AI Agent
AI-powered assistant for investigating, exploring, and building with your groundcover data
groundcover Agent is an AI-powered assistant built into the groundcover platform. Interact with it in natural language to investigate issues, explore your data, create dashboards and monitors, and more - across logs, traces, metrics, events, and entities.
What You Can Do
Investigate Issues
Ask the Agent to diagnose problems across your infrastructure. It queries logs, traces, metrics, and Kubernetes events, then reports what it found and what likely caused the issue.
"Why is the checkout service throwing 500 errors?" "What changed recently in the payments namespace?" "Triage the alert on high-error-rate monitor"
Explore Your Data
Query any signal type using plain language.
"Show me the top 10 error-producing workloads in production" "What are the slowest endpoints in the API gateway?" "Which pods are consuming the most memory?"
Create Dashboards & Monitors
Build production-ready dashboards and monitoring rules from a description.
"Build a dashboard for the payments namespace" "Create a monitor that alerts when error rate exceeds 5% on the checkout service"
Parse & Manage Logs
Generate log parsing rules and drop rules without learning OTTL syntax.
"Parse the unstructured logs from the nginx workload" "Create a drop rule for health check logs"
Navigate the Platform
The Agent can take you to the right page in the groundcover UI with filters already applied.
"Take me to the traces view for the auth service filtered to errors"
Signals
The Agent works across all groundcover signal types:
Logs
Application log lines with level, format, and content
Find error patterns, parse unstructured logs
Traces
Distributed traces with duration, status codes, and service dependencies
Diagnose latency, trace error paths
Metrics
Prometheus-compatible time-series data
Monitor resource usage, track SLIs
Events
Kubernetes events and infrastructure changes (deploys, crashes, scaling)
Correlate changes with incidents
Entities
Live Kubernetes resource state (pods, deployments, nodes, services)
Check current health, find resource issues
Issues
Active and resolved monitor alerts with severity levels
Triage alerts, review incident history
Next Steps
Getting Started - Learn how to interact with the Agent
Example Prompts - Copy-paste prompts for common scenarios
Privacy & Security - Data handling, LLM providers, and opt-out
MCP Integration - Use groundcover as a tool for external AI agents (Cursor, Claude Desktop, etc.)
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