GenAI Meets K8s

1. Komodor Presents: KlaudiaAI
2. Meet Komodor’s Klaudia Why: To keep up with Kubernetes complexity you need to be able to holistically correlate real-time and historic data and understand their ripple effect across the system. What: “Klaudia” identifies the root cause of issues in Kubernetes, and provides meaningful explanations, helping teams understand why issues occur and how to prevent them in the future. How: Klaudia leverages Komodor's comprehensive dataset of past investigation flows, historical changes, events, and metrics. This knowledge base enables precise diagnostics and actionable insights, with AI enhancing our ability to scale across the Kubernetes stack.
3. Klaudia Internal Flow 1. Problem Detection: Komodor identifies a Kubernetes issue 2. Model Selection: Klaudia chooses the most suitable AI model for the specific problem type 3. Autonomous Investigation: Independent root cause analysis agent is launched 4. Iterative Investigation: Agent forms hypotheses and tests them: a. Requests relevant data from Komodor API as needed b. Analyzes new information and refines investigation c. Repeats process, narrowing down to root cause 5. Analysis Completion: Klaudia generates precise root cause analysis, with clear, detailed explanations and actionable next steps 6. Presentation: The findings are displayed to users with supporting evidence
4. Detection MS Investigation Solution Klaudia: Internal Flow
5. Klaudia: Internal Flow Detection Komodor continuously monitors your entire K8s cluster fleet & detects any issues or potential risks.
6. Model Selection Based on the issue detected, Klaudia picks an appropriate model from a catalog of rule engines & LLMs. Klaudia: Internal Flow
7. Klaudia: Internal Flow Investigation The chosen model performs an iterative investigation process until the root cause analysis is fulfilled.
8. Klaudia: Internal Flow Investigation Klaudia provides a clear, detailed RC analysis with actionable next steps to remediate & prevent in the future, as the final stage.
9. 1. A pod failure occurred due to a corrupted key inside a changed ConfigMap. 2. Although the ConfigMap was properly mounted, it contained malformed data. This was not immediately obvious and required deep analysis to diagnose. 3. The GenAI agent took just a couple of seconds to digest logs, historical changes, K8s events, and flag the RC 4. Then provided clear instructions for remediation, including a direct link to the right ConfigMap Scenario from User’s POV:
10. How Do We Compare? We tested the leading K8s AI troubleshooting agents on the market with a simple scenario: A deployment relying on a ConfigMap with an invalid value. Here are the results 👉
11. Only Komodor’s Klaudia correctly detected the root-cause (including supporting evidence) & suggested exact instructions for remediation - Completing the troubleshooting cycle E2E 👇