🎨 Monitoring Examples API & UI

Generate realistic monitoring data through APIs or UI with custom parameters.

🚀 Quick Access

UI (Easiest)

http://localhost:3000/monitoring/examples

Features:

✅ Click-to-generate data
✅ 5 predefined scenarios
✅ Custom parameter controls
✅ Real-time preview
✅ One-click clear all data
✅ Visual results dashboard

API (Programmatic)

POST /api/v1/monitoring/examples/generate
DELETE /api/v1/monitoring/examples/clear

📖 Using the UI

Step 1: Navigate to Examples

From monitoring sidebar → Click "Examples" (with "New" badge)

Or go directly: http://localhost:3000/monitoring/examples

Step 2: Choose a Scenario

5 Predefined Scenarios:

Healthy System 🟢
- 95% success rate
- 120ms average latency
- 5% alert rate
- Perfect for demos
Degraded Performance 🟡
- 75% success rate
- 800ms average latency
- 25% alert rate
- Shows mixed conditions
Critical Issues 🔴
- 30% success rate
- 1500ms average latency
- 70% alert rate
- Worst-case scenario
Varied Conditions 🔵
- 70% success rate
- 500ms average latency
- 30% alert rate
- Default/balanced
Custom Configuration 🟣
- Fully customizable
- Control every parameter
- Advanced use cases

Step 3: Configure Data Volume

Use sliders to set:

Number of Monitors: 1-10
Number of Channels: 1-5
Runs per Monitor: 10-100

Example:

5 monitors
40 runs each
= 200 total runs

Step 4: (Optional) Custom Parameters

If you selected "Custom Configuration":

Success Rate: 0-100%
Average Latency: 50-2000ms
Alert Rate: 0-100%

Step 5: Generate Data

Click "Generate Data" button

Wait time: 2-10 seconds depending on volume

You'll see:

✅ Example data generated successfully!

Scenario: Varied Conditions
Monitors Created: 5
Channels Created: 5
Runs Generated: 200
Alerts Created: 42

Success Rate: 68.5%
Avg Latency: 512ms
Active Alerts: 15

Step 6: View Generated Data

Click quick links:

View Runs → /monitoring/runs
View Alerts → /monitoring/alerts
View Channels → /monitoring/channels

Step 7: (Optional) Clear All Data

Click 🗑️ trash button → Confirm → All data deleted

🔌 Using the API

1. Generate Example Data

Endpoint: POST /api/v1/monitoring/examples/generate

Request Body:

{
  "workspace_id": "69ea929e916c52ac2ca53ab5",
  "scenario": "varied",
  "config": {
    "num_monitors": 5,
    "num_channels": 5,
    "num_runs_per_monitor": 40
  }
}

Scenarios:

"healthy" - 95% success
"degraded" - 75% success
"critical" - 30% success
"varied" - 70% success (default)
"custom" - Use custom parameters

Custom Configuration (scenario = "custom"):

{
  "workspace_id": "69ea929e916c52ac2ca53ab5",
  "scenario": "custom",
  "config": {
    "num_monitors": 3,
    "num_channels": 3,
    "num_runs_per_monitor": 50,
    "success_rate": 0.85,
    "avg_latency": 300,
    "alert_rate": 0.15
  }
}

Response (200):

{
  "success": true,
  "message": "Example data generated successfully",
  "summary": {
    "scenario": "Varied Conditions",
    "channels": 5,
    "monitors": 5,
    "runs": 200,
    "alerts": 42,
    "stats": {
      "success_rate": "68.5%",
      "avg_latency": "512ms",
      "active_alerts": 15
    }
  }
}

cURL Example:

curl -X POST http://localhost:3000/api/v1/monitoring/examples/generate \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer <your-token>" \
  -d '{
    "workspace_id": "69ea929e916c52ac2ca53ab5",
    "scenario": "healthy",
    "config": {
      "num_monitors": 5,
      "num_channels": 5,
      "num_runs_per_monitor": 40
    }
  }'

2. Clear All Monitoring Data

Endpoint: DELETE /api/v1/monitoring/examples/clear?workspace_id={id}

Query Parameters:

workspace_id (required): Your workspace ID

Response (200):

{
  "success": true,
  "message": "All monitoring data cleared successfully",
  "deleted": {
    "monitors": 5,
    "runs": 200,
    "alerts": 42,
    "channels": 5
  }
}

cURL Example:

curl -X DELETE \
  "http://localhost:3000/api/v1/monitoring/examples/clear?workspace_id=69ea929e916c52ac2ca53ab5" \
  -H "Authorization: Bearer <your-token>"

📊 What Gets Generated

Monitors (1-10)

Names: "API Health Check", "Authentication Service", etc.
Types: All HTTP
Status: Active
Schedule: Various cron intervals
Regions: us-east-1, us-west-2, eu-west-1
Tags: production, critical, auth, etc.
Assertions: Status code + latency checks

Notification Channels (1-5)

Slack - Production Alerts
Email - DevOps Team
PagerDuty - Critical Incidents
Microsoft Teams - Engineering
Webhook - Custom integration

All have example configurations.

Monitor Runs (10-1000)

Distributed across monitors
Realistic timing data
HTTP request/response details
Waterfall metrics (DNS, TCP, TLS, TTFB)
Assertion results (pass/fail)
Varied statuses based on scenario

Alerts (varies)

Based on failed runs
Different severities (critical, high, medium, low)
Random status (active, acknowledged, resolved)
Linked to notification channels
Realistic trigger times

🎯 Use Cases

1. Demo/Presentation

Scenario: Healthy
Monitors: 5
Runs per Monitor: 20
Total: 100 runs, ~5 failures, ~2 alerts

Shows a well-functioning system.

2. Testing Alert Workflows

Scenario: Critical
Monitors: 3
Runs per Monitor: 30
Total: 90 runs, ~60 failures, ~40 alerts

Lots of alerts to test acknowledge/resolve features.

3. Performance Testing UI

Scenario: Varied
Monitors: 10
Runs per Monitor: 100
Total: 1000 runs, ~300 failures, ~90 alerts

Stress test the UI with large datasets.

4. Custom Simulation

Scenario: Custom
Success Rate: 85%
Latency: 250ms
Alert Rate: 10%

Match your specific requirements.

💡 Tips

For Demos

Use "Healthy" scenario
5 monitors, 20 runs each
Clean, professional data
Few alerts to manage

For Testing

Use "Varied" scenario
5-10 monitors
40-50 runs each
Good mix of conditions

For Development

Start with "Varied"
Generate data once
Test features thoroughly
Clear when done

For Load Testing

Use "Custom" scenario
10 monitors
100 runs each
Test pagination, performance

⚠️ Important Notes

Data Persistence

✅ Generated data persists in MongoDB
✅ Survives server restarts
✅ Accumulates with multiple generations
❌ Must manually clear to remove

Workspace Isolation

✅ Data is workspace-specific
✅ Each workspace has separate data
✅ Clearing only affects current workspace

Resource Usage

Generating 1000 runs takes ~5-10 seconds
Database size: ~1-5 MB per 1000 runs
TTL cleanup: 90 days automatic

Limitations

Max 10 monitors per generation
Max 5 channels per generation
Max 100 runs per monitor per generation
Can generate multiple times to accumulate more

🔧 Troubleshooting

"workspace_id is required"

→ Select a workspace first (top navbar)

Generation takes too long

→ Reduce number of runs (try 20 instead of 100)

UI not showing data

→ Refresh the page or click "View Runs" button

Clear doesn't work

→ Confirm the dialog prompt → Check workspace is selected

API returns 401

→ Check authentication token → Login again to refresh token

📚 Related Documentation

API Examples: MONITORING_API_EXAMPLES.md
Integration Guide: MONITORING_END_TO_END_GUIDE.md
Quick Start: INTEGRATION_SUMMARY.md

🎉 Quick Start

Fastest way to test the monitoring system:

Open http://localhost:3000/monitoring/examples
Keep default settings (Varied, 5 monitors, 40 runs)
Click "Generate Data"
Wait 5 seconds
Click "View Runs"
Explore the monitoring system!

Done! You now have 200 realistic runs to test with.

Last Updated: April 25, 2026
Version: 1.0.0

FilesExpand file tree

MONITORING_EXAMPLES_API.md

Latest commit

History