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AI Features

KubeStellar Console uses AI to help you manage your clusters. Think of it as having a helpful assistant who knows Kubernetes.

AI Missions Panel
AI Missions Panel

AI Missions

AI Missions are conversations with AI to solve problems. Click the mission button in the bottom right to start.

What Can You Do?

Mission TypeWhat it does
TroubleshootFind out why something is broken
AnalyzeUnderstand what’s happening
RepairFix problems automatically
UpgradePlan and execute upgrades
DeployHelp deploy applications

How It Works

  1. Click “AI Missions” button (bottom right)
  2. Choose a mission type or describe your problem
  3. AI asks questions to understand the issue
  4. AI runs commands and analyzes results
  5. AI suggests fixes or takes action
  6. You approve or reject the suggestions

Example: Troubleshooting a Crash

You: “Why is my nginx pod crashing?”

AI: “Let me check. I found the pod nginx-abc123 in namespace default is in CrashLoopBackOff. Looking at the logs…

The container is failing because it can’t bind to port 80. There’s already a process using that port.

Suggestion: Change the container port to 8080 or remove the conflicting service.”

Mission Panel Features

  • Full screen - Expand for more space
  • Minimize - Hide while AI works
  • Collapse - Show just the title
  • Multiple missions - Run several at
  • Token tracking - See how many tokens used

Mission Browser

The Mission Browser lets you discover, install, and share pre-built AI missions from a curated knowledge base. Access it from the AI Missions sidebar.

Installers & Solutions Tabs

The browser is organized into two tabs:

  • Installers — Pre-packaged missions for setting up tools and infrastructure (e.g., install Prometheus, deploy Gatekeeper, set up GitOps). Each installer card shows the CNCF category, author avatar, and a-click install button.
  • Solutions — Higher-level solutions that combine multiple components to solve common problems (e.g., “Full observability stack”, “Zero-trust network policies”).

Cards load progressively as they are fetched from the knowledge base, so you see results immediately rather than waiting for all missions to load.

Recommendations

The browser shows personalized recommendations based on your cluster configuration and installed tools. Each recommendation explains why it’s suggested — for example, “Recommended because you have GPU nodes but no monitoring” or “Your clusters use Helm but lack drift detection.”

Token Guidance Banner

A banner at the top of the Mission Browser shows estimated token usage for browsing and installing missions, helping you budget AI costs.

Sharing Missions

You can share missions with your team:

  1. Click the Share button on any mission
  2. Choose to share via link, export as JSON, or push to a repository
  3. Security scanning runs automatically before sharing to detect sensitive data

Importing Missions

Import missions from external sources:

  1. Click Import in the Mission Browser
  2. Paste a mission JSON, URL, or select from a repository
  3. The browser suggests matching missions from the knowledge base
  4. Preview before importing to your dashboard

AI Diagnose

Every card has an “Ask AI” button. Click it to get AI analysis of that specific data.

How to Use

  1. Look at any card
  2. Click the AI icon (brain/sparkle)
  3. AI analyzes the card data
  4. Get insights and suggestions

What AI Can Tell You

  • Why metrics look unusual
  • What’s causing issues
  • How to fix problems
  • What to watch out for
  • Historical context

Example

Card: Cluster Health showing 2 clusters offline

AI: “I see 2 clusters are offline. Let me check…

  • cluster-1: Network timeout - likely a firewall issue
  • cluster-2: Certificate expired 2 hours ago

Suggestions:

  1. Check VPN connection for cluster-1
  2. Renew certificate for cluster-2 with kubectl certificate approve”

AI Repair

When AI diagnoses a problem, it can often fix it automatically.

How Repair Works

  1. AI identifies the problem
  2. AI creates a fix
  3. You review the fix
  4. You approve or reject
  5. AI applies the fix

Safety First

  • AI always asks before making changes
  • You see exactly what will change
  • You can reject any action
  • Changes are logged

What AI Can Repair

  • Pod issues - Restart stuck pods, fix resource limits
  • Certificate problems - Approve pending certificates
  • Configuration errors - Fix ConfigMaps and Secrets
  • Scaling issues - Adjust replica counts
  • Resource quotas - Suggest adjustments

Custom AI Missions

You can create your own AI missions to investigate any problem or perform any task.

Starting a Custom Mission

  1. Click “AI Missions” button (bottom right)
  2. Click “Start Custom Mission”
  3. Type your question or task in plain English
  4. Press Cmd+Enter to submit
Custom Mission
Custom Mission

Example Custom Missions

  • “Find pods with high memory usage and suggest optimization”
  • “Check why my deployment is failing on cluster-2”
  • “Analyze network policies across all namespaces”
  • “Help me set up GPU reservations for my ML team”

Search-Based Missions

You can also start missions from the global search bar:

  1. Press Cmd/Ctrl + K to open search
  2. Type your question
  3. Select “Start AI Mission” from the results

Resolution History

AI missions automatically save their problem/solution pairs so you can reuse them later. This saves tokens and time by avoiding repeated analysis of the same issues.

How It Works

  1. When an AI mission diagnoses and resolves a problem, the resolution is saved
  2. The resolution includes the problem description, root cause, and solution steps
  3. Future missions can reference past resolutions for similar issues

Viewing Resolution History

  • Navigate to the Deploy dashboard to see Deployment Missions with resolution status
  • Each resolution shows whether it’s been applied (“In Orbit” for deployed fixes)
  • Click any resolution to see the full problem/solution details

Resolution Tabs

Resolutions are organized by status:

  • All - Every resolution recorded
  • Applied - Fixes that were successfully deployed
  • Pending - Suggested fixes awaiting approval
  • Archived - Past resolutions for reference

Sharing Resolutions

Resolutions are stored with the console and available to all users, enabling team knowledge sharing. When a team member solves a problem, the solution is available for everyone.

Predictive Failure Detection

AI-powered prediction system that detects potential node and GPU failures before they happen.

Predictive Health Monitor
Predictive Health Monitor

How It Works

  1. AI continuously analyzes cluster health data (CPU, memory, disk, network patterns)
  2. Detects anomalous patterns that correlate with past failures
  3. Generates predictions with confidence levels
  4. Alerts you before failures occur

Configuration

Configure in Settings > AI & Intelligence > Predictions:

  • AI Predictions - Toggle prediction analysis on/off
  • Analysis Interval - How often to run (15 min to 2 hours, default 30 min)
  • Minimum Confidence - Threshold for showing predictions (50% to 90%, default 60%)
  • Multi-Provider Consensus - Run analysis on multiple AI providers for higher confidence

Prediction Cards

The Predictive Health Monitor card on the Clusters dashboard shows:

  • Offline count - Currently offline nodes
  • GPU Issues count - GPU nodes with problems
  • Predicted count - Nodes predicted to have issues soon
  • Issue list with severity, confidence, cluster, and correlated patterns

Root Cause Analysis (RCA)

When the AI detects an issue or predicts a failure, it provides root cause analysis:

  • Pattern correlation - Links symptoms to likely causes (e.g., “restart pattern detected - crashes correlate with traffic spikes”)
  • Resource trending - “Memory usage trending upward, may hit limits in ~2 hours”
  • Historical comparison - Compares current patterns to past incidents

Heuristic Thresholds

Fine-tune detection sensitivity with heuristic thresholds for:

  • Memory pressure
  • CPU saturation
  • Disk I/O anomalies
  • Network connectivity patterns
  • Pod restart frequency

Smart Suggestions

AI watches how you use the console and suggests improvements.

Card Swap Suggestions

When AI notices you’re focusing on different things:

  1. AI detects focus change
  2. Shows a suggestion with countdown
  3. You can:
    • Accept - Swap to the new card
    • Snooze - Hide for 1 hour
    • Keep - Stay with current card
    • Cancel - Dismiss suggestion

What Triggers Suggestions?

  • Spending time on a specific card
  • Clicking into details repeatedly
  • Issues appearing in your clusters
  • Changes in cluster state

Example

You’ve been looking at pod issues for 5 minutes

AI Suggestion: “I notice you’re focused on pod issues. Would you like to swap the Cluster Metrics card for a Pod Health Trend card?”

AI Card Creation

You can create brand new cards just by describing what you want. This is the Card Factory feature.

How to Create a Card with AI

  1. Open the Card Factory (from the add card menu)
  2. Choose “Describe with AI”
  3. Type what you want in plain English
  4. AI builds the card
  5. Preview it and add to your dashboard

Example

You type: “Show me a card that displays the top 5 pods by memory usage with a bar chart”

AI creates: A custom bar chart card showing your top pods ranked by memory, updating in real time.

What You Can Create

  • Custom metric views for your specific needs
  • Charts and tables with your own filters
  • Cards that combine data from multiple sources
  • Specialized views for your team’s workflow

Other Ways to Create Cards

If you prefer code, the Card Factory also accepts:

  • JSON definitions - Declarative card configuration
  • TSX code - Full React components (compiled at runtime)

Provider Health Monitoring

The Provider Health card shows you the status of AI services and cloud providers your console depends on.

What It Shows

  • Claude (Anthropic) - Status and availability
  • OpenAI - Status and availability
  • Gemini (Google) - Status and availability
  • Cloud providers - AWS, Azure, GCP status

Why It Matters

If AI features stop working or respond slowly, check the Provider Health card first. It tells you whether the issue is on your side or the provider’s side.

AI-Driven Policy Creation

The OPA Policies card includes an AI-powered “Create Policy” modal that helps you write Gatekeeper policies using natural language.

How to Use

  1. Navigate to the Security Posture dashboard
  2. Find the OPA Policies card
  3. Click Create Policy
  4. Describe the policy you want in plain English (e.g., “require all pods to have resource limits”)
  5. AI generates the ConstraintTemplate and Constraint YAML
  6. Review, edit if needed, and apply to selected clusters

Supported Policy Types

  • Resource limits enforcement
  • Label requirements
  • Image registry restrictions
  • Network policy requirements
  • Security context constraints
  • Custom policy logic

GitHub Copilot CLI as Agent Provider

The console supports GitHub Copilot CLI as an AI agent provider alongside Claude and other providers.

Setup

  1. Ensure GitHub Copilot CLI is installed and authenticated
  2. Navigate to Settings > AI & Intelligence > Local Agent
  3. The console auto-detects available providers
  4. Copilot CLI appears as a provider option

Copilot Agents

The console includes refactored Copilot agents (from kagenti skills) that can:

  • Analyze cluster health
  • Review code and configurations
  • Provide security recommendations
  • Assist with deployments

AI Mode Levels

Control how much AI assistance you get:

Low Mode (~10% tokens)

  • AI responds when you ask
  • Direct kubectl commands
  • Best for: Cost control

Medium Mode (~50% tokens)

  • AI analyzes on request
  • Summaries and insights
  • Best for: Balanced usage

High Mode (~100% tokens)

  • Proactive suggestions
  • Auto-analysis of issues
  • Card swap recommendations
  • Best for: Maximum assistance

Changing AI Mode

  1. Go to Settings (/settings)
  2. Find “AI Mode”
  3. Select your preferred level
  4. Changes apply immediately

Token Usage

AI features use tokens, which may have costs. The console tracks usage.

Viewing Token Usage

  • Header bar - Shows percentage used
  • Settings page - Detailed breakdown
  • Mission panel - Per-mission tracking

Token Limits

You can set limits to control costs:

ai:
  tokenLimits:
    enabled: true
    monthlyLimit: 100000
    warningThreshold: 80   # Warn at 80%
    criticalThreshold: 95  # Restrict at 95%

When you hit the warning threshold, you’ll see a notification. At the critical threshold, some AI features are restricted.

Tips for Saving Tokens

  • Use Low or Medium mode for routine work
  • Switch to High mode when troubleshooting
  • Use direct kubectl for simple queries
  • Review mission history to avoid duplicates

Privacy & Safety

What AI Sees

  • Cluster names and namespaces
  • Pod and deployment names
  • Resource metrics
  • Event messages
  • Log snippets (when you share them)

What AI Doesn’t See

  • Your kubeconfig credentials
  • Secrets or sensitive data
  • Personal information
  • Data from other users

Data Handling

  • AI analysis happens through Anthropic’s API
  • According to Anthropic’s data usage policy, data sent via their API is not used to train Anthropic models by default. For details, see Anthropic’s privacy and data usage documentation.
  • Conversations are stored locally
  • You can delete mission history anytime