Dashboard design for agent monitoring in Agentic Ai - ML Experiment: Train & Evaluate

Experiment - Dashboard design for agent monitoring

Problem:You have an AI agent system running multiple agents performing tasks. You want to build a dashboard to monitor their status, performance, and alerts in real-time.

Current Metrics:Dashboard currently shows agent names and statuses only. No performance metrics or alert notifications. User feedback says it's hard to track agent health and task progress.

Issue:The dashboard lacks detailed monitoring features, making it difficult to quickly assess agent performance and detect issues.

Your Task

Enhance the dashboard to include real-time performance metrics (like task completion rate, error rate), alert notifications for failures, and visual indicators of agent health.

Use only the existing agent data streams available.

Keep the dashboard responsive and user-friendly.

Do not add backend changes; focus on frontend dashboard design.

Hint 1

Hint 2

Hint 3

Hint 4

Solution

Agentic_ai

import React, { useState, useEffect } from 'react';

function AgentDashboard({ agents }) {
  const [agentData, setAgentData] = useState(agents);

  useEffect(() => {
    const interval = setInterval(() => {
      // Simulate fetching updated agent data
      setAgentData(prev => prev.map(agent => ({
        ...agent,
        taskCompletionRate: Math.min(100, agent.taskCompletionRate + Math.random() * 5),
        errorRate: Math.max(0, agent.errorRate + (Math.random() - 0.5) * 0.1),
        status: agent.errorRate > 0.5 ? 'Error' : 'Healthy'
      })));
    }, 3000);
    return () => clearInterval(interval);
  }, []);

  return (
    <main aria-label="Agent Monitoring Dashboard">
      <h1>Agent Monitoring Dashboard</h1>
      <section>
        {agentData.map(agent => (
          <article key={agent.id} style={{
            border: '1px solid #ccc',
            padding: '1rem',
            marginBottom: '1rem',
            backgroundColor: agent.status === 'Error' ? '#ffe6e6' : '#e6ffe6'
          }} aria-live="polite">
            <h2>{agent.name}</h2>
            <p>Status: <strong>{agent.status}</strong></p>
            <p>Task Completion Rate: {agent.taskCompletionRate.toFixed(1)}%</p>
            <progress value={agent.taskCompletionRate} max={100} aria-label="Task completion progress"></progress>
            <p>Error Rate: {(agent.errorRate * 100).toFixed(1)}%</p>
            {agent.status === 'Error' && <p role="alert" style={{color: 'red'}}>Alert: High error rate detected!</p>}
          </article>
        ))}
      </section>
    </main>
  );
}

// Example usage
const initialAgents = [
  { id: 1, name: 'Agent A', taskCompletionRate: 70, errorRate: 0.1, status: 'Healthy' },
  { id: 2, name: 'Agent B', taskCompletionRate: 85, errorRate: 0.05, status: 'Healthy' },
  { id: 3, name: 'Agent C', taskCompletionRate: 60, errorRate: 0.6, status: 'Error' }
];

export default function App() {
  return <AgentDashboard agents={initialAgents} />;
}

Added task completion rate and error rate metrics for each agent.

Included progress bars to visualize task completion.

Implemented color-coded backgrounds to indicate agent health.

Added alert messages for agents with high error rates.

Set up periodic updates to simulate real-time data refresh.

Results Interpretation

Before: Dashboard showed only agent names and statuses, making it hard to track performance or detect issues.

After: Dashboard displays task completion rates, error rates, color-coded health indicators, and alerts, improving monitoring and quick issue detection.

Adding clear visual metrics and alerts helps users monitor AI agents effectively, reducing the time to spot problems and improving system oversight.

Bonus Experiment

Add filtering and sorting features to the dashboard to allow users to view agents by status or performance metrics.

💡 Hint

Use dropdown menus or buttons to filter agents and sort them by task completion or error rate dynamically.