📊 Monitoring Stack Interactive Demo

Experience real-time observability with Prometheus, Grafana, and AlertManager

🚀 Demo Scenarios

1

System Overview

Monitor CPU, memory, disk, and network metrics

2

Application Performance

Track response times, error rates, and throughput

3

Alert Simulation

Trigger and resolve monitoring alerts

4

Custom Queries

Execute PromQL queries and analyze results

🎮 Demo Controls

📈 Live Status

Prometheus
Grafana
AlertManager
📊 Grafana Dashboard - System Monitoring
CPU Usage
45%
+2.1%
Memory Usage
67%
-1.5%
Disk I/O
1.2K
+150
Network Traffic
45MB/s
+5.2MB/s
Response Time Distribution
📈
Real-time response time chart
P95: 245ms | P99: 890ms
Error Rate by Service
⚠️
Error rate monitoring
API: 0.02% | DB: 0.01% | Cache: 0.00%
🚨 Active Alerts
High memory usage on web-01
2m ago
Slow response time on API endpoint
5m ago
📈 Prometheus Query Interface
CPU Usage Query
rate(cpu_usage_percent[5m]) * 100
cpu_usage_percent{instance="web-01"} 45.23
cpu_usage_percent{instance="web-02"} 42.18
cpu_usage_percent{instance="db-01"} 67.89
HTTP Request Rate
sum(rate(http_requests_total[5m])) by (status_code)
{status_code="200"} 1247
{status_code="404"} 23
{status_code="500"} 2
Memory Usage Trend
memory_usage_bytes / memory_total_bytes * 100
memory_usage_percent{instance="web-01"} 67.45
memory_usage_percent{instance="web-02"} 71.23
memory_usage_percent{instance="db-01"} 82.67
Error Rate Alert
rate(http_requests_total{status_code=~"5.."}[5m]) / rate(http_requests_total[5m]) * 100 > 1
ALERTS{alertname="HighErrorRate", severity="warning"} 1
⚠️ Alert triggered: Error rate above 1%