Endpoint Statistics Application: Docker to Kubernetes Learning Journey

This project is a complete, production-grade example of transitioning a Python Flask application from Docker Compose to a fully monitored, secure, and observable Kubernetes deployment. It includes persistent storage, caching, monitoring, backup, and a robust CI/testing setup.

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For all deployment and testing steps, please follow the detailed instructions in the RUNBOOK.md.

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Project Overview

• Flask API for endpoint access tracking
• PostgreSQL for data persistence
• Redis for caching
• Grafana and Prometheus for monitoring and observability
• Automated dashboard provisioning
• Comprehensive test suite and health checks
• All Kubernetes manifests and scripts included

Current Status (May 2025)

• All components are deployed and managed via Kubernetes (see k8s/)
• Monitoring stack (Prometheus, Grafana) is fully integrated
• Automated dashboard creation and health checks are in place
• All deployment, testing, and troubleshooting steps are maintained in RUNBOOK.md
• Docker Compose setup is still available for local development/learning

Quick Start

Local Docker (for learning)

docker compose up -d
# ...
docker compose run --rm web pytest -v

Kubernetes (Production/Full Stack)

Follow the steps in RUNBOOK.md for all Kubernetes deployment, testing, and troubleshooting.

• Prerequisites: Minikube (or Kind/Docker Desktop), kubectl, Docker
• All manifests are in k8s/ (organized by component)
• Use the Makefile for common tasks (setup, deploy, test, clean)
• Monitoring stack and dashboards are provisioned automatically

Project Structure

• k8s/ — All Kubernetes manifests (core, database, cache, networking, security, storage, maintenance, monitoring)
• scripts/ — Operational scripts (deployment, monitoring, backup, health-check)
• docs/ — Implementation guides and project documentation
• tests/ — Automated tests
• Runbook.md — Main reference for deploying, testing, and managing the cluster

Development & Testing Tools

• Ruff — Python linter/formatter
• pytest — Testing framework
• pre-commit — Git hooks
• commitizen — Commit message formatting

Monitoring & Observability

• Grafana: http://localhost:3000 (default: admin/admin)
• Prometheus: http://localhost:9090
• Dashboards: Automatically provisioned (see Runbook)

Additional Resources

• Kubernetes Documentation
• Kubernetes Cheat Sheet
• Project Structure Guide

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For all Kubernetes deployment and testing, always refer to RUNBOOK.md for the latest, correct, and complete instructions.