AI-enabled observability with Red Hat OpenShift Lightspeed

Red Hat OpenShift® Lightspeed provides an AI‑based chat window that understands OpenShift and the current cluster state. When integrated through the Model Context Protocol (MCP), the chat window retrieves live data from the cluster when configured. As a result, responses reflect the current state rather than static documentation. You interact exclusively through the chat window: you submit a query, Lightspeed uses MCP to retrieve the required data, and then explains and summarizes the results. This approach provides a single location for monitoring health, troubleshooting issues, and reviewing summarized information without switching between the OpenShift console and other tools.

One place to ask questions

Use the Lightspeed chat window, either in the OpenShift console or from an IDE through MCP, to ask about cluster health, workloads, and issues. The chat window uses MCP to access live cluster state and, when available, metrics and alerts, providing a consolidated conversational view.

On‑demand debugging and analysis

Ask questions such as What's wrong with the cluster?, Why is this failing?, or Show me what's running in this namespace. The LLM retrieves current data through MCP and combines it with the knowledge of OpenShift to provide focused, context‑aware responses without running anything in the background.

Summarized insights

Request high‑level overviews in plain language, such as Summarize what’s unhealthy or What’s going on in this project? The chat window used MCP to retrieve the relevant resources and return concise summaries, enabling quick triage and deeper investigation only when required.

Integration with existing tools

MCP complements existing monitoring tools rather than replacing them by adding a chat window on top. Continue to use Grafana for dashboards and Prometheus for metrics, while using Lightspeed for quick queries, summaries, and guided troubleshooting based on the same data.