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When alerts trigger, Ankra’s AI automatically analyzes your cluster to identify the root cause, affected resources, and recommended actions.

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What are AI Incidents?

AI Incidents are automatically generated when an alert triggers. Ankra’s AI system:
  1. Collects cluster data - Gathers pods, events, logs, and resource status
  2. Analyzes the situation - Uses AI to identify what went wrong and why
  3. Provides actionable insights - Delivers a summary, root cause, and recommended fixes
This helps you diagnose issues faster without manually digging through logs and events.

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How AI Analysis Works

When an alert fires, Ankra automatically creates resources and jobs to analyze the issue.

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Resource and Job Creation

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Analysis Phases

The analysis progresses through these phases: If something goes wrong during analysis, the status will show as Failed with an error message.

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Data Collected

During the Collecting phase, the analysis job gathers:

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AI Processing

During the Analyzing phase, Ankra’s AI:
  1. Identifies patterns - Recognizes common failures (CrashLoopBackOff, OOMKilled, ImagePullBackOff)
  2. Correlates data - Connects events, logs, and status to find root cause
  3. Assesses severity - Determines impact level (critical, warning, info)
  4. Generates recommendations - Creates actionable steps with Ankra UI links

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Viewing AI Analysis

Click on any incident in the AI Incidents tab to open the analysis modal. The analysis includes:

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Quick Summary

A brief, AI-generated overview of the issue. This gives you the key information at a glance so you can quickly understand what happened.

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Root Cause

A detailed explanation of what caused the alert to trigger. This section identifies the underlying problem, not just the symptoms.

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Key Insights

Important observations about the incident, categorized by type:
  • Resource insights - Issues with specific Kubernetes resources
  • Performance insights - CPU, memory, or latency problems
  • Timing insights - When issues started and patterns over time
  • Error insights - Specific errors found in logs or events

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Affected Resources

A list of Kubernetes resources impacted by the incident. Click on any resource to navigate directly to it in your cluster view. An interactive checklist of steps to resolve the issue. Mark items as complete as you work through them to track your progress.

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Full Analysis

Expandable section containing the complete, detailed analysis. Use this when you need more context than the summary provides.

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Starting a Conversation with AI

After reviewing an analysis, click Start Conversation with AI to continue investigating. This opens the AI Assistant with the incident context already loaded, so you can:
  • Ask follow-up questions about the root cause
  • Get more specific remediation steps
  • Explore related issues in your cluster
  • Request help implementing the recommended actions

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Filtering and Searching Incidents

The AI Incidents tab provides filters to help you find specific incidents: Search across alert names, rule names, cluster names, resource names, and root cause text.

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Severity Filter

Filter by incident severity:

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Status Filter

Filter by analysis status:

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Incident Details

Each incident in the table shows: Click View on any incident to open the full analysis.

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Best Practices

Review Critical incidents first: Use the severity filter to prioritize your response to the most impactful issues.
Use the checklist: Work through recommended actions systematically and mark them complete to track progress.
Continue with AI: If the initial analysis doesn’t fully explain the issue, start a conversation to dig deeper.
Check affected resources: Navigate to affected resources directly from the analysis to verify the current state.
  • Alerts - Configure alert rules that generate AI incidents
  • AI Assistant - Learn more about Ankra’s AI capabilities
Still have questions? Join our Slack community and we’ll help out.