Blog Series Structure

๐Ÿงฑ Part 1: Introduction + Project Overview

  • What we are building and why

  • Why Kubernetes for PostgreSQL?

  • DevOps skills we'll learn: GitHub Actions, KIND, K8s, S3 backups, CI/CD

  • System Architecture (Diagram)

โš™๏ธ Part 2: Setting Up KIND for Kubernetes

  • Why KIND over Minikube

  • Installing Docker + KIND + kubectl

  • Creating your first KIND cluster

  • Deploying PostgreSQL StatefulSet

  • Verifying pods, services, PVC

๐Ÿ” Part 3: PostgreSQL + CronJob + S3 Backups

  • Write backup script using pg_dump

  • Mount volumes in CronJob

  • Configure AWS S3 using IAM and environment secrets

  • Test backup flow

  • Log backup results in a โ€œbackup_logsโ€ table

๐ŸŒ Part 4: FastAPI Backend for Real-Time Status

  • REST API to expose:

    • Last backup time

    • Disk usage

    • Active connections

  • Containerize and deploy on Kubernetes

  • Expose using Ingress or NodePort

๐ŸŽจ Part 5: Public Dashboard with React

  • Create frontend dashboard

  • Connect to FastAPI backend

  • Deploy on Render

  • Make it accessible to recruiters

๐Ÿš€ Part 6: CI/CD with GitHub Actions

  • Auto-deploy manifests to KIND using kubectl

  • Local CI testing for Dockerfiles, Linting, etc.

  • Optional GitHub environment secrets

๐Ÿ“ˆ Part 7 (Optional): Add Monitoring with Grafana + Prometheus

  • Monitor PostgreSQL pod

  • Visualize memory/CPU/disk trends

  • Add charts to frontend


๐Ÿ’ผ Ready Project Build Plan

๐Ÿ“Œ Core Features Checklist

FeatureStatus
PostgreSQL StatefulSet on KINDโœ… Planned
PVC & Headless Serviceโœ… Planned
S3 CronJob Backup Integrationโœ… Planned
FastAPI Status REST APIโœ… Planned
React.js Public Dashboardโœ… Planned
KIND Support Instead of Minikubeโœ… Updated
GitHub Actions CI/CDโœ… Planned
K8s Manifests Only (No Helm)โœ… Preferred
Optional Prometheus Monitoring๐Ÿ” Optional

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Written by

Digpal Singh Rathore
Digpal Singh Rathore

Cloud Engineer passionate about automation, scalability, and AI. On a journey to become an MLOps Engineerโ€”bridging the gap between machine learning and reliable deployment. Sharing what I learn along the way.