inputs:
1.kubeconfig files for source and destination clusters
2.Load the user input variables in the “.env”-
1.Backup target name and namespace on source cluster
2.Namespace to be backed up
3.Backup target name and namespace on destination cluster
4.Namespace to be used for restore
3.Workflow triggers - set appropriate triggers for the job to run
4.The workflow run is made up of Backup and Restore jobs that run sequentially
5.Backup job details:
1.runs-on: self-hosted
2.Setup the environment
1.install kubectl
2.Load kubeconfig files for source and destination clusters
3.Load the user inputs -
1.Backup target name and namespace on source cluster
2.Namespace to be backed up
3.Backup target name and namespace on destination cluster
4.Namespace to be used for restore
3.Create a backup plan
4.Perform backup
5.Capture the backup location that will be needed for the restore on destination cluster
6.Restore job details:
1.runs-on: self-hosted
2.Setup the environment
1.install kubectl
2.Load kubeconfig files for source and destination clusters
3.Load the user inputs -
1.Backup target name and namespace on source cluster
2.Namespace to be backed up
3.Backup target name and namespace on destination cluster
4.Namespace to be used for restore
3.Perform restore using the location of the backup
Extending the runner
1.The workflow can be extended to support additional destination clusters to cover several environments as part of the test cases.
2.Different storage classes that may be in use in the source and destination clusters are supported via T4K transforms.
3.Automation activities - can extend the runners to handle an array of applications instead of specific ones
Conclusion
With the advent of technology and proliferation of multiple software technologies, automation is key for success. Automation can only be possible via IAC. With the rise and mainstream adoption of Kubernetes, microservices and IAC is the future. Any technology entering the IT market must enable operations and control via code. Trilio is a purpose-built solution providing point-in-time orchestration for cloud-native applications. Trilio is able to support the application lifecycle from Day 0 to Day 2 by enabling the respective personas to perform their objectives leveraging IAC.\
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Last modified 22h ago