🐕 K8 Monitoring Simulation Data with Loki, Prometheus & Grafana

🚀 Overview

This guide explains how to set up Loki, Prometheus, and Grafana using Kubernetes to monitor CPU load data from a Python application locally.

🔹 Prometheus - Scrapes metrics from the app
🔹 Loki - Collects & indexes logs
🔹 Grafana - Visualizes the data

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📌 Prerequisites

Ensure you have the following installed:

• Docker & Docker Compose
• Colima (for Mac users)
• kind
• kubectl

If Mac user run the following script to install the tools:

brew install colima
colima start
brew install kind
brew install kubectl

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🚀 Start the Monitoring Stack

With Docker Compose or kind

Run the following command to build and start the services:

For non-K8 deployment:

docker compose up --build

or

For K8 deployment:

bash kind-setup.sh

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📊 Connect Grafana to Prometheus

1. Open Grafana UI → http://localhost:3000

2. Login with:

   • Username: admin
   • Password: admin

3. Navigate to "Configuration" > "Data Sources"

4. Click "Add Data Source" and select Prometheus

5. Set the URL:

   http://prometheus:9090
   

6. Click "Save & Test" 🎯

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📈 Create a Grafana Dashboard

1. Go to "Create" > "Dashboard"

2. Click "Add a new panel"

3. In the Metrics section, enter:

   cpu_load
   

4. Click "Run query" to visualize CPU load

5. Customize the graph, then click "Save" ✅

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📜 Configure Loki for Log Monitoring

1. Navigate to "Logs" in Grafana

2. Select "Loki" as the "Data Source"

3. Set the URL:

   http://loki:3100
   

4. Run a log query to filter logs:

   {app="sanitised-data"}
   

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🎉 Done!

Your sanitised-data service is now fully monitored with Prometheus, Loki & Grafana! 🚀

✅ Metrics → Tracked via Prometheus
✅ Logs → Indexed with Loki
✅ Visualization → Displayed in Grafana

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