K8sGPT

K8sGPT: AI-Powered Kubernetes Troubleshooting

What is K8sGPT?

K8sGPT is an open-source tool that uses AI to diagnose and fix issues in Kubernetes clusters. It aims to give Kubernetes superpowers to everyone by providing intelligent insights and automated troubleshooting.

Key Features of K8sGPT

• AI-Powered Analysis: Utilizes advanced AI algorithms to analyze the state of your Kubernetes cluster and provides intelligent insights for troubleshooting.
• Data Anonymization: Automatically anonymizes sensitive data before sending it to AI backends for analysis, ensuring data privacy.
• Multiple AI Providers: Supports various AI providers, including OpenAI, Azure OpenAI, Google Vertex AI, Amazon Bedrock, IBM WatsonX, and local AI models like Ollama, Cohere, and Hugging Face.
• Auto Remediation: Automatically applies suggested fixes to common Kubernetes issues, reducing manual intervention and speeding up recovery. This feature can be toggled on or off, giving users control over the automation.
• Claude Desktop Integration: Seamlessly integrates with Claude Desktop for enhanced Kubernetes management, providing a native CLI experience and leveraging Claude's advanced AI capabilities.
• AI-Free Analysis: Allows users to run built-in analyzers locally without involving any AI backend for simple diagnostics.
• Selective Analyzers: Enables users to choose precisely which analyzers to run, focusing only on the areas they need.

How does K8sGPT work?

K8sGPT analyzes Kubernetes cluster states using AI algorithms to identify potential issues. It then provides insights and suggests fixes, which can be automatically applied if auto-remediation is enabled. The tool supports multiple AI providers, allowing users to choose the one that best fits their needs. Sensitive data is anonymized before being sent to external AI backends, ensuring data privacy.

How to use K8sGPT?

1. Installation: Install K8sGPT on your system.
2. Configuration: Configure K8sGPT to connect to your Kubernetes cluster and AI provider of choice.
3. Analysis: Run K8sGPT to analyze your cluster state and identify potential issues.
4. Remediation: Apply suggested fixes automatically or manually, depending on your configuration.

Why choose K8sGPT?

• Efficiency: Automates the troubleshooting process, reducing the time and effort required to diagnose and fix Kubernetes issues.
• Intelligence: Provides intelligent insights based on AI analysis, helping users understand the root cause of issues.
• Flexibility: Supports multiple AI providers and allows users to control the level of automation.
• Privacy: Anonymizes sensitive data before sending it to external AI backends, ensuring data privacy.
• Community Support: Offers a growing community of users and contributors, providing support and resources.

Who is K8sGPT for?

K8sGPT is ideal for:

• Kubernetes administrators: Simplifies the troubleshooting process and reduces the time and effort required to manage Kubernetes clusters.
• Developers: Provides intelligent insights into the state of their applications running on Kubernetes, helping them identify and fix issues quickly.
• DevOps engineers: Automates the troubleshooting process, enabling them to focus on other tasks.

Supported AI Providers

• OpenAI
• Azure OpenAI
• Google Vertex AI
• Amazon Bedrock
• IBM WatsonX
• Local AI (Ollama, Cohere, Hugging Face)

Fine-Grained Control & Guardrails

K8sGPT puts you in control, allowing you to tailor analysis and remediation to your needs.

• Toggle Auto-Remediation: You decide if K8sGPT should automatically apply suggested fixes.
• AI-Free Analysis: Run built-in analyzers locally without involving any AI backend for simple diagnostics.
• Selective Analyzers: Choose precisely which analyzers to run, focusing only on the areas you need.
• Data Anonymization: Sensitive data is automatically anonymized before being sent to external AI backends.
• Local AI Models: Keep your data entirely within your environment by using supported local AI models.

By using K8sGPT, teams can significantly improve their Kubernetes management and troubleshooting workflows, leading to more stable and efficient deployments.