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📊 Guide: Setting Up Grafana for Benchmarking Visualization

This guide walks you through setting up Grafana to monitor and visualize results from performance benchmarking, including metrics like latency percentiles, throughput, CPU, memory, and I/O. It’s designed for engineers benchmarking databases, services, or systems under load.

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🧱 Requirements

Tool	Purpose
Grafana	Visualization layer
Prometheus	Metrics time-series database
Node Exporter	Captures CPU, memory, disk stats
Your Benchmark Tool	Emits custom metrics (e.g., K6, wrk, custom script)

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1. 🔧 Set Up Prometheus + Node Exporter

1.1 Install Prometheus

docker run -d \
  --name=prometheus \
  -p 9090:9090 \
  -v $(pwd)/prometheus.yml:/etc/prometheus/prometheus.yml \
  prom/prometheus

1.2 Sample prometheus.yml

global:
  scrape_interval: 5s

scrape_configs:
  - job_name: 'node'
    static_configs:
      - targets: ['localhost:9100']

1.3 Run Node Exporter (on target machine)

docker run -d \
  --name=node-exporter \
  -p 9100:9100 \
  prom/node-exporter

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2. 📦 Set Up Grafana

docker run -d \
  --name=grafana \
  -p 3000:3000 \
  grafana/grafana

• Access Grafana at http://localhost:3000
• Default login: admin / admin

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3. ➕ Add Prometheus as a Data Source in Grafana

1. Go to Settings > Data Sources > Add data source
2. Select Prometheus
3. URL: http://prometheus:9090
4. Click Save & Test

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4. 📊 Import a Benchmark Dashboard

Dashboard Template JSON

{
  "title": "Benchmark Performance Dashboard",
  "panels": [
    {
      "title": "Latency (P95)",
      "type": "timeseries",
      "targets": [
        {
          "expr": "histogram_quantile(0.95, rate(request_latency_bucket[1m]))",
          "legendFormat": "P95 Latency"
        }
      ]
    },
    {
      "title": "Throughput (RPS)",
      "type": "timeseries",
      "targets": [
        {
          "expr": "rate(request_count_total[1m])",
          "legendFormat": "Requests/sec"
        }
      ]
    },
    {
      "title": "CPU Usage (%)",
      "type": "timeseries",
      "targets": [
        {
          "expr": "100 - avg(irate(node_cpu_seconds_total{mode=\"idle\"}[1m])) * 100",
          "legendFormat": "CPU %"
        }
      ]
    },
    {
      "title": "Memory Usage",
      "type": "timeseries",
      "targets": [
        {
          "expr": "node_memory_MemTotal_bytes - node_memory_MemAvailable_bytes",
          "legendFormat": "Used Memory"
        }
      ]
    }
  ]
}

How to Import

1. Go to Grafana > Dashboards > Import
2. Paste the above JSON
3. Select Prometheus as the data source
4. Click Import

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5. 📡 Emit Custom Metrics (Optional)

If you're using a custom benchmark tool, emit metrics to a Pushgateway or expose an endpoint Prometheus can scrape.

# Example Prometheus metric format (text/plain)
request_latency_seconds_bucket{le="0.01"}  52
request_latency_seconds_bucket{le="0.05"}  107
request_latency_seconds_bucket{le="0.1"}   151
request_latency_seconds_count  180
request_latency_seconds_sum    7.39

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6. 📈 What to Track

Metric	Prometheus Query Example
P95 latency	histogram_quantile(0.95, rate(latency_bucket[1m]))
Throughput	rate(request_count_total[1m])
CPU %	100 - avg(rate(node_cpu_seconds_total{mode="idle"}[1m])) * 100
Memory used	node_memory_MemTotal_bytes - node_memory_MemAvailable_bytes
Disk I/O (reads)	rate(node_disk_reads_completed_total[1m])

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✅ Tips for Reliable Dashboards

• Add annotations for load test start/end times
• Tag data with build version, commit hash, or run ID
• Export dashboards via JSON for version control
• Create alert rules (e.g. P95 > threshold)

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📚 Resources

• Grafana Docs
• Prometheus Docs
• Node Exporter Metrics Reference
• Grafana Loki for logs alongside metrics

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📦 Appendix: Docker Compose Setup for Grafana Benchmarking Stack

version: "3.8"

services:
  prometheus:
    image: prom/prometheus
    container_name: prometheus
    ports:
      - "9090:9090"
    volumes:
      - ./prometheus/prometheus.yml:/etc/prometheus/prometheus.yml
      - prometheus_data:/prometheus
    networks:
      - monitoring

  grafana:
    image: grafana/grafana
    container_name: grafana
    ports:
      - "3000:3000"
    environment:
      - GF_SECURITY_ADMIN_USER=admin
      - GF_SECURITY_ADMIN_PASSWORD=admin
    volumes:
      - grafana_data:/var/lib/grafana
    depends_on:
      - prometheus
    networks:
      - monitoring

  node-exporter:
    image: prom/node-exporter
    container_name: node_exporter
    ports:
      - "9100:9100"
    networks:
      - monitoring

volumes:
  prometheus_data:
  grafana_data:

networks:
  monitoring:

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📄 Sample prometheus.yml

Save as ./prometheus/prometheus.yml:

global:
  scrape_interval: 5s

scrape_configs:
  - job_name: 'prometheus'
    static_configs:
      - targets: ['prometheus:9090']

  - job_name: 'node_exporter'
    static_configs:
      - targets: ['node-exporter:9100']

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▶️ How to Run

docker compose up -d

• Prometheus: http://localhost:9090
• Grafana: http://localhost:3000
  • Username: admin, Password: admin
• Node Exporter Metrics: http://localhost:9100/metrics

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