nlamirault / k8sgpt-operator

Automatic SRE Superpowers within your Kubernetes cluster

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.

Installation

helm repo add k8sgpt https://charts.k8sgpt.ai/
helm install release k8sgpt/k8sgpt-operator -n k8sgpt-operator-system --create-namespace

Run the example

1. Install the operator from the Installation section.

2. Create secret:

kubectl create secret generic k8sgpt-sample-secret --from-literal=openai-api-key=$OPENAI_TOKEN -n k8sgpt-
operator-system

3. Apply the K8sGPT configuration object:

kubectl apply -f - << EOF
apiVersion: core.k8sgpt.ai/v1alpha1
kind: K8sGPT
metadata:
  name: k8sgpt-sample
  namespace: k8sgpt-operator-system
spec:
  model: gpt-3.5-turbo
  backend: openai
  noCache: false
  version: v0.3.0
  enableAI: true
  # filters:
  #   - Ingress
  secret:
    name: k8sgpt-sample-secret
    key: openai-api-key
EOF

4. 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 in your cluster):

❯ 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.",

LocalAI Example

1. Install the operator from the Installation section.

2. Follow the LocalAI installation guide to install LocalAI. (No OpenAI secret is required when using LocalAI).

3. Apply the K8sGPT configuration object:

kubectl apply -f - << EOF
apiVersion: core.k8sgpt.ai/v1alpha1
kind: K8sGPT
metadata:
  name: k8sgpt-local-ai
  namespace: default
spec:
  model: gpt-3.5-turbo
  backend: localai
  noCache: false
  version: v0.3.0
  enableAI: true
EOF

4. Same as step 4. in the example above.

Architecture

Helm values

Here is an example of some of the values that can be configured. For more details please see here

Parameter	Description	Default
serviceMonitor.enabled	Enable Prometheus Operator ServiceMonitor	false
controllerManager.manager.image.repository	Image repository	k8sgpt/k8sgpt-operator
controllerManager.manager.image.pullPolicy	Image pull policy	IfNotPresent
controllerManager.manager.imagePullSecrets	Image pull secrets	[]