kubectl commands for managing Flokoa resources

# List agents in the current namespace
kubectl get agents

# List agents in a specific namespace
kubectl get agents -n my-namespace

# List agents across all namespaces
kubectl get agents --all-namespaces

# Show full details including status conditions
kubectl describe agent my-agent

# Print the full manifest as YAML
kubectl get agent my-agent -o yaml

# Stream status changes in real time
kubectl get agents -w

# Check the agent's current lifecycle phase (Pending / Running / Failed)
kubectl get agent my-agent -o jsonpath='{.status.phase}'

# Retrieve the stable in-cluster URL for the agent
kubectl get agent my-agent -o jsonpath='{.status.url}'

# Scale the number of replicas
kubectl patch agent my-agent --type='json' \
  -p='[{"op": "replace", "path": "/spec/runtime/spec/replicas", "value": 3}]'

# Update the container image
kubectl patch agent my-agent --type='json' \
  -p='[{"op": "replace", "path": "/spec/runtime/spec/container/image", "value": "new-image:v2.0.0"}]'

# Open the manifest in your default editor
kubectl edit agent my-agent

# Delete an agent (also removes the managed Deployment and Service)
kubectl delete agent my-agent

# List all ModelProviders
kubectl get modelproviders

# List all Models
kubectl get models

# Check whether a ModelProvider has successfully loaded its credentials
kubectl get modelprovider openai-provider -o jsonpath='{.status.ready}'

# Check whether a Model has been resolved and is ready for use
kubectl get model gpt-4o -o jsonpath='{.status.ready}'

# Show full details and conditions for a provider
kubectl describe modelprovider openai-provider

# Show full details and conditions for a model
kubectl describe model gpt-4o

# Adjust a model parameter (e.g. raise temperature)
kubectl patch model gpt-4o --type='json' \
  -p='[{"op": "replace", "path": "/spec/parameters/temperature", "value": "0.8"}]'

# Rotate an API key by updating the underlying Secret in place
kubectl create secret generic openai-credentials \
  --from-literal=api-key=sk-proj-new-key \
  --dry-run=client -o yaml | kubectl apply -f -

# List all AgentTools in the current namespace
kubectl get agenttools

# Show full details including status conditions
kubectl describe agenttool weather-api

# List the tool references configured on a specific agent
kubectl get agent my-agent -o jsonpath='{.spec.tools[*].toolRef.name}'

# Increase the HTTP timeout for a tool (in seconds)
kubectl patch agenttool weather-api --type='json' \
  -p='[{"op": "replace", "path": "/spec/openApi/timeoutSeconds", "value": 60}]'

# Delete a tool (agents referencing it will log resolution warnings)
kubectl delete agenttool weather-api

# Find the pods backing a specific agent
kubectl get pods -l flokoa.ai/agent=my-agent

# Print logs from the most recent pod
kubectl logs -l flokoa.ai/agent=my-agent

# Follow logs from all replicas in real time
kubectl logs -l flokoa.ai/agent=my-agent -f --all-containers

# Open a shell in a running agent pod
kubectl exec -it <pod-name> -- /bin/sh

# Forward the agent's service port to your local machine for ad-hoc testing
kubectl port-forward svc/my-agent 8080:8080

# List Kubernetes events related to a specific agent resource
kubectl get events --field-selector involvedObject.name=my-agent

# View recent events sorted by time (useful for spotting ImagePullBackOff, etc.)
kubectl get events --sort-by='.lastTimestamp'

# Inspect the operator's own logs for reconciliation errors
kubectl logs -n flokoa-system -l control-plane=controller-manager

# Follow operator logs in real time
kubectl logs -n flokoa-system -l control-plane=controller-manager -f

# Check live CPU and memory consumption for agent pods
kubectl top pods -l flokoa.ai/agent=my-agent

kubectl get agent my-agent -o jsonpath='{.status.availableReplicas}'
kubectl get agent my-agent -o jsonpath='{.status.conditions[?(@.type=="Ready")].message}'