Introducing Headlamp AI Assistant

Introducing Headlamp AI Assistant Hopping on the AI train Context is everything Tools AI Plugins Try it out! This announcement originally appeared on the Headlamp blog. To simplify Kubernetes management and troubleshooting, we're thrilled to introduce Headlamp AI Assistant : a powerful new plugin for Headlamp that helps you understand and operate your Kubernetes clusters and applications with greater clarity and ease. Whether you're a seasoned engineer or just getting started, the AI Assistant offers: Fast time to value: Ask questions like "Is my application healthy?" or "How can I fix this?" without needing deep Kubernetes knowledge. Deep insights: Start with high-level queries and dig deeper with prompts like "List all the problematic pods" or "How can I fix this pod?" Focused & relevant: Ask questions in the context of what you're viewing in the UI, such as "What's wrong here?" Action-oriented: Let the AI take action for you, like "Restart that deployment" , with your permission. Here is a demo of the AI Assistant in action as it helps troubleshoot an application running with issues in a Kubernetes cluster: Large Language Models (LLMs) have transformed not just how we access data but also how we interact with it. The rise of tools like ChatGPT opened a world of possibilities, inspiring a wave of new applications. Asking questions or giving commands in natural language is intuitive, especially for users who aren't deeply technical. Now everyone can quickly ask how to do X or Y, without feeling awkward or having to traverse pages and pages of documentation like before. Therefore, Headlamp AI Assistant brings a conversational UI to Headlamp , powered by LLMs that Headlamp users can configure with their own API keys. It is available as a Headlamp plugin, making it easy to integrate into your existing setup. Users can enable it by installing the plugin and configuring it with their own LLM API keys, giving them control over which model powers the assistant. Once enabled, the assistant becomes part of the Headlamp UI, ready to respond to contextual queries and perform actions directly from the interface.