This Operator is designed to enable K8sGPT within a Kubernetes cluster. It will allow you to create a custom resource that defines the behaviour and scope of a managed K8sGPT workload. Analysis and outputs will also be configurable to enable integration into existing workflows.
helm repo add k8sgpt https://charts.k8sgpt.ai/
helm install release k8sgpt/k8sgpt-operator
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Install the operator from the Installation section.
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Create secret:
kubectl create secret generic k8sgpt-sample-secret --from-literal=openai-api-key=$OPENAI_TOKEN -n default- Apply the K8sGPT configuration object:
kubectl apply -f - << EOF
apiVersion: core.k8sgpt.ai/v1alpha1
kind: K8sGPT
metadata:
name: k8sgpt-sample
spec:
namespace: default
model: gpt-3.5-turbo
backend: openai
noCache: false
version: v0.2.7
enableAI: true
secret:
name: k8sgpt-sample-secret
key: openai-api-key
EOF- Once the custom resource has been applied the K8sGPT-deployment will be installed and you will be able to see the Results objects of the analysis after some minutes ( if there are any issues):
❯ kubectl get results -o json | jq .
{
"apiVersion": "v1",
"items": [
{
"apiVersion": "core.k8sgpt.ai/v1alpha1",
"kind": "Result",
"metadata": {
"creationTimestamp": "2023-04-26T09:45:02Z",
"generation": 1,
"name": "placementoperatorsystemplacementoperatorcontrollermanagermetricsservice",
"namespace": "default",
"resourceVersion": "108371",
"uid": "f0edd4de-92b6-4de2-ac86-5bb2b2da9736"
},
"spec": {
"details": "The error message means that the service in Kubernetes doesn't have any associated endpoints, which should have been labeled with \"control-plane=controller-manager\". \n\nTo solve this issue, you need to add the \"control-plane=controller-manager\" label to the endpoint that matches the service. Once the endpoint is labeled correctly, Kubernetes can associate it with the service, and the error should be resolved.",
Please see our community contributing guidelines for more information on how to get involved.