DEV Community: VIJAY MANDA

I Built a Free Hybrid Kubernetes Homelab Using My Laptop + Oracle Cloud

VIJAY MANDA — Wed, 22 Jul 2026 14:26:28 +0000

Jul 22

I Built a Free Hybrid Kubernetes Homelab Using My Laptop + Oracle Cloud (Here's My Setup)

3 min read

I Built a Free Hybrid Kubernetes Homelab Using My Laptop + Oracle Cloud (Here's My Setup)

VIJAY MANDA — Wed, 22 Jul 2026 14:24:06 +0000

Over the last few weeks, I've been building a Kubernetes homelab that I can use to learn platform engineering, observability, storage, security, and cloud-native tooling.

I didn't want to spend money on extra hardware, so I tried to build something practical using what I already had.

The result is a hybrid Kubernetes cluster running across my laptop and Oracle Cloud's Always Free tier.

It isn't meant to replace production infrastructure. It's simply a place where I can safely experiment, break things, recover them, and understand how different components work together.

Why I built it

At work, I regularly use Kubernetes, AWS, Terraform, GitLab CI/CD, and other DevOps tools.

But production environments don't always give you the freedom to test new ideas.

Sometimes you just want to ask questions like:

What happens if the control plane goes down?
How does persistent storage recover?
How does Prometheus store metrics?
How does Loki collect logs?
What does Falco actually detect?
How does Trivy scan workloads?
Can I access everything securely without exposing ports to the internet?

A homelab is the perfect place to answer those questions.

Hardware

vijaymanda@vijay-ubuntu:~$ kubectl get nodes NAME STATUS ROLES AGE VERSION k8s-worker-1 Ready <none> 8d v1.30.14 k8s-worker-2 Ready <none> 8d v1.30.14 vijay-ubuntu Ready control-plane 8d v1.31.14

I intentionally kept the infrastructure simple.

Control Plane

Ubuntu Laptop
AMD Ryzen 5 5500U
16 GB RAM
512 GB SSD

This machine runs:

Kubernetes Control Plane
etcd
kube-apiserver
kube-scheduler
kube-controller-manager

Worker Nodes

Oracle Cloud Always Free provides two ARM virtual machines, which fit perfectly as worker nodes.

Both VMs are:

VM.Standard.A1.Flex
1 OCPU
6 GB RAM

That gave me a small but capable three-node cluster without paying for additional hardware.

Networking

For Kubernetes networking I'm using:

Calico

For secure remote access:

Tailscale
MagicDNS

`
This lets me reach Grafana, Prometheus, Longhorn, Open WebUI and other internal services from anywhere without exposing them publicly.

Storage

Persistent storage is handled by Longhorn.

Stateful applications store their data on Longhorn volumes, including:

Grafana
Prometheus
Alertmanager
Loki
Open WebUI

I tested this by rebooting my control plane and verifying that the applications came back with their data intact.

Monitoring

The monitoring stack includes:

Prometheus
Grafana
Alertmanager
kube-state-metrics
Node Exporter

This gives me visibility into:

Cluster health
Node health
Resource usage
Pod status
Alerts

Slack notifications are configured through Alertmanager so I receive alerts outside the cluster.

Logging

For centralized logging I deployed:

Grafana Alloy
Loki

Every Kubernetes pod forwards its logs into Loki, making it much easier to troubleshoot applications from a single place instead of connecting to individual nodes.

Security

I wanted security to be part of the platform instead of something added later.

I'm currently using:

Falco

Detects runtime security events happening inside the cluster.

Trivy Operator

Continuously scans Kubernetes workloads and generates vulnerability reports for container images.

What I learned

This project taught me much more than simply installing Kubernetes.

I learned how different pieces fit together.

Monitoring, logging, storage, networking, security, and remote access all become much easier to understand once you build them yourself and troubleshoot them when something breaks.

One of the biggest lessons was persistence.

Initially, Grafana was using ephemeral storage, which meant dashboards disappeared after restarting the pod.

After migrating Grafana, Prometheus, and Alertmanager to Longhorn persistent volumes, the platform became much more resilient.

What's next

I'm planning to continue expanding this lab by exploring:

Better dashboard provisioning
GitOps workflows
AI-assisted Kubernetes operations
More production-style automation

GitHub Repo: kubernetes-self-hosted-home-lab

Final thoughts

This cluster isn't intended to be "production ready."

It's simply my playground for learning Kubernetes by actually running it.

Building it has taught me far more than following tutorials because every mistake forced me to understand how Kubernetes behaves under real conditions.

If you're learning Kubernetes, you don't need an expensive rack of servers.

A laptop and Oracle Cloud's free ARM instances are enough to build something surprisingly capable.

How I Practice Cloud and DevOps Labs Without Expensive Setup

VIJAY MANDA — Thu, 21 May 2026 06:07:29 +0000

You don't need expensive hardware for daily labs if you're into Cloud, DevOps, or SRE.

1. Cloud Free Trial (AWS)

Personally, I use AWS.
When you sign up, you get $100 in free credits.
After logging into the AWS Console, go to the Home page and look for "Explore AWS" and select "Earn AWS Credits". These credits are valid for one year.
Most of the tasks take around 10 to 15 minutes to complete, and each task rewards you with $20 in credits.

Pro Tip:
Don't jump directly into NAT Gateways, EKS clusters, or other expensive services.
Start small.
Create multiple tiny VMs using Infrastructure as Code, connect them together, and practice real-world scenarios.
Once you're done, shut them down. Don't leave resources running 24/7 unless necessary.
You can also try Azure Free Trial and GCP Free Tier.

2. Free Labs from Udemy Business

Another great option is Udemy Business access through your organization email.
Many companies provide it for free to employees.
You get access to hands-on labs that run in real sandbox cloud environments.
What I personally like about these labs is they are not just empty sandboxes.
Most of them are designed around real production-style tasks.

3. If you're preparing for CKA, CKAD, or CKS, check these platforms as well.

KodeKloud Labs
https://kodekloud.com/studio/labs

KillerCoda
https://killercoda.com/

iximiuz Labs
https://labs.iximiuz.com/

These platforms are really good for hands-on Kubernetes practice.
You get browser-based labs where you can work directly on clusters, troubleshoot issues, practice YAMLs, networking, RBAC, storage, and other real exam-style scenarios without needing a powerful local machine.

devops #kubernetes #aws #cloudcomputing #sre

Understanding the CI/CD Pipeline.

VIJAY MANDA — Fri, 28 Feb 2025 17:45:03 +0000

Lets talk about CI/CD Pipeline.

VIJAY MANDA ・ Feb 28

#devops #cicd #azure #cloud

Take Control of Your VMs: Automating Deployments with PowerCLI in vCenter server.

VIJAY MANDA — Sat, 05 Oct 2024 10:19:17 +0000

Tired of manually creating virtual machines in VMware? It's a tedious process, especially when you need to spin up multiple VMs. PowerCLI, the command-line tool designed for managing VMware vSphere, has your back! Let's dive into a script that automates VM creation, either from scratch or using pre-built templates.

Breaking Down the Script
This script is structured in a logical way to make it easy to use:

Connect to Your vCenter: First things first, the script will ask for your vCenter Server's IP address or hostname, your username, and password. This establishes the connection to your VMware environment.
Set Your VM Parameters: Next, you get to customize your VM deployment:

How many VMs? Tell the script how many you need.
Where do they live? Specify the datastore, folder, and cluster for your VMs.
What do they look like? Define a naming convention with a prefix.
Speed is key? Choose if you want to create them asynchronously for faster deployment.
Template or fresh start? Decide if you're using a template and provide its name.
Ready to roll? Choose whether to power on the VMs automatically.

New VM Specifics (Optional): If you're not using a template, you'll need to provide some extra details:

Processing power: Set the number of CPUs.
Memory Muscle: Specify RAM size in MB.
Storage Space: Determine the disk size in MB.
Disk Type: Choose thin, thick, or eagerZeroedThick provisioning.
Operating System: Select the guest OS for your VMs.

Requirements

1. ESXI HOST

2. vCenter Server

## Code
[]https://github.com/vijaymanda06/Virtual-Machine-Deployment-Script