clanker k8s ask

Ask natural language questions about your Kubernetes cluster using AI

Ask natural language questions about your Kubernetes cluster using AI. The AI analyzes your question, executes the necessary kubectl operations, and provides a comprehensive markdown-formatted response.

Usage

clanker k8s ask [question] [flags]

Arguments

question · string · required

Natural language question about your Kubernetes cluster

Flags

--cluster · string

Kubernetes cluster name (EKS or GKE cluster name)

--profile · string

AWS profile for EKS clusters

--kubeconfig · string

Path to kubeconfig file (default: ~/.kube/config)

--context · string

kubectl context to use (overrides —cluster)

-n, --namespace · string

Default namespace for queries (default: all namespaces)

--ai-profile · string

AI profile to use for LLM queries

--debug · boolean

Enable debug output

--gcp · boolean

Use GKE cluster instead of EKS

--gcp-project · string

GCP project ID for GKE clusters

--gcp-region · string

GCP region for GKE clusters

How it works

The k8s ask command uses a three-stage AI pipeline:

1. Analysis: The AI analyzes your question and determines what kubectl operations are needed
2. Execution: The necessary kubectl commands are executed against your cluster
3. Response: The AI synthesizes the results into a comprehensive, markdown-formatted answer

Conversation history is maintained per cluster, allowing for follow-up questions that reference previous context.

Examples

Basic cluster information

clanker k8s ask "how many pods are running"

Output

## Running Pods

Your cluster currently has **12 pods** running across all namespaces:

- **default**: 3 pods
- **kube-system**: 8 pods
- **monitoring**: 1 pod

All pods are in a healthy state.

Query specific resources

clanker k8s ask --cluster test-cluster --profile myaws "show me all deployments"

clanker k8s ask "which pods are using the most memory"

Output

## Top Memory Consumers

Here are the pods using the most memory in your cluster:

1. **redis-master-0** (default): 512Mi
2. **postgres-primary-0** (database): 384Mi
3. **nginx-ingress-controller** (kube-system): 256Mi

The redis-master pod is consuming the most memory at 512Mi.

Troubleshooting

clanker k8s ask "why is my pod crashing"

Output

## Pod Crash Analysis

I found a pod in CrashLoopBackOff state:

**Pod**: my-app-abc123-xyz
**Namespace**: default
**Restarts**: 5

### Recent Logs

Health checks

clanker k8s ask "tell me the health of my cluster"

Output

## Cluster Health Report

### Overall Status: Healthy ✓

**Nodes**: 3/3 Ready
- ip-10-0-1-100: Ready (CPU: 12%, Memory: 38%)
- ip-10-0-1-101: Ready (CPU: 9%, Memory: 29%)
- ip-10-0-1-102: Ready (CPU: 15%, Memory: 42%)

**Pods**: 45/45 Running
- 0 Pending
- 0 Failed
- 0 CrashLoopBackOff

**System Components**:
- CoreDNS: Healthy
- kube-proxy: Running on all nodes
- CNI: Operational

Your cluster is operating normally with no issues detected.

GKE cluster queries

clanker k8s ask --gcp --gcp-project my-project --cluster my-gke-cluster "show me all pods"

Follow-up questions

The conversation history allows natural follow-ups:

clanker k8s ask "how many nodes are in the cluster"
# Response: "Your cluster has 3 nodes..."

clanker k8s ask "what about their CPU usage"
# Response references previous context about the 3 nodes

Error investigation

clanker k8s ask "give me error logs for nginx pod"

Resource recommendations

clanker k8s ask "are any pods over-utilizing resources"

The AI maintains conversation history per cluster, so you can ask follow-up questions that reference previous queries. For example, after asking “show me all pods”, you can ask “which one is using the most CPU” without re-specifying the context.

The k8s ask command requires:

• Valid kubeconfig or access to the specified cluster
• AI provider configured in your Clanker settings
• For EKS: AWS credentials with appropriate permissions
• For GKE: GCP credentials with appropriate permissions