Agent Chat for Metrics: Conversational Intelligence for Your Observability Data
Upload dashboards, ask questions in plain English, and get instant AI-powered insights from your metrics data
Imagine being able to ask your monitoring dashboards questions in plain English and getting intelligent, contextual answers instantly. No more scrolling through dozens of panels, no more memorizing PromQL or complex query languages, no more mental gymnastics to correlate different metrics.
That's the power of Agent Chat for Metrics:transforming how teams interact with their observability data.
The Metric Analysis Bottleneck
Modern observability platforms are drowning teams in data. Your Grafana has 200+ dashboards. Each dashboard has 20-50 panels. Each panel requires understanding the underlying query, units, baseline behavior, and relationships to other metrics.
Common Frustrations
- →"Which service is causing this spike in error rates?"
- →"Show me CPU trends compared to last week"
- →"What's the P99 latency pattern during peak hours?"
- →"Is this memory growth normal or a leak?"
Each question requires opening multiple dashboards, correlating data manually, and mental calculation. Agent Chat answers them in seconds.
How Agent Chat for Metrics Works
Step 1: Upload Your Dashboard
Import any Grafana dashboard URL or JSON. Agent Chat immediately understands all the metrics, their relationships, and what they represent.
-d '{ "dashboard_url": "grafana.example.com/d/..." }'
Step 2: Ask Questions Naturally
No query language needed. Ask in plain English like you would a colleague. The AI understands context, time ranges, comparisons, and metric relationships.
Step 3: Get Contextual Insights
Agent Chat doesn't just answer it provides context, identifies anomalies, suggests correlations, and explains significance.
Real-World Use Cases
Incident Investigation
"Compare current CPU usage to the same time last week across all pods" instantly identify which services are behaving abnormally.
Capacity Planning
"Show me disk usage growth rate for the database cluster" get projected full dates and recommendations.
Performance Optimization
"Which endpoints have the highest P99 latency?" quickly identify optimization targets.
Business Metrics
"Correlate checkout errors with revenue impact" understand business impact of technical issues.
The Impact on Your Team
Under the Hood: How It Works
Agent Chat combines multiple AI techniques to deliver accurate, contextual answers:
1. Dashboard Schema Understanding
Parses Grafana JSON to extract metrics, labels, units, and panel relationships. Builds a knowledge graph of your observability landscape.
2. Natural Language Processing
Converts your English questions into precise metric queries. Understands time expressions, comparisons, aggregations, and filters naturally.
3. Context-Aware Analysis
Maintains conversation history to understand follow-up questions. "What about yesterday?" knows you're referring to the previous metric you asked about.
4. Anomaly Detection
Automatically compares current values to historical baselines. Highlights unusual patterns without you having to ask.
Transform Your Metrics Analysis Today
Stop wrestling with query languages and complex dashboards. Start having conversations with your metrics.
Shafi Khan
Founder & CEO, AutonomOps AI
Building the future of autonomous site reliability engineering. Former AI/ML leader at VMware, passionate about eliminating toil and letting engineers focus on what matters.