Agentic AIml~20 mins

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

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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.

Practice

(1/5)

1. What is the main purpose of a dashboard in agent monitoring?

easy

A. To show agent information in one place for easy tracking

B. To write code for agents

C. To delete agents automatically

D. To store agent data permanently

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

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Practice

Solution

Step 1: Understand dashboard role

Step 2: Identify main benefit

Final Answer:

Quick Check:

Solution

Step 1: Check JSON syntax

Step 2: Identify correct option

Final Answer:

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Solution

Step 1: Identify widget type

Step 2: Check metric and agent

Final Answer:

Quick Check:

Solution

Step 1: Identify common cause of empty logs

Step 2: Fix agentId in widget config

Final Answer:

Quick Check:

Solution

Step 1: Understand dashboard modular design

Step 2: Choose best approach for combined info

Final Answer:

Quick Check: